Clinical Presentation of COVID-19: Case Series and Review of the Literature

Affiliation.

  • 1 Department of Mental health and Public Medicine, University of Campania, 80131 Naples, Italy.
  • PMID: 32674450
  • PMCID: PMC7399865
  • DOI: 10.3390/ijerph17145062

COVID-19 infection has a broad spectrum of severity ranging from an asymptomatic form to a severe acute respiratory syndrome that requires mechanical ventilation. Starting with the description of our case series, we evaluated the clinical presentation and evolution of COVID-19. This article is addressed particularly to physicians caring for patients with COVID-19 in their clinical practice. The intent is to identify the subjects in whom the infection is most likely to evolve and the best methods of management in the early phase of infection to determine which patients should be hospitalized and which could be monitored at home. Asymptomatic patients should be followed to evaluate the appearance of symptoms. Patients with mild symptoms lasting more than a week, and without evidence of pneumonia, can be managed at home. Patients with evidence of pulmonary involvement, especially in patients over 60 years of age, and/or with a comorbidity, and/or with the presence of severe extrapulmonary manifestations, should be admitted to a hospital for careful clinical-laboratory monitoring.

Keywords: COVID-19; SARS-CoV-2; clinical presentation; natural history.

Publication types

  • Betacoronavirus / isolation & purification*
  • Comorbidity
  • Coronavirus Infections / complications
  • Coronavirus Infections / pathology*
  • Coronavirus Infections / virology
  • Middle Aged
  • Pneumonia, Viral / complications
  • Pneumonia, Viral / pathology*
  • Pneumonia, Viral / virology
  • Research Design
  • Respiration, Artificial
  • Research article
  • Open access
  • Published: 04 June 2021

Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews

  • Israel Júnior Borges do Nascimento 1 , 2 ,
  • Dónal P. O’Mathúna 3 , 4 ,
  • Thilo Caspar von Groote 5 ,
  • Hebatullah Mohamed Abdulazeem 6 ,
  • Ishanka Weerasekara 7 , 8 ,
  • Ana Marusic 9 ,
  • Livia Puljak   ORCID: orcid.org/0000-0002-8467-6061 10 ,
  • Vinicius Tassoni Civile 11 ,
  • Irena Zakarija-Grkovic 9 ,
  • Tina Poklepovic Pericic 9 ,
  • Alvaro Nagib Atallah 11 ,
  • Santino Filoso 12 ,
  • Nicola Luigi Bragazzi 13 &
  • Milena Soriano Marcolino 1

On behalf of the International Network of Coronavirus Disease 2019 (InterNetCOVID-19)

BMC Infectious Diseases volume  21 , Article number:  525 ( 2021 ) Cite this article

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Navigating the rapidly growing body of scientific literature on the SARS-CoV-2 pandemic is challenging, and ongoing critical appraisal of this output is essential. We aimed to summarize and critically appraise systematic reviews of coronavirus disease (COVID-19) in humans that were available at the beginning of the pandemic.

Nine databases (Medline, EMBASE, Cochrane Library, CINAHL, Web of Sciences, PDQ-Evidence, WHO’s Global Research, LILACS, and Epistemonikos) were searched from December 1, 2019, to March 24, 2020. Systematic reviews analyzing primary studies of COVID-19 were included. Two authors independently undertook screening, selection, extraction (data on clinical symptoms, prevalence, pharmacological and non-pharmacological interventions, diagnostic test assessment, laboratory, and radiological findings), and quality assessment (AMSTAR 2). A meta-analysis was performed of the prevalence of clinical outcomes.

Eighteen systematic reviews were included; one was empty (did not identify any relevant study). Using AMSTAR 2, confidence in the results of all 18 reviews was rated as “critically low”. Identified symptoms of COVID-19 were (range values of point estimates): fever (82–95%), cough with or without sputum (58–72%), dyspnea (26–59%), myalgia or muscle fatigue (29–51%), sore throat (10–13%), headache (8–12%) and gastrointestinal complaints (5–9%). Severe symptoms were more common in men. Elevated C-reactive protein and lactate dehydrogenase, and slightly elevated aspartate and alanine aminotransferase, were commonly described. Thrombocytopenia and elevated levels of procalcitonin and cardiac troponin I were associated with severe disease. A frequent finding on chest imaging was uni- or bilateral multilobar ground-glass opacity. A single review investigated the impact of medication (chloroquine) but found no verifiable clinical data. All-cause mortality ranged from 0.3 to 13.9%.

Conclusions

In this overview of systematic reviews, we analyzed evidence from the first 18 systematic reviews that were published after the emergence of COVID-19. However, confidence in the results of all reviews was “critically low”. Thus, systematic reviews that were published early on in the pandemic were of questionable usefulness. Even during public health emergencies, studies and systematic reviews should adhere to established methodological standards.

Peer Review reports

The spread of the “Severe Acute Respiratory Coronavirus 2” (SARS-CoV-2), the causal agent of COVID-19, was characterized as a pandemic by the World Health Organization (WHO) in March 2020 and has triggered an international public health emergency [ 1 ]. The numbers of confirmed cases and deaths due to COVID-19 are rapidly escalating, counting in millions [ 2 ], causing massive economic strain, and escalating healthcare and public health expenses [ 3 , 4 ].

The research community has responded by publishing an impressive number of scientific reports related to COVID-19. The world was alerted to the new disease at the beginning of 2020 [ 1 ], and by mid-March 2020, more than 2000 articles had been published on COVID-19 in scholarly journals, with 25% of them containing original data [ 5 ]. The living map of COVID-19 evidence, curated by the Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre), contained more than 40,000 records by February 2021 [ 6 ]. More than 100,000 records on PubMed were labeled as “SARS-CoV-2 literature, sequence, and clinical content” by February 2021 [ 7 ].

Due to publication speed, the research community has voiced concerns regarding the quality and reproducibility of evidence produced during the COVID-19 pandemic, warning of the potential damaging approach of “publish first, retract later” [ 8 ]. It appears that these concerns are not unfounded, as it has been reported that COVID-19 articles were overrepresented in the pool of retracted articles in 2020 [ 9 ]. These concerns about inadequate evidence are of major importance because they can lead to poor clinical practice and inappropriate policies [ 10 ].

Systematic reviews are a cornerstone of today’s evidence-informed decision-making. By synthesizing all relevant evidence regarding a particular topic, systematic reviews reflect the current scientific knowledge. Systematic reviews are considered to be at the highest level in the hierarchy of evidence and should be used to make informed decisions. However, with high numbers of systematic reviews of different scope and methodological quality being published, overviews of multiple systematic reviews that assess their methodological quality are essential [ 11 , 12 , 13 ]. An overview of systematic reviews helps identify and organize the literature and highlights areas of priority in decision-making.

In this overview of systematic reviews, we aimed to summarize and critically appraise systematic reviews of coronavirus disease (COVID-19) in humans that were available at the beginning of the pandemic.

Methodology

Research question.

This overview’s primary objective was to summarize and critically appraise systematic reviews that assessed any type of primary clinical data from patients infected with SARS-CoV-2. Our research question was purposefully broad because we wanted to analyze as many systematic reviews as possible that were available early following the COVID-19 outbreak.

Study design

We conducted an overview of systematic reviews. The idea for this overview originated in a protocol for a systematic review submitted to PROSPERO (CRD42020170623), which indicated a plan to conduct an overview.

Overviews of systematic reviews use explicit and systematic methods for searching and identifying multiple systematic reviews addressing related research questions in the same field to extract and analyze evidence across important outcomes. Overviews of systematic reviews are in principle similar to systematic reviews of interventions, but the unit of analysis is a systematic review [ 14 , 15 , 16 ].

We used the overview methodology instead of other evidence synthesis methods to allow us to collate and appraise multiple systematic reviews on this topic, and to extract and analyze their results across relevant topics [ 17 ]. The overview and meta-analysis of systematic reviews allowed us to investigate the methodological quality of included studies, summarize results, and identify specific areas of available or limited evidence, thereby strengthening the current understanding of this novel disease and guiding future research [ 13 ].

A reporting guideline for overviews of reviews is currently under development, i.e., Preferred Reporting Items for Overviews of Reviews (PRIOR) [ 18 ]. As the PRIOR checklist is still not published, this study was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 statement [ 19 ]. The methodology used in this review was adapted from the Cochrane Handbook for Systematic Reviews of Interventions and also followed established methodological considerations for analyzing existing systematic reviews [ 14 ].

Approval of a research ethics committee was not necessary as the study analyzed only publicly available articles.

Eligibility criteria

Systematic reviews were included if they analyzed primary data from patients infected with SARS-CoV-2 as confirmed by RT-PCR or another pre-specified diagnostic technique. Eligible reviews covered all topics related to COVID-19 including, but not limited to, those that reported clinical symptoms, diagnostic methods, therapeutic interventions, laboratory findings, or radiological results. Both full manuscripts and abbreviated versions, such as letters, were eligible.

No restrictions were imposed on the design of the primary studies included within the systematic reviews, the last search date, whether the review included meta-analyses or language. Reviews related to SARS-CoV-2 and other coronaviruses were eligible, but from those reviews, we analyzed only data related to SARS-CoV-2.

No consensus definition exists for a systematic review [ 20 ], and debates continue about the defining characteristics of a systematic review [ 21 ]. Cochrane’s guidance for overviews of reviews recommends setting pre-established criteria for making decisions around inclusion [ 14 ]. That is supported by a recent scoping review about guidance for overviews of systematic reviews [ 22 ].

Thus, for this study, we defined a systematic review as a research report which searched for primary research studies on a specific topic using an explicit search strategy, had a detailed description of the methods with explicit inclusion criteria provided, and provided a summary of the included studies either in narrative or quantitative format (such as a meta-analysis). Cochrane and non-Cochrane systematic reviews were considered eligible for inclusion, with or without meta-analysis, and regardless of the study design, language restriction and methodology of the included primary studies. To be eligible for inclusion, reviews had to be clearly analyzing data related to SARS-CoV-2 (associated or not with other viruses). We excluded narrative reviews without those characteristics as these are less likely to be replicable and are more prone to bias.

Scoping reviews and rapid reviews were eligible for inclusion in this overview if they met our pre-defined inclusion criteria noted above. We included reviews that addressed SARS-CoV-2 and other coronaviruses if they reported separate data regarding SARS-CoV-2.

Information sources

Nine databases were searched for eligible records published between December 1, 2019, and March 24, 2020: Cochrane Database of Systematic Reviews via Cochrane Library, PubMed, EMBASE, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Sciences, LILACS (Latin American and Caribbean Health Sciences Literature), PDQ-Evidence, WHO’s Global Research on Coronavirus Disease (COVID-19), and Epistemonikos.

The comprehensive search strategy for each database is provided in Additional file 1 and was designed and conducted in collaboration with an information specialist. All retrieved records were primarily processed in EndNote, where duplicates were removed, and records were then imported into the Covidence platform [ 23 ]. In addition to database searches, we screened reference lists of reviews included after screening records retrieved via databases.

Study selection

All searches, screening of titles and abstracts, and record selection, were performed independently by two investigators using the Covidence platform [ 23 ]. Articles deemed potentially eligible were retrieved for full-text screening carried out independently by two investigators. Discrepancies at all stages were resolved by consensus. During the screening, records published in languages other than English were translated by a native/fluent speaker.

Data collection process

We custom designed a data extraction table for this study, which was piloted by two authors independently. Data extraction was performed independently by two authors. Conflicts were resolved by consensus or by consulting a third researcher.

We extracted the following data: article identification data (authors’ name and journal of publication), search period, number of databases searched, population or settings considered, main results and outcomes observed, and number of participants. From Web of Science (Clarivate Analytics, Philadelphia, PA, USA), we extracted journal rank (quartile) and Journal Impact Factor (JIF).

We categorized the following as primary outcomes: all-cause mortality, need for and length of mechanical ventilation, length of hospitalization (in days), admission to intensive care unit (yes/no), and length of stay in the intensive care unit.

The following outcomes were categorized as exploratory: diagnostic methods used for detection of the virus, male to female ratio, clinical symptoms, pharmacological and non-pharmacological interventions, laboratory findings (full blood count, liver enzymes, C-reactive protein, d-dimer, albumin, lipid profile, serum electrolytes, blood vitamin levels, glucose levels, and any other important biomarkers), and radiological findings (using radiography, computed tomography, magnetic resonance imaging or ultrasound).

We also collected data on reporting guidelines and requirements for the publication of systematic reviews and meta-analyses from journal websites where included reviews were published.

Quality assessment in individual reviews

Two researchers independently assessed the reviews’ quality using the “A MeaSurement Tool to Assess Systematic Reviews 2 (AMSTAR 2)”. We acknowledge that the AMSTAR 2 was created as “a critical appraisal tool for systematic reviews that include randomized or non-randomized studies of healthcare interventions, or both” [ 24 ]. However, since AMSTAR 2 was designed for systematic reviews of intervention trials, and we included additional types of systematic reviews, we adjusted some AMSTAR 2 ratings and reported these in Additional file 2 .

Adherence to each item was rated as follows: yes, partial yes, no, or not applicable (such as when a meta-analysis was not conducted). The overall confidence in the results of the review is rated as “critically low”, “low”, “moderate” or “high”, according to the AMSTAR 2 guidance based on seven critical domains, which are items 2, 4, 7, 9, 11, 13, 15 as defined by AMSTAR 2 authors [ 24 ]. We reported our adherence ratings for transparency of our decision with accompanying explanations, for each item, in each included review.

One of the included systematic reviews was conducted by some members of this author team [ 25 ]. This review was initially assessed independently by two authors who were not co-authors of that review to prevent the risk of bias in assessing this study.

Synthesis of results

For data synthesis, we prepared a table summarizing each systematic review. Graphs illustrating the mortality rate and clinical symptoms were created. We then prepared a narrative summary of the methods, findings, study strengths, and limitations.

For analysis of the prevalence of clinical outcomes, we extracted data on the number of events and the total number of patients to perform proportional meta-analysis using RStudio© software, with the “meta” package (version 4.9–6), using the “metaprop” function for reviews that did not perform a meta-analysis, excluding case studies because of the absence of variance. For reviews that did not perform a meta-analysis, we presented pooled results of proportions with their respective confidence intervals (95%) by the inverse variance method with a random-effects model, using the DerSimonian-Laird estimator for τ 2 . We adjusted data using Freeman-Tukey double arcosen transformation. Confidence intervals were calculated using the Clopper-Pearson method for individual studies. We created forest plots using the RStudio© software, with the “metafor” package (version 2.1–0) and “forest” function.

Managing overlapping systematic reviews

Some of the included systematic reviews that address the same or similar research questions may include the same primary studies in overviews. Including such overlapping reviews may introduce bias when outcome data from the same primary study are included in the analyses of an overview multiple times. Thus, in summaries of evidence, multiple-counting of the same outcome data will give data from some primary studies too much influence [ 14 ]. In this overview, we did not exclude overlapping systematic reviews because, according to Cochrane’s guidance, it may be appropriate to include all relevant reviews’ results if the purpose of the overview is to present and describe the current body of evidence on a topic [ 14 ]. To avoid any bias in summary estimates associated with overlapping reviews, we generated forest plots showing data from individual systematic reviews, but the results were not pooled because some primary studies were included in multiple reviews.

Our search retrieved 1063 publications, of which 175 were duplicates. Most publications were excluded after the title and abstract analysis ( n = 860). Among the 28 studies selected for full-text screening, 10 were excluded for the reasons described in Additional file 3 , and 18 were included in the final analysis (Fig. 1 ) [ 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ]. Reference list screening did not retrieve any additional systematic reviews.

figure 1

PRISMA flow diagram

Characteristics of included reviews

Summary features of 18 systematic reviews are presented in Table 1 . They were published in 14 different journals. Only four of these journals had specific requirements for systematic reviews (with or without meta-analysis): European Journal of Internal Medicine, Journal of Clinical Medicine, Ultrasound in Obstetrics and Gynecology, and Clinical Research in Cardiology . Two journals reported that they published only invited reviews ( Journal of Medical Virology and Clinica Chimica Acta ). Three systematic reviews in our study were published as letters; one was labeled as a scoping review and another as a rapid review (Table 2 ).

All reviews were published in English, in first quartile (Q1) journals, with JIF ranging from 1.692 to 6.062. One review was empty, meaning that its search did not identify any relevant studies; i.e., no primary studies were included [ 36 ]. The remaining 17 reviews included 269 unique studies; the majority ( N = 211; 78%) were included in only a single review included in our study (range: 1 to 12). Primary studies included in the reviews were published between December 2019 and March 18, 2020, and comprised case reports, case series, cohorts, and other observational studies. We found only one review that included randomized clinical trials [ 38 ]. In the included reviews, systematic literature searches were performed from 2019 (entire year) up to March 9, 2020. Ten systematic reviews included meta-analyses. The list of primary studies found in the included systematic reviews is shown in Additional file 4 , as well as the number of reviews in which each primary study was included.

Population and study designs

Most of the reviews analyzed data from patients with COVID-19 who developed pneumonia, acute respiratory distress syndrome (ARDS), or any other correlated complication. One review aimed to evaluate the effectiveness of using surgical masks on preventing transmission of the virus [ 36 ], one review was focused on pediatric patients [ 34 ], and one review investigated COVID-19 in pregnant women [ 37 ]. Most reviews assessed clinical symptoms, laboratory findings, or radiological results.

Systematic review findings

The summary of findings from individual reviews is shown in Table 2 . Overall, all-cause mortality ranged from 0.3 to 13.9% (Fig. 2 ).

figure 2

A meta-analysis of the prevalence of mortality

Clinical symptoms

Seven reviews described the main clinical manifestations of COVID-19 [ 26 , 28 , 29 , 34 , 35 , 39 , 41 ]. Three of them provided only a narrative discussion of symptoms [ 26 , 34 , 35 ]. In the reviews that performed a statistical analysis of the incidence of different clinical symptoms, symptoms in patients with COVID-19 were (range values of point estimates): fever (82–95%), cough with or without sputum (58–72%), dyspnea (26–59%), myalgia or muscle fatigue (29–51%), sore throat (10–13%), headache (8–12%), gastrointestinal disorders, such as diarrhea, nausea or vomiting (5.0–9.0%), and others (including, in one study only: dizziness 12.1%) (Figs. 3 , 4 , 5 , 6 , 7 , 8 and 9 ). Three reviews assessed cough with and without sputum together; only one review assessed sputum production itself (28.5%).

figure 3

A meta-analysis of the prevalence of fever

figure 4

A meta-analysis of the prevalence of cough

figure 5

A meta-analysis of the prevalence of dyspnea

figure 6

A meta-analysis of the prevalence of fatigue or myalgia

figure 7

A meta-analysis of the prevalence of headache

figure 8

A meta-analysis of the prevalence of gastrointestinal disorders

figure 9

A meta-analysis of the prevalence of sore throat

Diagnostic aspects

Three reviews described methodologies, protocols, and tools used for establishing the diagnosis of COVID-19 [ 26 , 34 , 38 ]. The use of respiratory swabs (nasal or pharyngeal) or blood specimens to assess the presence of SARS-CoV-2 nucleic acid using RT-PCR assays was the most commonly used diagnostic method mentioned in the included studies. These diagnostic tests have been widely used, but their precise sensitivity and specificity remain unknown. One review included a Chinese study with clinical diagnosis with no confirmation of SARS-CoV-2 infection (patients were diagnosed with COVID-19 if they presented with at least two symptoms suggestive of COVID-19, together with laboratory and chest radiography abnormalities) [ 34 ].

Therapeutic possibilities

Pharmacological and non-pharmacological interventions (supportive therapies) used in treating patients with COVID-19 were reported in five reviews [ 25 , 27 , 34 , 35 , 38 ]. Antivirals used empirically for COVID-19 treatment were reported in seven reviews [ 25 , 27 , 34 , 35 , 37 , 38 , 41 ]; most commonly used were protease inhibitors (lopinavir, ritonavir, darunavir), nucleoside reverse transcriptase inhibitor (tenofovir), nucleotide analogs (remdesivir, galidesivir, ganciclovir), and neuraminidase inhibitors (oseltamivir). Umifenovir, a membrane fusion inhibitor, was investigated in two studies [ 25 , 35 ]. Possible supportive interventions analyzed were different types of oxygen supplementation and breathing support (invasive or non-invasive ventilation) [ 25 ]. The use of antibiotics, both empirically and to treat secondary pneumonia, was reported in six studies [ 25 , 26 , 27 , 34 , 35 , 38 ]. One review specifically assessed evidence on the efficacy and safety of the anti-malaria drug chloroquine [ 27 ]. It identified 23 ongoing trials investigating the potential of chloroquine as a therapeutic option for COVID-19, but no verifiable clinical outcomes data. The use of mesenchymal stem cells, antifungals, and glucocorticoids were described in four reviews [ 25 , 34 , 35 , 38 ].

Laboratory and radiological findings

Of the 18 reviews included in this overview, eight analyzed laboratory parameters in patients with COVID-19 [ 25 , 29 , 30 , 32 , 33 , 34 , 35 , 39 ]; elevated C-reactive protein levels, associated with lymphocytopenia, elevated lactate dehydrogenase, as well as slightly elevated aspartate and alanine aminotransferase (AST, ALT) were commonly described in those eight reviews. Lippi et al. assessed cardiac troponin I (cTnI) [ 25 ], procalcitonin [ 32 ], and platelet count [ 33 ] in COVID-19 patients. Elevated levels of procalcitonin [ 32 ] and cTnI [ 30 ] were more likely to be associated with a severe disease course (requiring intensive care unit admission and intubation). Furthermore, thrombocytopenia was frequently observed in patients with complicated COVID-19 infections [ 33 ].

Chest imaging (chest radiography and/or computed tomography) features were assessed in six reviews, all of which described a frequent pattern of local or bilateral multilobar ground-glass opacity [ 25 , 34 , 35 , 39 , 40 , 41 ]. Those six reviews showed that septal thickening, bronchiectasis, pleural and cardiac effusions, halo signs, and pneumothorax were observed in patients suffering from COVID-19.

Quality of evidence in individual systematic reviews

Table 3 shows the detailed results of the quality assessment of 18 systematic reviews, including the assessment of individual items and summary assessment. A detailed explanation for each decision in each review is available in Additional file 5 .

Using AMSTAR 2 criteria, confidence in the results of all 18 reviews was rated as “critically low” (Table 3 ). Common methodological drawbacks were: omission of prospective protocol submission or publication; use of inappropriate search strategy: lack of independent and dual literature screening and data-extraction (or methodology unclear); absence of an explanation for heterogeneity among the studies included; lack of reasons for study exclusion (or rationale unclear).

Risk of bias assessment, based on a reported methodological tool, and quality of evidence appraisal, in line with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) method, were reported only in one review [ 25 ]. Five reviews presented a table summarizing bias, using various risk of bias tools [ 25 , 29 , 39 , 40 , 41 ]. One review analyzed “study quality” [ 37 ]. One review mentioned the risk of bias assessment in the methodology but did not provide any related analysis [ 28 ].

This overview of systematic reviews analyzed the first 18 systematic reviews published after the onset of the COVID-19 pandemic, up to March 24, 2020, with primary studies involving more than 60,000 patients. Using AMSTAR-2, we judged that our confidence in all those reviews was “critically low”. Ten reviews included meta-analyses. The reviews presented data on clinical manifestations, laboratory and radiological findings, and interventions. We found no systematic reviews on the utility of diagnostic tests.

Symptoms were reported in seven reviews; most of the patients had a fever, cough, dyspnea, myalgia or muscle fatigue, and gastrointestinal disorders such as diarrhea, nausea, or vomiting. Olfactory dysfunction (anosmia or dysosmia) has been described in patients infected with COVID-19 [ 43 ]; however, this was not reported in any of the reviews included in this overview. During the SARS outbreak in 2002, there were reports of impairment of the sense of smell associated with the disease [ 44 , 45 ].

The reported mortality rates ranged from 0.3 to 14% in the included reviews. Mortality estimates are influenced by the transmissibility rate (basic reproduction number), availability of diagnostic tools, notification policies, asymptomatic presentations of the disease, resources for disease prevention and control, and treatment facilities; variability in the mortality rate fits the pattern of emerging infectious diseases [ 46 ]. Furthermore, the reported cases did not consider asymptomatic cases, mild cases where individuals have not sought medical treatment, and the fact that many countries had limited access to diagnostic tests or have implemented testing policies later than the others. Considering the lack of reviews assessing diagnostic testing (sensitivity, specificity, and predictive values of RT-PCT or immunoglobulin tests), and the preponderance of studies that assessed only symptomatic individuals, considerable imprecision around the calculated mortality rates existed in the early stage of the COVID-19 pandemic.

Few reviews included treatment data. Those reviews described studies considered to be at a very low level of evidence: usually small, retrospective studies with very heterogeneous populations. Seven reviews analyzed laboratory parameters; those reviews could have been useful for clinicians who attend patients suspected of COVID-19 in emergency services worldwide, such as assessing which patients need to be reassessed more frequently.

All systematic reviews scored poorly on the AMSTAR 2 critical appraisal tool for systematic reviews. Most of the original studies included in the reviews were case series and case reports, impacting the quality of evidence. Such evidence has major implications for clinical practice and the use of these reviews in evidence-based practice and policy. Clinicians, patients, and policymakers can only have the highest confidence in systematic review findings if high-quality systematic review methodologies are employed. The urgent need for information during a pandemic does not justify poor quality reporting.

We acknowledge that there are numerous challenges associated with analyzing COVID-19 data during a pandemic [ 47 ]. High-quality evidence syntheses are needed for decision-making, but each type of evidence syntheses is associated with its inherent challenges.

The creation of classic systematic reviews requires considerable time and effort; with massive research output, they quickly become outdated, and preparing updated versions also requires considerable time. A recent study showed that updates of non-Cochrane systematic reviews are published a median of 5 years after the publication of the previous version [ 48 ].

Authors may register a review and then abandon it [ 49 ], but the existence of a public record that is not updated may lead other authors to believe that the review is still ongoing. A quarter of Cochrane review protocols remains unpublished as completed systematic reviews 8 years after protocol publication [ 50 ].

Rapid reviews can be used to summarize the evidence, but they involve methodological sacrifices and simplifications to produce information promptly, with inconsistent methodological approaches [ 51 ]. However, rapid reviews are justified in times of public health emergencies, and even Cochrane has resorted to publishing rapid reviews in response to the COVID-19 crisis [ 52 ]. Rapid reviews were eligible for inclusion in this overview, but only one of the 18 reviews included in this study was labeled as a rapid review.

Ideally, COVID-19 evidence would be continually summarized in a series of high-quality living systematic reviews, types of evidence synthesis defined as “ a systematic review which is continually updated, incorporating relevant new evidence as it becomes available ” [ 53 ]. However, conducting living systematic reviews requires considerable resources, calling into question the sustainability of such evidence synthesis over long periods [ 54 ].

Research reports about COVID-19 will contribute to research waste if they are poorly designed, poorly reported, or simply not necessary. In principle, systematic reviews should help reduce research waste as they usually provide recommendations for further research that is needed or may advise that sufficient evidence exists on a particular topic [ 55 ]. However, systematic reviews can also contribute to growing research waste when they are not needed, or poorly conducted and reported. Our present study clearly shows that most of the systematic reviews that were published early on in the COVID-19 pandemic could be categorized as research waste, as our confidence in their results is critically low.

Our study has some limitations. One is that for AMSTAR 2 assessment we relied on information available in publications; we did not attempt to contact study authors for clarifications or additional data. In three reviews, the methodological quality appraisal was challenging because they were published as letters, or labeled as rapid communications. As a result, various details about their review process were not included, leading to AMSTAR 2 questions being answered as “not reported”, resulting in low confidence scores. Full manuscripts might have provided additional information that could have led to higher confidence in the results. In other words, low scores could reflect incomplete reporting, not necessarily low-quality review methods. To make their review available more rapidly and more concisely, the authors may have omitted methodological details. A general issue during a crisis is that speed and completeness must be balanced. However, maintaining high standards requires proper resourcing and commitment to ensure that the users of systematic reviews can have high confidence in the results.

Furthermore, we used adjusted AMSTAR 2 scoring, as the tool was designed for critical appraisal of reviews of interventions. Some reviews may have received lower scores than actually warranted in spite of these adjustments.

Another limitation of our study may be the inclusion of multiple overlapping reviews, as some included reviews included the same primary studies. According to the Cochrane Handbook, including overlapping reviews may be appropriate when the review’s aim is “ to present and describe the current body of systematic review evidence on a topic ” [ 12 ], which was our aim. To avoid bias with summarizing evidence from overlapping reviews, we presented the forest plots without summary estimates. The forest plots serve to inform readers about the effect sizes for outcomes that were reported in each review.

Several authors from this study have contributed to one of the reviews identified [ 25 ]. To reduce the risk of any bias, two authors who did not co-author the review in question initially assessed its quality and limitations.

Finally, we note that the systematic reviews included in our overview may have had issues that our analysis did not identify because we did not analyze their primary studies to verify the accuracy of the data and information they presented. We give two examples to substantiate this possibility. Lovato et al. wrote a commentary on the review of Sun et al. [ 41 ], in which they criticized the authors’ conclusion that sore throat is rare in COVID-19 patients [ 56 ]. Lovato et al. highlighted that multiple studies included in Sun et al. did not accurately describe participants’ clinical presentations, warning that only three studies clearly reported data on sore throat [ 56 ].

In another example, Leung [ 57 ] warned about the review of Li, L.Q. et al. [ 29 ]: “ it is possible that this statistic was computed using overlapped samples, therefore some patients were double counted ”. Li et al. responded to Leung that it is uncertain whether the data overlapped, as they used data from published articles and did not have access to the original data; they also reported that they requested original data and that they plan to re-do their analyses once they receive them; they also urged readers to treat the data with caution [ 58 ]. This points to the evolving nature of evidence during a crisis.

Our study’s strength is that this overview adds to the current knowledge by providing a comprehensive summary of all the evidence synthesis about COVID-19 available early after the onset of the pandemic. This overview followed strict methodological criteria, including a comprehensive and sensitive search strategy and a standard tool for methodological appraisal of systematic reviews.

In conclusion, in this overview of systematic reviews, we analyzed evidence from the first 18 systematic reviews that were published after the emergence of COVID-19. However, confidence in the results of all the reviews was “critically low”. Thus, systematic reviews that were published early on in the pandemic could be categorized as research waste. Even during public health emergencies, studies and systematic reviews should adhere to established methodological standards to provide patients, clinicians, and decision-makers trustworthy evidence.

Availability of data and materials

All data collected and analyzed within this study are available from the corresponding author on reasonable request.

World Health Organization. Timeline - COVID-19: Available at: https://www.who.int/news/item/29-06-2020-covidtimeline . Accessed 1 June 2021.

COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). Available at: https://coronavirus.jhu.edu/map.html . Accessed 1 June 2021.

Anzai A, Kobayashi T, Linton NM, Kinoshita R, Hayashi K, Suzuki A, et al. Assessing the Impact of Reduced Travel on Exportation Dynamics of Novel Coronavirus Infection (COVID-19). J Clin Med. 2020;9(2):601.

Chinazzi M, Davis JT, Ajelli M, Gioannini C, Litvinova M, Merler S, et al. The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak. Science. 2020;368(6489):395–400. https://doi.org/10.1126/science.aba9757 .

Article   CAS   PubMed   PubMed Central   Google Scholar  

Fidahic M, Nujic D, Runjic R, Civljak M, Markotic F, Lovric Makaric Z, et al. Research methodology and characteristics of journal articles with original data, preprint articles and registered clinical trial protocols about COVID-19. BMC Med Res Methodol. 2020;20(1):161. https://doi.org/10.1186/s12874-020-01047-2 .

EPPI Centre . COVID-19: a living systematic map of the evidence. Available at: http://eppi.ioe.ac.uk/cms/Projects/DepartmentofHealthandSocialCare/Publishedreviews/COVID-19Livingsystematicmapoftheevidence/tabid/3765/Default.aspx . Accessed 1 June 2021.

NCBI SARS-CoV-2 Resources. Available at: https://www.ncbi.nlm.nih.gov/sars-cov-2/ . Accessed 1 June 2021.

Gustot T. Quality and reproducibility during the COVID-19 pandemic. JHEP Rep. 2020;2(4):100141. https://doi.org/10.1016/j.jhepr.2020.100141 .

Article   PubMed   PubMed Central   Google Scholar  

Kodvanj, I., et al., Publishing of COVID-19 Preprints in Peer-reviewed Journals, Preprinting Trends, Public Discussion and Quality Issues. Preprint article. bioRxiv 2020.11.23.394577; doi: https://doi.org/10.1101/2020.11.23.394577 .

Dobler CC. Poor quality research and clinical practice during COVID-19. Breathe (Sheff). 2020;16(2):200112. https://doi.org/10.1183/20734735.0112-2020 .

Article   Google Scholar  

Bastian H, Glasziou P, Chalmers I. Seventy-five trials and eleven systematic reviews a day: how will we ever keep up? PLoS Med. 2010;7(9):e1000326. https://doi.org/10.1371/journal.pmed.1000326 .

Lunny C, Brennan SE, McDonald S, McKenzie JE. Toward a comprehensive evidence map of overview of systematic review methods: paper 1-purpose, eligibility, search and data extraction. Syst Rev. 2017;6(1):231. https://doi.org/10.1186/s13643-017-0617-1 .

Pollock M, Fernandes RM, Becker LA, Pieper D, Hartling L. Chapter V: Overviews of Reviews. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.1 (updated September 2020). Cochrane. 2020. Available from www.training.cochrane.org/handbook .

Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al. Cochrane handbook for systematic reviews of interventions version 6.1 (updated September 2020). Cochrane. 2020; Available from www.training.cochrane.org/handbook .

Pollock M, Fernandes RM, Newton AS, Scott SD, Hartling L. The impact of different inclusion decisions on the comprehensiveness and complexity of overviews of reviews of healthcare interventions. Syst Rev. 2019;8(1):18. https://doi.org/10.1186/s13643-018-0914-3 .

Pollock M, Fernandes RM, Newton AS, Scott SD, Hartling L. A decision tool to help researchers make decisions about including systematic reviews in overviews of reviews of healthcare interventions. Syst Rev. 2019;8(1):29. https://doi.org/10.1186/s13643-018-0768-8 .

Hunt H, Pollock A, Campbell P, Estcourt L, Brunton G. An introduction to overviews of reviews: planning a relevant research question and objective for an overview. Syst Rev. 2018;7(1):39. https://doi.org/10.1186/s13643-018-0695-8 .

Pollock M, Fernandes RM, Pieper D, Tricco AC, Gates M, Gates A, et al. Preferred reporting items for overviews of reviews (PRIOR): a protocol for development of a reporting guideline for overviews of reviews of healthcare interventions. Syst Rev. 2019;8(1):335. https://doi.org/10.1186/s13643-019-1252-9 .

Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Open Med. 2009;3(3):e123–30.

Krnic Martinic M, Pieper D, Glatt A, Puljak L. Definition of a systematic review used in overviews of systematic reviews, meta-epidemiological studies and textbooks. BMC Med Res Methodol. 2019;19(1):203. https://doi.org/10.1186/s12874-019-0855-0 .

Puljak L. If there is only one author or only one database was searched, a study should not be called a systematic review. J Clin Epidemiol. 2017;91:4–5. https://doi.org/10.1016/j.jclinepi.2017.08.002 .

Article   PubMed   Google Scholar  

Gates M, Gates A, Guitard S, Pollock M, Hartling L. Guidance for overviews of reviews continues to accumulate, but important challenges remain: a scoping review. Syst Rev. 2020;9(1):254. https://doi.org/10.1186/s13643-020-01509-0 .

Covidence - systematic review software. Available at: https://www.covidence.org/ . Accessed 1 June 2021.

Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008.

Borges do Nascimento IJ, et al. Novel Coronavirus Infection (COVID-19) in Humans: A Scoping Review and Meta-Analysis. J Clin Med. 2020;9(4):941.

Article   PubMed Central   Google Scholar  

Adhikari SP, Meng S, Wu YJ, Mao YP, Ye RX, Wang QZ, et al. Epidemiology, causes, clinical manifestation and diagnosis, prevention and control of coronavirus disease (COVID-19) during the early outbreak period: a scoping review. Infect Dis Poverty. 2020;9(1):29. https://doi.org/10.1186/s40249-020-00646-x .

Cortegiani A, Ingoglia G, Ippolito M, Giarratano A, Einav S. A systematic review on the efficacy and safety of chloroquine for the treatment of COVID-19. J Crit Care. 2020;57:279–83. https://doi.org/10.1016/j.jcrc.2020.03.005 .

Li B, Yang J, Zhao F, Zhi L, Wang X, Liu L, et al. Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China. Clin Res Cardiol. 2020;109(5):531–8. https://doi.org/10.1007/s00392-020-01626-9 .

Article   CAS   PubMed   Google Scholar  

Li LQ, Huang T, Wang YQ, Wang ZP, Liang Y, Huang TB, et al. COVID-19 patients’ clinical characteristics, discharge rate, and fatality rate of meta-analysis. J Med Virol. 2020;92(6):577–83. https://doi.org/10.1002/jmv.25757 .

Lippi G, Lavie CJ, Sanchis-Gomar F. Cardiac troponin I in patients with coronavirus disease 2019 (COVID-19): evidence from a meta-analysis. Prog Cardiovasc Dis. 2020;63(3):390–1. https://doi.org/10.1016/j.pcad.2020.03.001 .

Lippi G, Henry BM. Active smoking is not associated with severity of coronavirus disease 2019 (COVID-19). Eur J Intern Med. 2020;75:107–8. https://doi.org/10.1016/j.ejim.2020.03.014 .

Lippi G, Plebani M. Procalcitonin in patients with severe coronavirus disease 2019 (COVID-19): a meta-analysis. Clin Chim Acta. 2020;505:190–1. https://doi.org/10.1016/j.cca.2020.03.004 .

Lippi G, Plebani M, Henry BM. Thrombocytopenia is associated with severe coronavirus disease 2019 (COVID-19) infections: a meta-analysis. Clin Chim Acta. 2020;506:145–8. https://doi.org/10.1016/j.cca.2020.03.022 .

Ludvigsson JF. Systematic review of COVID-19 in children shows milder cases and a better prognosis than adults. Acta Paediatr. 2020;109(6):1088–95. https://doi.org/10.1111/apa.15270 .

Lupia T, Scabini S, Mornese Pinna S, di Perri G, de Rosa FG, Corcione S. 2019 novel coronavirus (2019-nCoV) outbreak: a new challenge. J Glob Antimicrob Resist. 2020;21:22–7. https://doi.org/10.1016/j.jgar.2020.02.021 .

Marasinghe, K.M., A systematic review investigating the effectiveness of face mask use in limiting the spread of COVID-19 among medically not diagnosed individuals: shedding light on current recommendations provided to individuals not medically diagnosed with COVID-19. Research Square. Preprint article. doi : https://doi.org/10.21203/rs.3.rs-16701/v1 . 2020 .

Mullins E, Evans D, Viner RM, O’Brien P, Morris E. Coronavirus in pregnancy and delivery: rapid review. Ultrasound Obstet Gynecol. 2020;55(5):586–92. https://doi.org/10.1002/uog.22014 .

Pang J, Wang MX, Ang IYH, Tan SHX, Lewis RF, Chen JIP, et al. Potential Rapid Diagnostics, Vaccine and Therapeutics for 2019 Novel coronavirus (2019-nCoV): a systematic review. J Clin Med. 2020;9(3):623.

Rodriguez-Morales AJ, Cardona-Ospina JA, Gutiérrez-Ocampo E, Villamizar-Peña R, Holguin-Rivera Y, Escalera-Antezana JP, et al. Clinical, laboratory and imaging features of COVID-19: a systematic review and meta-analysis. Travel Med Infect Dis. 2020;34:101623. https://doi.org/10.1016/j.tmaid.2020.101623 .

Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus disease 2019 (COVID-19): a systematic review of imaging findings in 919 patients. AJR Am J Roentgenol. 2020;215(1):87–93. https://doi.org/10.2214/AJR.20.23034 .

Sun P, Qie S, Liu Z, Ren J, Li K, Xi J. Clinical characteristics of hospitalized patients with SARS-CoV-2 infection: a single arm meta-analysis. J Med Virol. 2020;92(6):612–7. https://doi.org/10.1002/jmv.25735 .

Yang J, Zheng Y, Gou X, Pu K, Chen Z, Guo Q, et al. Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis. Int J Infect Dis. 2020;94:91–5. https://doi.org/10.1016/j.ijid.2020.03.017 .

Bassetti M, Vena A, Giacobbe DR. The novel Chinese coronavirus (2019-nCoV) infections: challenges for fighting the storm. Eur J Clin Investig. 2020;50(3):e13209. https://doi.org/10.1111/eci.13209 .

Article   CAS   Google Scholar  

Hwang CS. Olfactory neuropathy in severe acute respiratory syndrome: report of a case. Acta Neurol Taiwanica. 2006;15(1):26–8.

Google Scholar  

Suzuki M, Saito K, Min WP, Vladau C, Toida K, Itoh H, et al. Identification of viruses in patients with postviral olfactory dysfunction. Laryngoscope. 2007;117(2):272–7. https://doi.org/10.1097/01.mlg.0000249922.37381.1e .

Rajgor DD, Lee MH, Archuleta S, Bagdasarian N, Quek SC. The many estimates of the COVID-19 case fatality rate. Lancet Infect Dis. 2020;20(7):776–7. https://doi.org/10.1016/S1473-3099(20)30244-9 .

Wolkewitz M, Puljak L. Methodological challenges of analysing COVID-19 data during the pandemic. BMC Med Res Methodol. 2020;20(1):81. https://doi.org/10.1186/s12874-020-00972-6 .

Rombey T, Lochner V, Puljak L, Könsgen N, Mathes T, Pieper D. Epidemiology and reporting characteristics of non-Cochrane updates of systematic reviews: a cross-sectional study. Res Synth Methods. 2020;11(3):471–83. https://doi.org/10.1002/jrsm.1409 .

Runjic E, Rombey T, Pieper D, Puljak L. Half of systematic reviews about pain registered in PROSPERO were not published and the majority had inaccurate status. J Clin Epidemiol. 2019;116:114–21. https://doi.org/10.1016/j.jclinepi.2019.08.010 .

Runjic E, Behmen D, Pieper D, Mathes T, Tricco AC, Moher D, et al. Following Cochrane review protocols to completion 10 years later: a retrospective cohort study and author survey. J Clin Epidemiol. 2019;111:41–8. https://doi.org/10.1016/j.jclinepi.2019.03.006 .

Tricco AC, Antony J, Zarin W, Strifler L, Ghassemi M, Ivory J, et al. A scoping review of rapid review methods. BMC Med. 2015;13(1):224. https://doi.org/10.1186/s12916-015-0465-6 .

COVID-19 Rapid Reviews: Cochrane’s response so far. Available at: https://training.cochrane.org/resource/covid-19-rapid-reviews-cochrane-response-so-far . Accessed 1 June 2021.

Cochrane. Living systematic reviews. Available at: https://community.cochrane.org/review-production/production-resources/living-systematic-reviews . Accessed 1 June 2021.

Millard T, Synnot A, Elliott J, Green S, McDonald S, Turner T. Feasibility and acceptability of living systematic reviews: results from a mixed-methods evaluation. Syst Rev. 2019;8(1):325. https://doi.org/10.1186/s13643-019-1248-5 .

Babic A, Poklepovic Pericic T, Pieper D, Puljak L. How to decide whether a systematic review is stable and not in need of updating: analysis of Cochrane reviews. Res Synth Methods. 2020;11(6):884–90. https://doi.org/10.1002/jrsm.1451 .

Lovato A, Rossettini G, de Filippis C. Sore throat in COVID-19: comment on “clinical characteristics of hospitalized patients with SARS-CoV-2 infection: a single arm meta-analysis”. J Med Virol. 2020;92(7):714–5. https://doi.org/10.1002/jmv.25815 .

Leung C. Comment on Li et al: COVID-19 patients’ clinical characteristics, discharge rate, and fatality rate of meta-analysis. J Med Virol. 2020;92(9):1431–2. https://doi.org/10.1002/jmv.25912 .

Li LQ, Huang T, Wang YQ, Wang ZP, Liang Y, Huang TB, et al. Response to Char’s comment: comment on Li et al: COVID-19 patients’ clinical characteristics, discharge rate, and fatality rate of meta-analysis. J Med Virol. 2020;92(9):1433. https://doi.org/10.1002/jmv.25924 .

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Acknowledgments

We thank Catherine Henderson DPhil from Swanscoe Communications for pro bono medical writing and editing support. We acknowledge support from the Covidence Team, specifically Anneliese Arno. We thank the whole International Network of Coronavirus Disease 2019 (InterNetCOVID-19) for their commitment and involvement. Members of the InterNetCOVID-19 are listed in Additional file 6 . We thank Pavel Cerny and Roger Crosthwaite for guiding the team supervisor (IJBN) on human resources management.

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Israel Júnior Borges do Nascimento & Milena Soriano Marcolino

Medical College of Wisconsin, Milwaukee, WI, USA

Israel Júnior Borges do Nascimento

Helene Fuld Health Trust National Institute for Evidence-based Practice in Nursing and Healthcare, College of Nursing, The Ohio State University, Columbus, OH, USA

Dónal P. O’Mathúna

School of Nursing, Psychotherapy and Community Health, Dublin City University, Dublin, Ireland

Department of Anesthesiology, Intensive Care and Pain Medicine, University of Münster, Münster, Germany

Thilo Caspar von Groote

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Livia Puljak

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IJBN conceived the research idea and worked as a project coordinator. DPOM, TCVG, HMA, IW, AM, LP, VTC, IZG, TPP, ANA, SF, NLB and MSM were involved in data curation, formal analysis, investigation, methodology, and initial draft writing. All authors revised the manuscript critically for the content. The author(s) read and approved the final manuscript.

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Supplementary Information

Additional file 1: appendix 1..

Search strategies used in the study.

Additional file 2: Appendix 2.

Adjusted scoring of AMSTAR 2 used in this study for systematic reviews of studies that did not analyze interventions.

Additional file 3: Appendix 3.

List of excluded studies, with reasons.

Additional file 4: Appendix 4.

Table of overlapping studies, containing the list of primary studies included, their visual overlap in individual systematic reviews, and the number in how many reviews each primary study was included.

Additional file 5: Appendix 5.

A detailed explanation of AMSTAR scoring for each item in each review.

Additional file 6: Appendix 6.

List of members and affiliates of International Network of Coronavirus Disease 2019 (InterNetCOVID-19).

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Borges do Nascimento, I.J., O’Mathúna, D.P., von Groote, T.C. et al. Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews. BMC Infect Dis 21 , 525 (2021). https://doi.org/10.1186/s12879-021-06214-4

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Published : 04 June 2021

DOI : https://doi.org/10.1186/s12879-021-06214-4

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Total discharges of patients with COVID-19 by quarter (Q) and infection rate per 100 000 patient-days for central line–associated bloodstream infection (CLABSI) (A), catheter-associated urinary tract infection (CAUTI) (B), methicillin-resistant Staphylococcus aureus (MRSA) bacteremia (C), and Clostridioides difficile (CDIFF) infection (D) among all inpatients, inpatients without COVID-19, and inpatients with COVID-19.

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Sands KE , Blanchard EJ , Fraker S , Korwek K , Cuffe M. Health Care–Associated Infections Among Hospitalized Patients With COVID-19, March 2020-March 2022. JAMA Netw Open. 2023;6(4):e238059. doi:10.1001/jamanetworkopen.2023.8059

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Health Care–Associated Infections Among Hospitalized Patients With COVID-19, March 2020-March 2022

  • 1 HCA Healthcare, Nashville, Tennessee

Question   What is the incidence of health care–associated infections (HAIs) among hospitalized patients with COVID-19 vs those without COVID-19?

Findings   In a cross-sectional analysis of more than 5 million hospitalizations between 2020 and 2022, the occurrence of central line–associated bloodstream infection, catheter-associated urinary tract infection, and methicillin-resistant Staphylococcus aureus bacteremia was between 2.7- and 3.7-fold higher in the COVID-19 population. Occurrence of these HAIs among patients hospitalized without COVID-19 did not increase significantly from baseline during this same time frame.

Meaning   Despite the strain on the health care system, the increase in HAIs was not observed in the non–COVID-19 population, suggesting that key safety processes were maintained and patients with COVID-19 may require additional protective care to prevent HAIs.

Importance   The reported incidence of many health care–associated infections (HAIs) increased during the COVID-19 pandemic; however, it is unclear whether this is due to increased patient risk or to increased pressure on the health care system.

Objective   To assess HAI occurrence among patients admitted to hospitals with and without COVID-19.

Design, Setting, and Participants   A cross-sectional retrospective analysis of inpatients discharged both with and without laboratory-confirmed COVID-19 infection was conducted. Data were obtained between January 1, 2019, and March 31, 2022, from community hospitals affiliated with a large health care system in the US.

Exposure   COVID-19 infection.

Main Outcomes and Measures   Occurrence of central line–associated bloodstream infection (CLABSI), catheter-associated urinary tract infection (CAUTI), methicillin-resistant Staphylococcus aureus (MRSA) bacteremia, and Clostridioides difficile infection as reported to the National Healthcare Safety Network.

Results   Among nearly 5 million hospitalizations in 182 hospitals between 2020 and 2022, the occurrence of health care–associated infections (HAIs) was high among the 313 200 COVID-19 inpatients (median [SD] age, 57 [27.3] years; 56.0% women). Incidence per 100 000 patient-days showed higher HAIs among those with COVID-19 compared with those without. For CLABSI, the incidence for the full 9 quarters of the study was nearly 4-fold higher among the COVID-19 population than the non–COVID-19 population (25.4 vs 6.9). For CAUTI, the incidence in the COVID-19 population was 2.7-fold higher in the COVID-19 population (16.5 vs 6.1), and for MRSA, 3.0-fold higher (11.2 vs 3.7). Quarterly trends were compared with the same quarter in 2019. The greatest increase in the incidence of HAI in comparison with the same quarter in 2019 for the entire population occurred in quarter 3 of 2020 for CLABSI (11.0 vs 7.3), quarter 4 of 2021 for CAUTI (7.8 vs 6.8), and quarter 3 of 2021 for MRSA (5.2 vs 3.9). When limited to the non–COVID-19 population, the increase in CLABSI incidence vs the 2019 incidence was eliminated, and the quarterly rates of MRSA and CAUTI were lower vs the prepandemic 2019 comparator quarter.

Conclusions and Relevance   In this cross-sectional study of hospitals during the pandemic, HAI occurrence among inpatients without COVID-19 was similar to that during 2019 despite additional pressures for infection control and health care professionals. The findings suggest that patients with COVID-19 may be more susceptible to HAIs and may require additional prevention measures.

The occurrence of health care–associated infections (HAIs) increased during the COVID-19 pandemic. An analysis of data submitted to the National Healthcare Safety Network (NHSN), comparing the HAI incidence by quarter in 2020 to 2019, demonstrated substantial increases in the occurrence of central line–associated bloodstream infection (CLABSI), catheter-associated urinary tract infection (CAUTI), ventilator-associated adverse events, and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia, while the occurrence of Clostridioides difficile (CDIFF) infection showed a modest decrease. 1 A follow-up analysis demonstrated that HAI rates continued to increase through the third quarter of 2021. 2 Similarly, a report from the VA Health Care system documented increases in the occurrence of CLABSI and ventilator-associated adverse events and a simultaneous decrease in CDIFF during the pandemic, although there was no reported change in CAUTI or MRSA CLABSIs. 3 In the HCA Healthcare (HCA) system in 2021, data from 82 hospitals indicated an increase in HAIs as well as clusters of infection, and these increases correlated with surges in volume of patients with COVID-19 at the hospital level. 4

While this evidence indicates that the occurrence of HAIs increased during the COVID-19 pandemic, it is unclear whether this was due to the increased strain on available hospital resources or increased susceptibility of patients with COVID-19. It has been speculated that the stress of the COVID-19 pandemic on hospitals, particularly nursing and infection prevention resources, led to an inability to maintain strict attention to known processes that prevent HAIs. 5 Yet reports also suggest that the enhanced infection prevention controls implemented in response to COVID-19 were associated with local reductions in HAIs. 6 , 7 The change to optional reporting of health care–associated infections to the Centers for Medicare & Medicaid Services in early 2020 further complicate the accurate assessment of HAI rates. 8

If overall changes to the hospital system are the primary source of the increase in HAIs, one would expect that rates increased among all hospitalized populations during the COVID-19 pandemic. However, to our knowledge, none of the published analyses to date have evaluated the occurrence of HAIs specifically among inpatients with a diagnosis of COVID-19 vs the occurrence among those who are hospitalized for other reasons. In this retrospective analysis, we assessed HAI occurrences between January 1, 2019, and March 31, 2022, for inpatients admitted to hospitals in a large health care system. We compared quarterly HAI trends between patients with and without COVID-19.

This retrospective cross-sectional analysis was conducted using data collected during the course of clinical care at 182 inpatient facilities in 21 states affiliated with the HCA system. The HCA system maintains a clinical data warehouse that includes information about coded diagnoses, laboratory events, and events reported to the NHSN. In accordance with HCA institutional policy, this research was determined to be exempt from institutional review board oversight. This determination was made using a decision support system based on a wide variety of interconnected decision trees and regulations to determine whether an activity must or may not be reviewed by an institutional review board before engaging human participants. This system was developed by and is overseen by institutional experts and has been recognized as a best practice in human research protection. 9 This study followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline.

We used these centralized data resources for the study period of January 1, 2019, through March 31, 2022, to identify the aggregate occurrence of HAIs and the COVID-19 patient population. The HAIs (CLABSI, CAUTI, MRSA, and CDIFF) were defined by the NHSN and detected using standard HAI surveillance by trained infection preventionists. 10 These 4 HAIs were selected for analysis as they are required to be reported to the NHSN and underwent consistent surveillance during the pandemic, resulting in reliable data that were applicable to all hospitalized patients. All HCA facilities continued to report HAIs to the NHSN throughout the pandemic.

Using the same data set, demographic characteristics (age, sex, race and ethnicity) were obtained. Race and ethnicity were included to evaluate potential demographic differences between those hospitalized with COVID-19 and the rest of the hospitalized population. The total patient days of discharges were calculated and separated into those with an accompanying COVID-19 diagnosis and those without. The diagnosis of COVID-19 was based on laboratory-confirmed SARS-CoV-2, via either molecular or antigen testing, during the encounter or within 30 days of admission without laboratory-confirmed negative tests before admission.

Case mix index was calculated from the total Medicare Severity Diagnosis Related Group weights of discharges divided by the total number of discharges per quarter. 11 Length of stay was calculated based on documented day of admission through day of discharge.

Event rates were calculated per calendar quarter for each of the 4 HAIs for the full population and for both the COVID-19 and non–COVID-19 populations separately. Incidence is reported as events per 100 000 patient-days for each HAI.

Comparisons are described in relation to same-quarter performance during 2019, to minimize the influence of seasonal trends. For the overall study period, an F test for a linear trend in HAI occurrence was calculated for each type of HAI for both the COVID-19 population and the population without COVID-19. Additionally, an exact binomial test for significance was calculated for each HAI each year, comparing the HAI rates in the COVID-19 population with those in the non–COVID-19 population.

There were 313 200 patients with COVID-19 from quarter (Q) 1 of 2020, the first documented diagnosis of COVID-19 in the data set, through the first quarter of 2022. The overall inpatient population included 43.5% men and 56.0% women; median (SD) age was 57 (27.3) years. For the same period, there were 4 564 375 discharges of individuals without a diagnosis of COVID-19. This translates to a total of 28 527 585 inpatient days overall: 25 652 380 non–COVID-19 patient-days and 2 875 205 COVID-19 patient-days. Case mix index was 2.29 days and mean (SD) length of stay was 8.2 (10.8) days for patients with COVID-19 during the study; for the non–COVID-19 population, the case mix index was 1.63 and mean (SD) length of stay was 4.7 (7.5). The percentage of total discharges of patients with a COVID-19 diagnosis was 6.4% overall, with a range from 0.1% (n = 780; Q1 2020) to 10.7% (n = 61 080; Q3 2021). Additional population demographic characteristics for the study period are presented in the Table .

Occurrences of CLABSI, CAUTI, MRSA, and CDIFF per 100 000 patient-days are shown in the Figure . Discharges and HAI data from 2019 are included to allow historical comparison quarter to quarter. Broad-based trends show that HAIs among the COVID-19 population were consistently higher than for the non–COVID-19 population ( Figure ). The greatest difference was for occurrence of CLABSI, where the incidence for the full 9 quarters was 3.7-fold higher among the COVID-19 population (25.4 vs 6.9). For CAUTI, the occurrence was higher in the COVID-19 population by 2.7-fold (16.5 vs 6.1), and for MRSA, 3.0-fold (11.2 vs 3.7). There was no significant difference in the CDIFF occurrence between the COVID-19 and non–COVID-19 populations.

The greatest increase in the incidence of HAI in comparison with the same quarter in 2019 for the entire population occurred in Q3 2020 for CLABSI (11.0 vs 7.3), Q4 2021 for CAUTI (7.8 vs 6.8), and Q3 2021 for MRSA (5.2 vs 3.9). When limited to the non–COVID-19 population, the same comparisons showed that any increase in HAI incidence was eliminated. In Q3 2020, the incidence of CLABSI in the non–COVID-19 population was 7.3 vs 7.3 in Q3 2019. For CAUTI, the incidence in the non–COVID-19 population was lower in Q4 2021 vs Q4 2019 (6.2 vs 6.8). The incidence of MRSA for patients without COVID-19 was also lower in Q3 2021 vs the 2019 comparator quarter (3.7 vs 3.9).

The CDIFF rate in both patients without COVID-19 and all inpatients significantly decreased by quarter ( F test; non–COVID-19, β = −7.1; P  < .001; all inpatients, β = −6.8; P  < .001), but was not significant for the COVID-19 population (β = −3.2; P  = .57). The CAUTI rate in patients without COVID-19 significantly decreased over time (β = −1.6; P  = .01). There were no significant trends identified for CLABSI or MRSA for any of the populations. When comparing the occurrence of each HAI between the COVID-19 and non–COVID-19 populations, the COVID-19 population had a significantly higher rate of infection for every HAI except CDIFF and every year (exact binomial test, P  < .001, for all combinations of year and infection type except CDIFF).

In our analysis of a large multistate population of inpatients, our findings are consistent with previous reports that the occurrence of HAIs increased during the COVID-19 pandemic, reversing a multiyear national trend of improving performance regarding hospital infection. 1 However, our subanalysis revealed that this increase in the overall infection rate appeared to be entirely due to the occurrence of HAIs in the COVID-19 population. Patients without COVID-19 had rates of HAIs that would be expected based on the incidence observed before the pandemic. The differences in HAI rates between the COVID-19 and non–COVID-19 populations for CLABSI, MRSA, and CAUTI were all significant during every year since the beginning of the pandemic.

A study of HAIs during the COVID-19 pandemic in facilities within our HCA system confirmed that the relative rates of CLABSI, CAUTI, and MRSA bacteremia were associated with increasing monthly COVID-19 discharges. 4 Between March and September 2020, there were 43% to 60% more of these infections than expected. Furthermore, clusters of hospital-onset pathogens also increased during COVID-19 surges, suggesting possible increased transmission. That study temporally linked increased HAI rates with increases in the number of patients with COVID-19 but did not distinguish among which patients (those with or without COVID-19) the HAIs were more likely to occur. Given this, that study, and others that were similar, could not discount disruptions in routine infection prevention practice as a mechanism for increased HAIs during the COVID-19 pandemic.

Previous commentary has invoked an association between the increase in HAIs during the COVID-19 pandemic and the enormous stress on hospital personnel during this time, particularly with nursing and infection prevention personnel, and the ability to maintain general infection prevention practices, such as hand hygiene, dressing care, and appropriate use of personal protective equipment. 12 The results presented herein, however, suggest that HAI prevention practices were maintained, at least for the population without COVID-19.

There are several possible mechanisms by which the HAI rate increased in the COVID-19 population at the exclusion of patients without COVID-19. First, patients with COVID-19 had a longer length of stay, which increases the risk of developing and detecting HAI. However, including patient-days as the denominator in the analysis adjusts for this difference in length of stay. Second, health care personnel assigned to COVID-19 units may have experienced reduced resources or altered workflows. Both resource limitations and care of patients with COVID-19 improved over the course of the pandemic, but the retrospective nature of this data set is not able to fully account for individual decisions that could have increased HAI risk. Third, the overall degradation in performance could be fully or partially attributable to the risks associated with this new, very high-risk population: patients with COVID-19. A previous analysis suggested that the reduction in elective admissions during the COVID-19 pandemic skewed the overall population toward patients with conditions of higher acuity. 13 In our study, the difference in HAI incidence between those with and without COVID-19, after adjusting for major confounders, suggests that the disease or its treatment preferentially increases the vulnerability of the COVID-19 population to HAIs.

A full understanding of the high vulnerability of the COVID-19 population to HAIs will be useful in guiding infection prevention practices in the future. The high occurrence of HAIs may be associated with inherent risk associated with the clinical condition of COVID-19 infection requiring hospitalization or it may be associated with care practices that introduce risk. Patient care management, particularly at the beginning of the pandemic, had elements of improvisation. Examples would include proning techniques, intravenous line extension to allow remote access, and room ventilation alterations. While HAI rates were higher in the COVID-19 population, the occurrence of CLABSI, MRSA, and CAUTI in this population decreased over the course of the pandemic from 2020 to 2022. This is likely reflective of both improving practice in the management of COVID-19 as well as the decreasing acuity and length of stay in this population over time. Additional analysis will be needed to determine whether the occurrence of HAIs continues to decrease or will stabilize in the COVID-19 population.

There are several limitations to this study. First, we are only reporting on 4 HAIs and have not assessed other reportable HAIs, such as ventilator-associated adverse events and surgical site infection. We also did not assess other measures of infection performance, such as the occurrence of clusters or trends in antimicrobial resistance. Baker et al 4 reported that clusters of hospital-onset pathogens increased as the COVID-19 burden increased, as did the occurrence of multidrug-resistant organisms. The degree to which these phenomena are attributable to the COVID-19 population exclusively has not been identified.

Second, the measure used for comparison herein is an unadjusted incidence rate and does not address potential factors such as variation in patient acuity, patient conditions, or patient demographic characteristics. However, for the non–COVID-19 population, the length of stay and case mix index remained relatively constant. While reductions in elective procedures may have affected the number and acuity of patients seen during the pandemic, the consistency in case mix index for patients without COVID-19 suggests there were minimal systemwide changes in the overall risk of populations served by participating hospitals during this timeframe. The COVID-19 population is clearly at higher risk of HAIs both because of a longer length of stay and higher level of acuity, although the substantially higher occurrence of HAIs, as well as the variability between infection types, suggests that there are additional factors inherent to this population that place them at greater risk of HAIs.

Third, this cross-sectional study was conducted at facilities within a single health care system in the US. While these facilities represent primarily community hospitals in urban and suburban settings across multiple states, it is possible that there are features of the health care system that limit generalizability. For instance, affiliated hospitals have the benefit of access to the expanded purchasing power of a large system, which may have helped with distribution of personal protective equipment, as well as access to clinical experts and best practices, and may have provided support to infection control practices during the pandemic. However, as HAIs during the pandemic increased in these facilities to a similar degree as in unaffiliated facilities, we are reasonably certain that the findings reported herein may extend outside our health care system.

Fourth, conclusions regarding trended multiyear observations in HAIs require that HAI surveillance is performed consistently, and if surveillance practice degraded during the pandemic, it could mask a true increase in the HAI rate. The HCA facilities all continued to report HAIs to the NHSN, even while reporting expectations were relaxed during the pandemic, and continued to perform routine audits of surveillance processes by an external vendor, thereby minimizing the risk of any inconsistencies in surveillance during the period of the study.

In this cross-sectional study of a large, diverse group of hospitals, we observed an increase in HAIs coincident with the increase in the volume of patients with COVID-19, and further observed that the increase may be explained by the high proportion of HAIs in the COVID-19 population specifically. Our findings suggest that, despite the unquestionable stressors that hospitals experienced during the COVID-19 pandemic, key safety processes appear to have been maintained, and HAI increases may be associated with the unique risks and intensive needs of patients with COVID-19. This analysis suggests that the greatest opportunity to improve outcomes may involve targeting additional resources to provide even greater attention to the hospitalized COVID-19 population.

Accepted for Publication: February 28, 2023.

Published: April 13, 2023. doi:10.1001/jamanetworkopen.2023.8059

Open Access: This is an open access article distributed under the terms of the CC-BY-NC-ND License . © 2023 Sands KE et al. JAMA Network Open .

Corresponding Author: Kenneth E. Sands, MD, MPH, HCA Healthcare, One Park Plaza, Nashville, TN 37203 ( [email protected] ).

Author Contributions: Dr Sands and Ms Fraker had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Sands, Blanchard, Fraker, Cuffe.

Acquisition, analysis, or interpretation of data: Sands, Fraker, Korwek, Cuffe.

Drafting of the manuscript: Sands, Blanchard.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Sands, Fraker.

Obtained funding: Cuffe.

Administrative, technical, or material support: Cuffe.

Supervision: Sands, Cuffe.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was self-funded by HCA Healthcare.

Role of the Funder/Sponsor: The authors were independent and unrestricted in the design and conduct of the study, including collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The views expressed in this publication represent those of the authors and do not necessarily represent the official views of HCA Healthcare or any of its affiliated entities.

Data Sharing Statement: See the Supplement .

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What Happened When a Man Got 217 COVID-19 Vaccines

Covid-19-vaccine

COVID-19 vaccines have been key to controlling the pandemic, but researchers in Germany report on one man who took the vaccination message to the extreme.

The subject of the research published in Lancet Infectious Diseases is a 62-year-old man from Magdeburg, Germany who claims to have received 217 COVID-19 vaccinations within about 2.5 years. (German prosecutors confirmed he received 130 shots in nine months during an investigation into fraud; ultimately, they did not file criminal charges.)

It's not clear why the man wanted so many vaccinations or how he obtained them. But after reading news reports of the man's story, scientists at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) became intrigued and wanted to study how the vaccinations affected his immune system. The man—who told researchers he hadn't experienced side effects from his shots—volunteered to provide blood and saliva samples to the scientists and allowed them to mine his health records so that they could better understand what effect aggressively stimulating the immune system with a COVID-19 vaccine might have. Even during this analysis, the man requested and received an additional two COVID-19 shots, against the advice of the study researchers.

The man’s extreme vaccination history provided a unique opportunity for scientists to see whether hyper-vaccination would positively or negatively affect the immune system's ability to respond to pathogens like viruses. “It was unclear in which direction the 200 vaccinations would go,” says Dr. Kilian Schober, the study's lead author and group leader at the Institute for Clinical Microbiology, Immunology, and Hygiene in Erlangen at FAU. Would these shots enhance his immune response—"like we want to see with multiple vaccinations and booster shots"—or perhaps damage it?

Read More : Why Older Adults Need Another COVID-19 Shot

Schober and the team compared the man’s immune responses—measured by his blood antibody levels, the first line of defense against a virus, and T cell levels, which are responsible for the body's longer-term response—to those of a control group of 29 people who had received three COVID-19 shots.

Based on how the immune system works, Schober and his team thought that the man's immune response might mirror that of people with chronic infections, such as HIV or hepatitis B. In those conditions, in which the immune system is constantly stimulated, immune cells can become overwhelmed and start to mount weaker responses.

But that's not what they found. The man's antibody levels and a type of T cell called effector T cells were six times higher than those in the control group on average. Those high levels proved that his immune response was strong.

However, his level of memory T cells—which are responsible for remembering viruses that a person has been infected with and replenishing the immune system's overall T-cell population—were about the same as those in the control group. “It made sense,” says Schober, since memory T cells are reactivated when the body sees the same virus again. "But it was intriguing for us to actually see it in the data.”

According to repeated negative tests for COVID-19, which the researchers confirmed by the fact that that his immune system “showed no sign that it had dealt with the virus yet,” says Schober, the man was likely never infected with SARS-CoV-2. Schober cautions, however, against assuming that his hyper-vaccinated status was responsible for protecting him.

The researchers concluded that overall, while the man's excessive vaccination history increased his antibody levels and apparently protected him from infection, hyper-activating his immune system did not seem to have a negative effect on his ability to mount an adequate response. At the same time, his extreme measures did not seem to afford him a level of super-immunity that distinguished his response dramatically from others who followed the recommended vaccination schedule. “His immune system was neither positively nor negatively affected," says Schober.

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Watch CBS News

A man got 217 COVID-19 vaccinations. Here's what happened.

By Caitlin O'Kane

Edited By Paula Cohen

Updated on: March 6, 2024 / 11:32 AM EST / CBS News

A 62-year-old man in Germany intentionally got 217 doses of  COVID-19 vaccines within 29 months. The vaccinations occurred outside of a clinical study, and after hearing about the "hypervaccinated" man, medical researchers in Germany reached out to him to run tests.

The researchers first learned about the man, who they say got the vaccines "deliberately and for private reasons," when a public prosecutor in Magdeburg, Germany, opened a fraud investigation, according to a paper  published in The Lancet Infectious Diseases  medical journal on Monday. The prosecutor confirmed 130 of the vaccinations and ultimately did not file criminal charges against the man.

The researchers sent a proposal to the man and the prosecutor saying they wanted to investigate the potential impact on his immune system from getting so many of the shots.

The man voluntarily gave them blood and saliva samples and the researchers compared his antibody levels to a control group of 29 people who had three doses of mRNA COVID-19 vaccines , according to the study. 

They were able to measure the man's antibody levels after his 214th vaccination and found them highest on that day and again three days after his 215th vaccination. His contraction kinetics — the cell response to the antibodies — mirrored those of the control group. His 217th vaccination showed just a modest increase in antibodies.

They checked the levels of a variety of types of cells involved in immune system responses, and while some were boosted as his vaccinations increased, many levels were in line with the control group.

The researchers say the man appeared to suffer no significant side effects despite the extreme number of doses.

"In summary, our case report shows that SARS-CoV-2 hypervaccination did not lead to adverse events and increased the quantity of spike-specific antibodies and T cells without having a strong positive or negative effect on the intrinsic quality of adaptive immune responses," the study reads. "While we found no signs of SARS-CoV-2 breakthrough infections in [the man] to date, it cannot be clarified whether this is causally related to the hypervaccination regimen."

"Importantly, we do not endorse hypervaccination as a strategy to enhance adaptive immunity," they note.

Staying up to date with  COVID-19 vaccinations  is recommended for everyone ages 6 months and older in the U.S. There are three types of COVID-19 vaccines available in the U.S. — two mRNA vaccines from Moderna and Pfizer, and a protein subunit vaccine from Novavax — and there is no preferential recommendation of one over the other, according to the CDC.  The CDC has a table with information  on the number of recommended doses based on your past vaccinations.

The CDC recently amended its COVID-19 guidelines, shortening the 5-day isolation period and updating its guidance on masks and testing. The new recommendations offer a "unified, practical approach to addressing risk" from COVID as well as other infections like the flu and RSV, the agency said.

  • COVID-19 Vaccine

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Caitlin O'Kane is a New York City journalist who works on the CBS News social media team as a senior manager of content and production. She writes about a variety of topics and produces "The Uplift," CBS News' streaming show that focuses on good news.

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Case Report: COVID-19 Risk in CLL Could Be Exacerbated by Hypogammaglobulinemia

The patient continued to test positive for COVID-19, but intravenous immunoglobulin eventually led to his recovery.

People with chronic lymphocytic leukemia (CLL) are at a higher risk of contracting COVID-19, but a new case report shows that some patients with CLL may experience particularly persistent, worsening cases of COVID-19 as a result of CLL-secondary hypogammaglobulinemia.

The report was published in Cureus .

Chronic lymphocytic leukemia | Image Credit: © jarun011 - stock.adobe.com

Chronic lymphocytic leukemia | Image Credit: © jarun011 - stock.adobe.com

clinical case study on covid 19

The case involved a 77-year-old man who received a diagnosis of CLL 13 years ago and whose disease was classified as stage 3 according to the modified Rai clinical staging system. The patient was taking 6 cycles of venetoclax (Venclexta; AbbVie/Genentech) 300 mg daily maintenance.

The patient explained that, despite being fully vaccinated, he had been diagnosed with COVID-19 4 months ago, and since that time he had experienced shortness of breath that got progressively worse. He was treated with antivirals and steroids, but continued to test positive for COVID-19. Two months prior to the visit documented in the case report, he had started requiring oxygen to walk.

“Shortness of breath was associated with a productive cough, and the patient could not walk a few steps without rest,” the authors wrote.

The patient had stable vital signs, and a chest examination showed fine bilateral crackles without lower limb edema or jugular venous distension, according to the authors.

“Initial labs showed normal complete blood count, complete metabolic panel, and brain natriuretic peptide,” they wrote. “Procalcitonin was negative, but C-reactive protein (CRP) was 11 mg/L (normal range: 0-0.8 mg/L).”

A respiratory panel came back negative, with the exception of COVID-19.

The patient was given a CT scan, which showed he had scattered peripheral ground-glass infiltrates that were worse than in previous scans 3 and 4 months prior.

“The patient was again started on [intravenous] steroids and molnupiravir (Lagevrio; Merck) with no improvement in his symptoms over the next few days, so immunoglobulin levels were ordered and showed IgA was 13 mg/dL (normal value: 61-437 mg/dL), IgG 109 mg/dL (normal value: 603-1613 mg/dL), and IgM 15 mg/dL (normal value: 15-143 mg/dL),” the authors reported.

Based on those results, the patient was started on intravenous immunoglobulin (IVIG), which led to immediate improvement following the first dose, they wrote.

After 2 weeks, the patient was no longer requiring oxygen and he reported that shortness of breath was no longer an issue. Additionally, the patient achieved a negative COVID-19 test despite not holding rituximab (Rituxan; Genentech/Biogen) or venetoclax during his treatment.

The authors explained that the patient’s CLL likely affected the course of his COVID-19.

“CLL patients, in particular, have a high risk for a poor outcome from COVID-19 infection, and this can be attributed to co-existing low immunoglobulin levels caused by CLL itself or the treatment regimens which include rituximab,” they noted.

The authors noted that one study found up to 6.6% of patients taking rituximab may develop chronic hypogammaglobulinemia as a result of anti-CD20 medication.

The investigators said they were unable to find in the medical literature a similar case in which a patient continuously tested positive for COVID-19 and had worsening symptoms after being treated with standard therapies. However, they said physicians should keep hypogammaglobulinemia in mind in cases of patients with CLL and COVID-19.

“In conclusion, the use of IVIG, long considered only an ancillary therapy in individuals with CLL on long-term/continuous therapies, must be carefully taken into consideration by physicians who manage these patients with COVID-19 infections, given the longer life expectancy,” they wrote.

Haddad A, Al-Maharmeh Q, Kloub MN, Ali EA, Shaaban H. Long-lasting SARS-CoV-2 infection with post-COVID-19 chronic interstitial pneumonia in a patient with chronic lymphocytic leukemia treated successfully with intravenous immunoglobulin. Cureus . 2024;16(1):e51890. doi:10.7759/cureus.51890

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clinical case study on covid 19

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  • Published: 05 August 2020

Impact of the COVID-19 pandemic on clinical research

  • Katherine R. Tuttle   ORCID: orcid.org/0000-0002-2235-0103 1 , 2  

Nature Reviews Nephrology volume  16 ,  pages 562–564 ( 2020 ) Cite this article

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  • Acute kidney injury
  • Clinical trials
  • Infectious diseases

The COVID-19 pandemic has placed a tremendous strain on sustaining the clinical research enterprise and will also likely affect key study outcomes; these effects must be considered during data analysis and interpretation. Nevertheless, the responses to the pandemic have also introduced innovations that will advance the conduct of clinical research.

The first recognized case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leading to coronavirus disease 2019 (COVID-19) in the USA occurred during late January 2020 in the state of Washington 1 . Our state was hit hard by the outbreak that followed, as hospitals and emergency medical services became overwhelmed by severely ill patients in the major health-care hubs 2 , 3 , 4 , 5 . We first had a sprint, from March through to May 2020 when elective procedures and in-person patient visits were halted to reduce the risk of viral transmission, conserve personal protective equipment (PPE) and make more health-care workers available for the enormous clinical impact of COVID-19. As initial social distancing and other efforts to contain the virus dampened the spread, we began to gradually re-open in health-care systems and society at large. However, this was soon followed by another uptick in cases beginning in June 2020 that required backtracking to more restrictive measures. It is now clear that COVID-19 is with us for the long haul, a marathon that we will run for months or years to come.

COVID-19 is with us for the long haul, a marathon that we will run for months or years to come

SARS-CoV-2 infection spreads via extremely contagious respiratory droplets 6 . COVID-19 is commonly a mild upper respiratory illness, but a substantial minority of patients develop severe bilateral pneumonia leading to hospitalization for supplementary oxygen and supportive care, or respiratory failure requiring mechanical ventilation 7 , 8 , 9 . SARS-CoV-2 infection also spreads from the lungs to other organs 6 . Acute kidney injury is common in patients with COVID-19 and may be due to viral infiltration or other kidney injuries caused by a systemic inflammatory response, hypotension or nephrotoxins 2 , 3 , 4 , 7 , 10 . As a result, clinical nephrology services have been overwhelmed by the acute dialysis needs of patients hospitalized with COVID-19. Many of us, no matter how senior or focused on academic work, have been called to clinical service. I was the only nephrologist still in practice who knew how to implement acute peritoneal dialysis should we run short of resources for continuous kidney replacement therapy. This important skill has all but disappeared in contemporary nephrology practice, despite its practicality and effectiveness in acute care settings.

I began my career as an intern in 1982 when AIDS had started to wreak havoc at Northwestern Memorial Hospital in Chicago. I cared for more pneumocystis pneumonia than pneumococcal pneumonia and more Kaposi’s sarcoma than breast cancer. Nearly half of the medical services were AIDS wards when I finished my residency in 1985. HIV was identified as the cause around that time. However, intense research efforts led to HIV testing and novel treatment options, which have dramatically reduced the number of full-blown AIDS cases and turned HIV infection into a mostly manageable chronic condition. There are many lessons from HIV/AIDS that have informed my current thinking and response to COVID-19.

The Providence St Joseph Health hospitals in Washington state have had >7,000 admissions for COVID-19 as of 20 July 2020, and more come each day. Within this health-care system, I am executive director for research in the Providence Health Care region and, in this role, I rapidly turned old lessons from the HIV/AIDS era into new actions. Our overarching goal was to address the critical needs of COVID-19 research while maintaining research for essential concerns across other therapeutic areas in both adult and paediatric medicine. The main priority was to open the platform clinical trial of anti-viral treatments sponsored by the National Institutes of Allergy and Infectious Diseases/National Institutes of Health (NIAID/NIH), which required redirection of clinical research resources from other therapeutic areas to COVID-19 and a rapid administrative response. Our regulatory group and Institutional Review Board prepared, reviewed and approved the study protocol and informed consent form within 3 days over a weekend. Our budget and contracting groups similarly moved with record speed. As a result, our site was among the first ten sites activated on the initial NIAID/NIH clinical trial of remdesivir versus placebo. Our first participant was enrolled just 5 days after we received the study protocol.

Research groups from other therapeutic areas were quickly deployed, trained and certified by NIAID/NIH to ensure that enough investigators and study coordinators were available to manage this intense clinical trial activity. Our COVID-19 investigators are a multi-specialty team consisting of experts in infectious diseases, pulmonary and critical care, hospital medicine and nephrology. Similarly, research coordinators who normally manage studies in cardiology and nephrology were moved onto the COVID-19 team. We meet in a daily huddle to review all hospital admissions for COVID-19 with the goal of having a study option for every patient. The NIAID/NIH platform trial is continuing and we have since activated other new protocols for serology testing, biobanking and therapeutic interventions in those who have been excluded from the NIAID/NIH protocols, such as patients with an estimated glomerular filtration rate of <30 ml/min/1.73m 2 . Informed consent forms are currently available in five languages, and we have implemented Institutional Review Board-approved consent via remote technologies and using legally authorized representatives.

The COVID-19 pandemic has placed a tremendous strain on the clinical research enterprise. With the redirection of resources and temporary halting of in-person visits, studies in other therapeutic areas have been unavoidably constrained. However, the COVID-19 response has also introduced innovations that have advanced our overall conduct of clinical research (Table  1 ). Although recruitment and enrolment for most other studies stopped during the early stages of the pandemic, both our study sponsors and sites developed new approaches to conduct remote visits by telehealth, use home-based testing or monitoring technologies, and provide curbside or courier pick-up and delivery of participant samples and investigational products. Our research leaders, investigators and staff have made concerted efforts to provide study updates to participants — by telephone, email and through the electronic health record portal — during and after the pause in the studies. We re-opened for in-person visits on 18 May 2020 under strict enforcement of clinical protocols for viral infection prevention and the use of PPE according to the guidelines established by our health-care system. Study participants are given the option of a remote visit whenever possible. Every person who enters the clinical research centre is screened for COVID-19 symptoms, fever and potential exposure. Masks and physical distancing are required for all in-person interactions and no visitors are allowed, except for one parent in the case of paediatric patients, or one carer in the case of patients with disabilities.

The enrolment rates for our research programme are now similar to those recorded pre-pandemic. To the best of our knowledge, we have sustained retention in the ongoing studies. We will survey participants about their experiences and perspectives to facilitate research despite the risks associated with COVID-19. Notably, we must be cognizant that COVID-19 might affect key study outcomes. For example, SARS-CoV-2 infection could worsen glycaemic control in persons with diabetes, raise or lower blood pressure in those with hypertension, or accelerate progression of chronic kidney disease. Adverse events, particularly acute illnesses, hospitalizations and mortality may be caused by the viral infection or by deferral of care due to fear of contracting it. Participants are also likely to have changed their lifestyles to minimize contact with others, which may also affect outcomes. These are crucial considerations for study analysis and interpretation. Potential confounding may be addressed by examining pre-and post-pandemic outcome rates and COVID-19 surveillance with control for evidence of exposure or infection entered into data analysis plans. Nevertheless, with proactive measures, it is feasible to maintain interest, participation and quality in clinical research.

with proactive measures, it is feasible to maintain interest, participation and quality in clinical research

Investigators, coordinators and clinicians have a renewed sense of urgency and purpose to use science to solve problems that are important to patients and the public. We do get tired at times, and burnout is a real risk. Yet, we move forward with mutual support, encouragement and focus on tangible goals to keep making research better. All of these are positive changes that we will retain long after the COVID-19 pandemic subsides.

Holshue, M. L. et al. First case of 2019 novel coronavirus in the United States. N. Engl. J. Med. 382 , 929–936 (2020).

Article   CAS   Google Scholar  

Bhatraju, P. K. et al. Covid-19 in critically ill patients in the Seattle region – case series. N. Engl. J. Med. 382 , 2012–2022 (2020).

Buckner, F. S. et al. Clinical features and outcomes of 105 hospitalized patients with COVID-19 in Seattle, Washington. Clin. Infect. Dis. https://doi.org/10.1093/cid/ciaa632 (2020).

Article   PubMed   PubMed Central   Google Scholar  

Arentz, M. et al. Characteristics and outcomes of 21 critically ill patients with COVID-19 in Washington State. JAMA 323 , 1612–1614 (2020).

Yang, B. Y. et al. Clinical characteristics of patients with coronavirus disease 2019 (COVID-19) receiving emergency medical services in King County, Washington. JAMA Netw. Open 3 , e2014549 (2020).

Article   Google Scholar  

Tay, M. Z., Poh, C. M., Rénia, L., MacAry, P. A. & Ng, L. F. P. The trinity of COVID-19: immunity, inflammation and intervention. Nat. Rev. Immunol. 20 , 363–374 (2020).

Richardson, S. et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA 323 , 2052–2059 (2020).

Grasselli, G. et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy region, Italy. JAMA 323 , 1574–1581 (2020).

Zhou, F. et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 395 , 1054–1062 (2020).

Hirsch, J. S. et al. Acute kidney injury in patients hospitalized with COVID-19. Kidney Int. 98 , 209–218 (2020).

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Tuttle, K.R. Impact of the COVID-19 pandemic on clinical research. Nat Rev Nephrol 16 , 562–564 (2020). https://doi.org/10.1038/s41581-020-00336-9

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clinical case study on covid 19

ORIGINAL RESEARCH article

Association between loss of hypercoagulable phenotype, clinical features and complement pathway consumption in covid-19.

Daisuke Kasugai*

  • 1 Department of Emergency and Critical Care Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
  • 2 Department of Pediatrics, Nagoya University Graduate School of Medicine, Nagoya, Japan
  • 3 Department of Biostatistics, Nagoya University Graduate School of Medicine, Nagoya, Japan
  • 4 Department of Critical Care Medicine, Komaki City Hospital, Komaki, Japan
  • 5 Department of Respiratory Medicine, Daido Hospital, Nagoya, Japan
  • 6 Department of Emergency and Critical Care Medicine, Tosei General Hospital, Seto, Japan
  • 7 Department of Emergency and Critical Care Medicine, Tokyo Metropolitan Tama Medical Center, Fuchu, Japan
  • 8 Department of Respiratory Medicine, Meitetsu Hospital, Nagoya, Japan
  • 9 Department of Emergency and Critical Care Medicine, Nagoya City University Hospital, Nagoya, Japan
  • 10 Department of Emergency and General Internal Medicine, Fujita Health University, Toyoake, Japan
  • 11 Department of Internal Medicine, National Hospital Organization Nagoya Medical Center, Nagoya, Japan
  • 12 Department of Respiratory Medicine, Chukyo Hospital, Nagoya, Japan
  • 13 Department of Internal Medicine, Kyoritsu General Hospital, Nagoya, Japan
  • 14 Department of Emergency and Disaster Medicine, Mie University Graduate School of Medicine, Tsu, Japan
  • 15 Department of Emergency and Critical Care Medicine, Gifu University Graduate School of Medicine, Gifu, Japan
  • 16 Department of Internal Medicine, SaiShukan Hospital, Kitanagoya, Japan
  • 17 Department of Emergency Medicine, Nagoya EkiSaikai Hospital, Nagoya, Japan

Background: Coronavirus disease 2019 (COVID-19) features a hypercoagulable state, but therapeutic anticoagulation effectiveness varies with disease severity. We aimed to evaluate the dynamics of the coagulation profile and its association with COVID-19 severity, outcomes, and biomarker trajectories.

Methods: This multicenter, prospective, observational study included patients with COVID-19 requiring respiratory support. Rotational thromboelastometry findings were evaluated for coagulation and fibrinolysis status. Hypercoagulable status was defined as supranormal range of maximum clot elasticity in an external pathway. Longitudinal laboratory parameters were collected to characterize the coagulation phenotype.

Results: Of 166 patients, 90 (54%) were severely ill at inclusion (invasive mechanical ventilation, 84; extracorporeal membrane oxygenation, 6). Higher maximum elasticity ( P =0.02) and lower maximum lysis in the external pathway ( P =0.03) were observed in severely ill patients compared with the corresponding values in patients on non-invasive oxygen supplementation. Hypercoagulability components correlated with platelet and fibrinogen levels. Hypercoagulable phenotype was associated with favorable outcomes in severely ill patients, while normocoagulable phenotype was not (median time to recovery, 15 days vs. 27 days, P =0.002), but no significant association was observed in moderately ill patients. In patients with severe COVID-19, lower initial C3, minimum C3, CH50, and greater changes in CH50 were associated with the normocoagulable phenotype. Changes in complement components correlated with dynamics of coagulation markers, hematocrit, and alveolar injury markers.

Conclusions: While hypercoagulable states become more evident with increasing severity of respiratory disease in patients with COVID-19, normocoagulable phenotype is associated with triggered by alternative pathway activation and poor outcomes.

Introduction

Coronavirus disease 2019 (COVID-19) triggered a global pandemic by causing primarily, respiratory distress occasionally escalating into respiratory failure, thereby posing significant public health challenges worldwide ( 1 ). In this context, coagulopathy, characterized by hypercoagulation is identified as one of the key pathogenic factors in COVID-19 ( 2 , 3 ). Associations of COVID-19 with macro- and microthrombosis have been established ( 4 – 6 ), which have spurred numerous clinical trials aiming to mitigate coagulopathy induced by this disease ( 7 ). Despite these efforts, previous studies did not consistently demonstrate the efficacy of therapeutic anticoagulation against COVID-19, irrespective of disease severity ( 8 ). While the effectiveness of therapeutic anticoagulation has been explored in moderately and critically ill patients with COVID-19 ( 9 , 10 ), the contrasting results from these trials suggest that therapeutic anticoagulation might be more effective in non-critically ill patients than in their critically ill counterparts. This discrepancy could stem from the evolving nature of coagulopathy as the disease progresses. Hence, understanding how coagulopathy varies with disease severity is essential for optimizing therapeutic interventions aimed at controlling coagulation status.

This study aimed to investigate the changes in coagulation characteristics with increasing severity of COVID-19.

Study population and setting

This prospective observational study conducted at 14 centers in Japan, from March 2021 to March 2022 included individuals aged ≥18 years, who were hospitalized for COVID-19 pneumonia and required oxygenation. COVID-19 was diagnosed based on findings from lung imaging and a positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) polymerase chain reaction or antigen test. Patients were classified into four groups based on COVID-19 severity at the time of coagulation status assessment according to the WHO ordinal scale: moderately ill patients requiring supplemental oxygen, patients on non-invasive respiratory support, patients on mechanical ventilation, and patients on extracorporeal membrane oxygenation ( 11 ). Exclusion criteria included known coagulopathy, previous oral anticoagulants administration, hematologic malignancy, and thrombocytopenia (detailed criteria listed in the Supplementary Methods in Additional File 1 ). Patients provided pre-enrollment informed consent. The study was approved by Nagoya University Hospital Institutional Review Board (Approval No. 2020-0548).

Evaluation of coagulation profile using thromboelastometry

In addition to clinical laboratory coagulation function tests, thromboelastometry with ROTEM sigma™ was used to evaluate the coagulation profile of participants on the day of inclusion. The maximum clot elasticity (MCE) of each component was calculated from maximum clot firmness (MCF) using the previously described: MCE = (100×MCF)/(100-MCF) ( 12 ). The platelet component of MCE is evaluated using the difference between MCE EXTEM and FIBTEM. A hypercoagulable state was defined as the MCE of the external pathway exceeding the normal reference value ( 13 ). Figure 1 illustrates responentable image of EXTEM components of the thromboelastometry test for patients with normal and hypercoagulable states. A comprehensive description of the thromboelastometry parameters can be found in the previous publicaion ( 14 ).

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Figure 1 Representative image of thromboelastometry test. The figure shows the output of the EXTEM component of thromboelastometry, illustrating normal coagulation (A) and hypercoagulable states in patient with COVID-19 patients (B) . The double arrow indicates maximum clot firmness.

Outcomes and clinical data

The primary endpoint was the time to recovery, with the recovery day defined as the first day during the 28 days after enrollment, on which patients did not require any respiratory support ( 11 ). Secondary outcomes included ventilator-free days within the 28 days and in-hospital mortality. Other recorded clinical data included demographics, comorbidity, activities of daily living ( 15 ), history of COVID-19 vaccinations, respiratory mechanics, laboratory values at the time of thromboelastometry evaluation, and treatments. In patients requiring mechanical ventilation at the Nagoya University Hospital, daily laboratory results within the initial 7 days from intubation to ICU discharge were recorded to assess the association between biomarker dynamics. The collected longitudinal data were analyzed to identify the initial, the highest, and lowest value, and calculate the maximum changes(ΔC3 = lowest C3/initial C3 ×100%). These routine lab tests were conducted by the central laboratory, with the specific testing methods and reagents detailed in Table E1 in the Supplementary Material .

Viral load assessment and genotyping of SARS-CoV-2

To explore the relationship with coagulation profiles, plasma viral loads were analyzed using quantitative reverse-transcription polymerase chain reaction. To investigate the relationship between coagulation profiles and viral genotypes in SARS-CoV-2, we performed whole-genome sequencing using stored specimens from the lower respiratory tract.

Statistical analysis

Spearman’s rank correlation test was used for statistical analysis, focusing on assessing the relationships between thromboelastometry parameters and clinical laboratory tests, such as coagulation function tests, using Spearman’s rank correlation test. The results were visualized using a heatmap. This method was also employed to examine longitudinal associations between complements and laboratory biomarkers. To assess differences in thromboelastometry results by severity, the Kruskal–Wallis test was used. P values for pairwise comparisons were adjusted using the Bonferroni method. The association between hypercoagulable state and baseline respiratory and laboratory parameters was evaluated using the Mann–Whitney U test. To decrease type-I error of multiple comparisons for 29 variables, the Benjamini–Hochberg procedure with a false discovery rate of 0.05 was applied to adjust the P value. Time to recovery was evaluated using the log-rank test, with a competing event of death regarded as “not recovered” on the last observation day, following an approach similar to the Fine–Grey method ( 11 , 16 ). A P value less than 0.05 was considered statistically significant. All statistical analyses were performed using R software (version 4.2.2) and RStudio.

Characteristics of patients and outcomes

Of the 192 cases identified during the observation period, 166 were finally included in the study ( Figure E1 in the Additional File 1 ). Among the enrolled patients, 76 had moderate respiratory failure at the time of inclusion (conventional oxygen supplementation, 62; non-invasive respiratory support, 14), and 90 had severe respiratory failure (mechanical ventilation, 84; extracorporeal membrane oxygenation, 6) ( Table 1 ). The most common comorbidities were hypertension (40%) and diabetes mellitus (28%). Prior to disease onset, 159 (96%) patients could independently perform activities of daily living. Of the enrolled patients, 26 (16%) had received two doses of SARS-CoV-2 vaccine before disease onset. Unfractionated heparin was more commonly administered in severe cases, 88 (98%), than in moderate ones, 34 (45%), and was mainly used for therapeutic dose titration. Among patients with moderate respiratory failure at the time of inclusion, 10 (13%) experienced disease progression. Of the patients who received mechanical ventilation, 59 (66%) recovered after 28 days, 11 (12%) died, and 20 (22%) became ventilator dependent.

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Table 1 Baseline characteristics of study participants.

Coagulation profiles vary according to the severity of respiratory failure

Figure 2 demonstrates a correlation between thromboelastometry parameters and laboratory biomarkers, where MCF and MCE were positively correlated with platelet counts (rho for MCE EXTEM = 0.67, P < 0.001) in all components except for in FIBTEM. Maximum lysis parameters were weak and negatively associated with white blood cell count, D-dimer levels, and platelet count (rho = -0.3, -0.32, and -0.32, respectively, for maximum lysis (EXTEM), P < 0.001). Figures 3 , 4 illustrate the relationship between elasticity and fibrinolytic profile among different severities of respiratory failure. Patients receiving non-invasive respiratory support exhibited the highest MCE EXTEM values among other severity levels ( Figure 3A , median [interquartile range (IQR)], 223 [186-245] for supplemental oxygen, 257 [213-281] for on-invasive respiratory support, 244 [203-270] for mechanical ventilation, and 178 [170-213] for extracorporeal membrane oxygenation, respectively).MCE was higher in patients on mechanical ventilation than in those receiving supplemental oxygen, which mainly reflects the platelet component ( Figure 3B , median [IQR] MCE platelet of supplemental oxygen vs mechanical ventilation, 184 [154–213] vs. 206 [170–230], P = 0.02). Meanwhile, maximum lysis declined as respiratory failure progressed ( Figures 4A, B , median [IQR] ML EXTEM of supplemental oxygen vs mechanical ventilation, 11 [6–13] vs. 8 [5–11], P = 0.03). No significant differences between the groups were observed in terms of the fibrinogen component ( Figures 3D , 4C ).

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Figure 2 Correlation of thromboelastometry results with clinical laboratory test results. A heatmap showing correlation of viscoelasticity test parameters with clinical laboratory test results. Each rectangle represents Spearman’s rank correlation coefficient. P values are displayed in asterisks. * P value < 0.05, ** P value < 0.01, *** P value < 0.001, **** P value < 0.0001. WBC, white blood cell; vWF, von Willebrand factor; sTM, soluble thrombomodulin; TAT, thrombin-antithrombin complex; PIC, plasmin-alpha 2-plasmin inhibitor complex; PCT, procalcitonin; PAI1, plasminogen activator inhibitor-1; LAC, lupus anticoagulant; INR, international normalized ratio; FDP, fibrin degradation product; CRP, c reactive protein; CH50, total hemolytic complement; AT3, antithrombin 3; APTT, activated partial thrombin time; CT, clotting time; CFT, clot formation time; MCF, maximum clot firmness; ML, maximum lysis; MCE, maximum clot elasticity.

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Figure 3 Association between maximum clot elasticity and severity of respiratory distress. Box plots showing (A) maximum clot elasticity of EXTEM for each severity level, (B) maximum clot elasticity of platelet components for each severity level, (C) maximum clot elasticity of INTEM for each severity level, and (D) maximum clot elasticity of FIBTEM for each severity level. MCE, maximum clot elasticity; NIRS= non-invasive respiratory support; MV, mechanical ventilation; ECMO, extracorporeal membrane oxygenation. P values calculated from the Mann–Whitney U test for pairwise comparison and adjusted using the Bonferroni method. Adjusted P values are displayed only if <0.05.

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Figure 4 Association between maximum lysis and severity of respiratory distress. Box plots showing (A) maximum lysis of EXTEM for each severity level, (B) maximum lysis of INTEM for each severity level, and (C) maximum lysis of FIBTEM for each severity level. ML, maximum lysis; NIRS, non-invasive respiratory support; MV, mechanical ventilation; ECMO, extracorporeal membrane oxygenation. P values calculated from the Mann–Whitney U test for pairwise comparison and adjusted using the Bonferroni method. P values are displayed if P < 0.05.

Hypercoagulable state in patients with severe COVID-19 is associated with favorable prognosis

Figure 5 illustrates the association between hypercoagulable status and clinical outcomes. No correlation was observed between hypercoagulable state and the disease course in moderate COVID-19 cases ( Figure 5A , median [95% confidence interval (CI)] time to recovery of hypercoagulable group vs. normocoagulable group, 6 [5–11] days vs. 6 [5–9] days, P = 0.66). However, in severe COVID-19 cases, hypercoagulable state was associated with a favorable prognosis ( Figures 5B, C , median [95% CI] time to recovery, 15 [13–18] days vs. 27 [19–censored] days, P = 0.002; median [IQR] ventilator-free days, 18 [2–21] vs. 21 [16–23], P = 0.01). There was no significant difference in mortality associated with the two coagulation states (15% vs. 13%). The normocoagulable state in severe COVID-19 cases was associated with lower fibrinogen (median [IQR], 551 [481–579] mg/dL vs. 428 [359–534] mg/dL, adjusted P value = 0.03), lower platelet count (median [IQR], 246 [194–308] × 10 3 /μL vs. 154 [126–204] × 10 3 /μL, adjusted P value <0.001), and lower complement C3 value (median [IQR], 116 [100–128] mg/dL vs. 96 [73–118] mg/dL, adjusted P value = 0.05) ( Table E3 in Additional File 1 ). No significant differences in respiratory parameters were observed between the two coagulation states. Further analysis in severe COVID-19 cases demonstrated no correlation between viral load and hypercoagulable state; there was no clear association between the viral genotype and hypercoagulable state ( Figure 6 ).

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Figure 5 Association between coagulation profile and outcomes. Association between (A) coagulation profile and time to recovery in moderate COVID-19 cases, (B) coagulation profile and time to recovery in severe COVID-19 cases, and (C) coagulation profile and ventilator-free days in severe COVID-19 cases. P values calculated from the Mann–Whitney U test for pairwise comparison and adjusted using the Bonferroni method. P values are displayed if P < 0.05.

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Figure 6 Association between coagulation profile and viral load and genotype. (A) Plasma viral load of SARS-CoV-2 at the time of coagulation profile evaluation. (B) Phylogenetic analysis of SARS-CoV-2 sequences obtained from the patients (n = 21) and their coagulation phenotypes. Scale bar indicates the measure of evolutionary distance calculated from the proportion of differing bases in the total sequence. Representative strains are indicated by GenBank accession number as references. OL672836.1(Omicron BA.1); MZ169911.1(Gamma P.1); MZ344997.1(Alpha B.1.1.7); MW598419.1(Beta B.1.351); MZ359841.1(Delta B.1.617.2).

Association between coagulation profile and complement dynamics

Figure 7 illustrates the relationship between coagulation profiles and the dynamics of complement components. Complement C3, in addition to the initial assessment, had a significantly lower minimum value in the normocoagulable group (median [IQR], 85.9 [74.8–94.1] mg/dL vs. 77.3 [51.6–86.6] mg/dL, P = 0.016) ( Figure 7A ). Meanwhile, any significant difference in the dynamics of C4 was not found between the two coagulation profile groups. Total complement activity was significantly reduced in patients in the normocoagulable group compared to those in the hypercoagulable group (median [IQR] reductions of 58 [42–69]% versus 43 [24–52]%, respectively, P = 0.001) ( Figure 7B ). Decreases in C3 minimum correlated with the decrease in platelet count(rho = 0.56, P < 0.001), and hematocrit minimums (rho = 0.61, P < 0.001) and were associated with increases in D-dimer levels(rho = -0.56, P < 0.001), fibrin degradation product(rho = -0.51, P < 0.001), KL-6(rho = -0.45, P < 0.001), and soluble thrombomodulin maxima (rho = -0.33, P = 0.01) ( Figure 7C ). Notably, changes in each component of complement system (ΔC3, ΔC4, and ΔCH50) were positively correlated with changes in hematocrit (rho = 0.53, 0.46, and 0.53, respectively, P < 0.001 for each) and ventilator-free days (rho = 0.45, 0.5, and 0.53, respectively, P < 0.001 for each), and negatively correlated with changes in KL-6 (rho = -0.34, -0.48, and -0.45, respectively, P = 0.007, <0.001, and <0.001, respectively) ( Figure 7D ).

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Figure 7 Association between complement dynamic and biomarkers in severe COVID-19 cases. (A) Association between coagulation profiles and initial minimum value for each complement component. (B) Association between coagulation profiles and changes in each complement component. (C) A heatmap showing association between minimum complement value and biomarkers, clinical outcome, and viral load evaluated with Spearman’s rank correlation coefficient. (D) A heatmap showing association between changes for each complement component and variables. Each laboratory variable was evaluated daily for 7 days from the day of intubation until ICU discharge. Minimum/Maximum values of each variable within 7 days were recorded and used to calculate the changes (e.g., ΔC3 = minimum C3/initial C3 ×100%). P values are displayed in asterisks. * P value < 0.05, ** P value < 0.01, *** P value < 0.001, **** P value < 0.0001. H= hypercoagulable status; N, normocoagulable status; CH50= total complement activity; VFD, ventilator-free days; VL, plasma viral load; sTM, soluble Thrombomodulin; vWF= von Willebrand factor; PAI-1= plasminogen activator inhibitor-1; Plt, platelet count; FG, fibrinogen; AT3, antithrombin 3; PIC, plasmin-alpha 2-plasmin inhibitor complex; TAT, thrombin-antithrombin complex; FDP, fibrin degradation product; DD, D-dimer; Hct, hematocrit; KL-6, Krebs von den lungen-6; T-bil, total bilirubin.

In this study, we evaluated the coagulation profiles of patients with different COVID-19 severities and found that while hypercoagulation was common with worsening respiratory failure, absence of hypercoagulation was associated with poor prognosis in severely ill patients. Platelet components were mainly involved in changes in blood viscoelasticity. Furthermore, the absence of hypercoagulation was also associated with coagulopathy, with complement consumption initiated by the alternative pathway activation.

Hypercoagulable state is considered a risk for COVID-19 macro-micro thrombosis, and treatment aimed at controlling hypercoagulation has been well studied so far ( 17 ). However, the efficacy of therapeutic anticoagulation and antiplatelet therapy has not been illustrated in critically ill patients ( 18 ). Our study depicted that hypercoagulable status was associated with rather favorable outcomes, which might be one of the reasons that previous randomized control trials failed to show the efficacy of anticoagulation in critically ill patients with COVID-19 ( 7 – 10 ). The hypercoagulable state is known to be influenced primarily by changes in platelet component ( 12 ), and individualized anticoagulation therapies to control the component of hypercoagulability in critically ill patients may be promising ( 19 , 20 ). We demonstrated that thromboelastometry may be a simple and effective way to stratify severity and to identify different phenotypes of coagulation status. In this study, therapeutic anticoagulation and anti-inflammatory therapy were the standard of care in most critically ill patients. This may have partially led to a favorable outcome in patients with coagulable phenotype compared to the outcome in patients with normocoagulable phenotype. Whether phenotypic differences in coagulation profiles can help in individual treatment selection, such as anticoagulation therapy, needs further evaluation.

Our study showed that complement consumption was associated with normocoagulable phenotype and with poor prognosis in mechanically ventilated patients with COVID-19. Lower C3 but not C4 observed in the normocoagulable group at the initial assessment is consistent with similar results of previous in vivo studies that reported that SARS-CoV-2 triggers the alternative pathway overactivation ( 21 ). Previous studies reported indirect activation of the alternative pathway in addition to direct activation by viral components ( 22 ): viral infection of the alveolar epithelium activates the alternative pathway via the Janus kinase/signal transducer and activator of transcription pathway ( 23 ). In our study, elevated KL-6, a biomarker of type II alveolar cells, was associated with decreased C3, and there was no significant association between the viral load and decreased C3. Based on these findings, we speculate that the host response, via type 2 alveolar epithelial cell injury rather than pathogen factors, leads to overactivation of the alternative pathway, which results in phenotypic changes in coagulation phenotype and poor prognosis. The phenotypic difference may be triggered by host heterogeneity such as genetic variants in C3 genes reported in a previous study ( 24 ). We also showed that complement consumptions were correlated with reduction in coagulation components. These findings are also consistent with those of a recent randomized trial, which reported that target C3 blockage suppressed thrombin production ( 25 ). In contrast to the findings of a previous study ( 26 ), we observed that the alternative pathway consumption was associated with consumptive coagulopathy but not with hypercoagulable profile. Higher levels of D-dimer and fibrin degradation product in relation to complement dynamics, together with the findings that maximum lysis decreases as the severity increases, may imply the activity of microthrombosis. Our findings are further supported by ex vivo experiments on virus-induced senescence, which demonstrate that the secretome enhances coagulation, promotes the formation of the lytic complement complex C5b-C9, and stimulates the formation of Neutrophil Extracellular Traps ( 27 , 28 ). Additionally, a rise in C3a enhances the differentiation of CD16 positive cytotoxic T cells in COVID-19 ( 29 ). These underlying processes are implicated in causing lung damage from COVID-19 and result in delayed recovery. The higher maximum soluble thrombomodulin and lower minimum hematocrit may suggest the feature of thrombotic microangiopathy ( 30 , 31 ). Further studies are warranted to understand the control overactivation of the alternative pathway, especially in high-risk phenotypes.

The strength of this study was the standardized introduction of evidence-based treatments in many patients from multiple hospitals, which was useful in visualizing uncontrolled pathologies in a real-world setting. However, this study had some limitations. First, as the current cohort was a predominantly unvaccinated population, extrapolation to a post-vaccinated population may not be possible. Second, considering that the SARS-CoV-2 outbreak in the region was sporadic and the local health office conducted triage of hospitalized patients during the outbreak, selection bias may have occurred in hospitalized patients. Lastly, the present study is a hypothesis-generating analysis, and further investigation is needed to validate the stratification of severity by coagulation profile and the possibility of individualizing treatment for each phenotype.

In summary, the coagulation profile changes according to the severity of respiratory failure in COVID-19. As per our findings, normocoagulable status characterized by C3 consumption is associated with delayed recovery in patients with severe COVID-19. These findings support the heterogeneous treatment effect of anticoagulation depending on COVID-19 severity. Further studies are warranted to develop phenotype-specific treatments based on the coagulation profiles.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s. Nucleotide sequence data reported are available in the DDBJ Sequenced Read Archive under the accession numbers DRX512987-DRX513007.

Ethics statement

The studies involving humans were approved by Nagoya University Hospital Institutional Review Board. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

DK: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Visualization, Writing – original draft, Writing – review & editing. TT: Data curation, Investigation, Supervision, Visualization, Writing – review & editing. TS: Data curation, Investigation, Methodology, Supervision, Writing – review & editing. YI: Data curation, Methodology, Supervision, Writing – review & editing. KN: Formal Analysis, Funding acquisition, Methodology, Supervision, Writing – review & editing. MO: Investigation, Supervision, Writing – review & editing. TK: Data curation, Investigation, Supervision, Writing – review & editing. TYo: Data curation, Investigation, Supervision, Writing – review & editing. HK: Data curation, Investigation, Supervision, Writing – review & editing. RO: Data curation, Investigation, Supervision, Writing – review & editing. RM: Data curation, Investigation, Supervision, Writing – review & editing. TG: Data curation, Investigation, Supervision, Writing – review & editing. HH: Data curation, Investigation, Supervision, Writing – review & editing. AI: Investigation, Supervision, Writing – review & editing, Data curation. YK: Data curation, Investigation, Supervision, Writing – review & editing. NJ: Data curation, Investigation, Supervision, Writing – review & editing. KI: Data curation, Investigation, Supervision, Writing – review & editing. RK: Data curation, Investigation, Supervision, Writing – review & editing. MT: Data curation, Investigation, Supervision, Writing – review & editing. HO: Data curation, Investigation, Supervision, Writing – review & editing. TYa: Conceptualization, Funding acquisition, Supervision, Writing – review & editing. YG: Conceptualization, Data curation, Funding acquisition, Investigation, Supervision, Writing – review & editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by grants from the Japan Agency for Medical Research and Development (AMED) to DK, TYa, and YG (grant no., 20fk0108532h0001) and Japan Society for the Promotion of Science (JSPS) to DK and KN (grant no., JP 22K09180).

Acknowledgments

The authors thank Yasushi Ogawa for the invaluable help in conducting this study.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2024.1337070/full#supplementary-material

1. Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A novel coronavirus from Patients with pneumonia in China, 2019. N Engl J Med . (2020) 382:727–33. doi: 10.1056/NEJMoa2001017

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Conway EM, Mackman N, Warren RQ, Wolberg AS, Mosnier LO, Campbell RA, et al. Understanding COVID-19-associated coagulopathy. Nat Rev Immunol . (2022) 22:639–49. doi: 10.1038/s41577-022-00762-9

3. Moores LK, Tritschler T, Brosnahan S, Carrier M, Collen JF, Doerschug K, et al. Thromboprophylaxis in patients with COVID-19: A brief update to the CHEST guideline and expert panel report. Chest . (2022) 162:213–25. doi: 10.1016/j.chest.2022.02.006

4. Gómez CA, Sun CK, Tsai IT, Chang YP, Lin MC, Hung IY, et al. Mortality and risk factors associated with pulmonary embolism in coronavirus disease 2019 patients: a systematic review and meta-analysis. Sci Rep . (2021) 11:16025. doi: 10.1038/s41598-021-95512-7

5. Pellegrini D, Kawakami R, Guagliumi G, Sakamoto A, Kawai K, Gianatti A, et al. Microthrombi as a major cause of cardiac injury in COVID-19: A pathologic study. Circulation . (2021) 143:1031–42. doi: 10.1161/CIRCULATIONAHA.120.051828

6. Fahmy OH, Daas FM, Salunkhe V, Petrey JL, Cosar EF, Ramirez J, et al. Is microthrombosis the main pathology in coronavirus disease 2019 severity?-A systematic review of the postmortem pathologic findings. Crit Care Explor . (2021) 3:e0427. doi: 10.1097/CCE.0000000000000427

7. Reis S, Popp M, Schießer S, Metzendorf MI, Kranke P, Meybohm P, et al. Anticoagulation in COVID-19 patients - An updated systematic review and meta-analysis. Thromb Res . (2022) 219:40–8. doi: 10.1016/j.thromres.2022.09.001

8. Pilia E, Belletti A, Fresilli S, Lee TC, Zangrillo A, Finco G, et al. The effect of heparin full-dose anticoagulation on survival of hospitalized, non-critically ill COVID-19 patients: A meta-analysis of high quality studies. Lung . (2023) 201:135–47. doi: 10.1007/s00408-023-00599-6

9. REMAP-CAP Investigators, ACTIV-4a Investigators, ATTACC Investigators, Goligher EC, Bradbury CA, McVerry BJ, et al. Therapeutic anticoagulation with heparin in critically ill patients with Covid-19. N Engl J Med . (2021) 385:777–89. doi: 10.1056/NEJMoa2103417

10. ATTACC Investigators, ACTIV-4a Investigators, REMAP-CAP Investigators, Lawler PR, Goligher EC, Berger JS, et al. Therapeutic anticoagulation with heparin in noncritically ill patients with Covid-19. N Engl J Med . (2021) 385:790–802. doi: 10.1056/NEJMoa2105911

11. Kalil AC, Patterson TF, Mehta AK, Tomashek KM, Wolfe CR, Ghazaryan V, et al. Baricitinib plus remdesivir for hospitalized adults with Covid-19. N Engl J Med . (2021) 384:795–807. doi: 10.1056/NEJMoa2031994

12. Solomon C, Ranucci M, Hochleitner G, Schöchl H, Schlimp CJ. Assessing the methodology for calculating platelet contribution to clot Strength (platelet component) in thromboelastometry and thrombelastography. Anesth Analg . (2015) 121:868–78. doi: 10.1213/ANE.0000000000000859

13. Lang T, Bauters A, Braun SL, Pötzsch B, von Pape KW, Kolde HJ, et al. Multi-centre investigation on reference ranges for ROTEM thromboelastometry. Blood Coagul Fibrinolysis . (2005) 16:301–10. doi: 10.1097/01.mbc.0000169225.31173.19

14. Whiting D, DiNardo JA. TEG and ROTEM: technology and clinical applications. Am J Hematol . (2014) 89:228–32. doi: 10.1002/ajh.23599

15. Tsutsui T, Muramatsu N. Care-needs certification in the long-term care insurance system of Japan. J Am Geriatr Soc . (2005) 53:522–7. doi: 10.1111/j.1532-5415.2005.53175.x

16. Dodd LE, Follmann D, Wang J, Koenig F, Korn LL, Schoergenhofer C, et al. Endpoints for randomized controlled clinical trials for COVID-19 treatments. Clin Trials . (2020) 17:472–82. doi: 10.1177/1740774520939938

17. Poor HD. Pulmonary thrombosis and thromboembolism in COVID-19. Chest . (2021) 160:1471–80. doi: 10.1016/j.chest.2021.06.016

18. REMAP-CAP Writing Committee for the REMAP-CAP Investigators;, Bradbury CA, Lawler PR, Stanworth SJ, Wolberg AS, Mosnier LO, Campbell RA, et al. Effect of antiplatelet therapy on survival and organ support-free days in critically ill patients with COVID-19: A randomized clinical trial. JAMA . (2022) 327:1247–59. doi: 10.1001/jama.2022.2910

19. Kruse JM, Magomedov A, Kurreck A, Münch FH, Koerner R, Kamhieh-Milz J, et al. Thromboembolic complications in critically ill COVID-19 patients are associated with impaired fibrinolysis. Crit Care . (2020) 24:676. doi: 10.1186/s13054-020-03401-8

20. Roh DJ, Eiseman K, Kirsch H, Yoh N, Boehme A, Agarwal S, et al. Hypercoagulable viscoelastic blood clot characteristics in critically ill coronavirus disease 2019 patients and associations with thrombotic complications. J Trauma Acute Care Surg . (2021) 90:e7–12. doi: 10.1097/TA.0000000000002963

21. Lo MW, Amarilla AA, Lee JD, Albornoz EA, Modhiran N, Clark RJ, et al. SARS-CoV-2 triggers complement activation through interactions with heparan sulfate. Clin Transl Immunol . (2022) 11:e1413. doi: 10.1002/cti2.1413

CrossRef Full Text | Google Scholar

22. Yu J, Yuan X, Chen H, Chaturvedi S, Braunstein EM, Brodsky RA. Direct activation of the alternative complement pathway by SARS-CoV-2 spike proteins is blocked by factor D inhibition. Blood . (2020) 136:2080–9. doi: 10.1182/blood.2020008248

23. Yan B, Freiwald T, Chauss D, Wang L, West E, Mirabelli C, et al. SARS-CoV-2 drives JAK1/2-dependent local complement hyperactivation. Sci Immunol . (2021) 6:eabg0833. doi: 10.1126/sciimmunol.abg0833

24. Asteris PG, Gavriilaki E, Touloumenidou T, Koravou EE, Koutra M, Papayanni PG, et al. Genetic prediction of ICU hospitalization and mortality in COVID-19 patients using artificial neural networks. J Cell Mol Med . (2022) 26:1445–55. doi: 10.1111/jcmm.17098

25. Skendros P, Germanidis G, Mastellos DC, Antoniadou C, Gavriilidis E, Kalopitas G, et al. Complement C3 inhibition in severe COVID-19 using compstatin AMY-101. Sci Adv . (2022) 8:eabo2341. doi: 10.1126/sciadv.abo2341

26. Ma L, Sahu SK, Cano M, Kuppuswamy V, Bajwa J, McPhatter J, et al. Increased complement activation is a distinctive feature of severe SARS-CoV-2 infection. Sci Immunol . (2021) 6:eabh2259. doi: 10.1126/sciimmunol.abh2259

27. Lee S, Yu Y, Trimpert J, Benthani F, Mairhofer M, Richter-Pechanska P, et al. Virus-induced senescence is a driver and therapeutic target in COVID-19. Nature . (2021) 599:283–9. doi: 10.1038/s41586-021-03995-1

28. Schmitt CA, Tchkonia T, Niedernhofer LJ, Robbins PD, Kirkland JL, Lee S. COVID-19 and cellular senescence. Nat Rev Immunol . (2023) 23:251–63. doi: 10.1038/s41577-022-00785-2

29. Georg P, Astaburuaga-García R, Bonaguro L, Brumhard S, Michalick L, Lippert LJ, et al. Complement activation induces excessive T cell cytotoxicity in severe COVID-19. Cell . (2022) 185:493–512.e25. doi: 10.1016/j.cell.2021.12.040

30. Lam LKM, Reilly JP, Rux AH, Murphy SJ, Kuri-Cervantes L, Weisman AR, et al. Erythrocytes identify complement activation in patients with COVID-19. Am J Physiol Lung Cell Mol Physiol . (2021) 321:L485–9. doi: 10.1152/ajplung.00231.2021

31. Roh JD, Kitchen RR, Guseh JS, McNeill JN, Aid M, Martinot AJ, et al. Plasma proteomics of COVID-19-associated cardiovascular complications: implications for pathophysiology and therapeutics. JACC Basic Transl Sci . (2022) 7:425–41. doi: 10.1016/j.jacbts.2022.01.013

Keywords: COVID-19, blood coagulation disorders, rotational thromboelastometry, alternative complement pathway, microthrombosis

Citation: Kasugai D, Tanaka T, Suzuki T, Ito Y, Nishida K, Ozaki M, Kutsuna T, Yokoyama T, Kaneko H, Ogata R, Matsui R, Goshima T, Hamada H, Ishii A, Kodama Y, Jingushi N, Ishikura K, Kamidani R, Tada M, Okada H, Yamamoto T and Goto Y (2024) Association between loss of hypercoagulable phenotype, clinical features and complement pathway consumption in COVID-19. Front. Immunol. 15:1337070. doi: 10.3389/fimmu.2024.1337070

Received: 12 November 2023; Accepted: 27 February 2024; Published: 11 March 2024.

Reviewed by:

Copyright © 2024 Kasugai, Tanaka, Suzuki, Ito, Nishida, Ozaki, Kutsuna, Yokoyama, Kaneko, Ogata, Matsui, Goshima, Hamada, Ishii, Kodama, Jingushi, Ishikura, Kamidani, Tada, Okada, Yamamoto and Goto. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Daisuke Kasugai, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Wait, how many? —

German man got 217 covid shots over 29 months—here’s how it went, it conflicts with concerns of repeat boosters, but authors warn against hypervaccination..

Beth Mole - Mar 5, 2024 7:40 pm UTC

German man got 217 COVID shots over 29 months—here’s how it went

A 62-year-old man in Germany decided to get 217 COVID-19 vaccinations over the course of 29 months —for "private reasons." But, somewhat surprisingly, he doesn't seem to have suffered any ill effects from the excessive immunization, particularly weaker immune responses, according to a newly published case study in The Lancet Infectious Diseases .

The case is just one person, of course, so the findings can't be extrapolated to the general population. But, they conflict with a widely held concern among researchers that such overexposure to vaccination could lead to weaker immune responses. Some experts have raised this concern in discussions over how frequently people should get COVID-19 booster doses.

In cases of chronic exposure to a disease-causing germ, "there is an indication that certain types of immune cells, known as T-cells, then become fatigued, leading to them releasing fewer pro-inflammatory messenger substances," according to co-lead study author Kilian Schober from the Institute of Microbiology – Clinical Microbiology, Immunology and Hygiene. This, along with other effects, can lead to "immune tolerance" that leads to weaker responses that are less effective at fighting off a pathogen, Schober explained in a news release.

The German man's extreme history of hypervaccination seemed like a good case to look for evidence of such tolerance and weaker responses. Schober and his colleagues learned of the man's case through news headlines—officials had opened a fraud investigation against the man, confirming 130 vaccinations over nine months, but no criminal charges were ever filed. "We then contacted him and invited him to undergo various tests in Erlangen [a city in Bavaria]," Schober said. "He was very interested in doing so." The man then reported an additional 87 vaccinations to the researchers, which in total included eight different vaccine formulations, including updated boosters.

The researchers were able to collect blood and saliva samples from the man during his 214th to 217th vaccine doses. They compared his immune responses to those of 29 people who had received a standard three-dose series.

Throughout the dizzying number of vaccines, the man never reported any vaccine side effects, and his clinical testing revealed no abnormalities related to hypervaccination. The researchers conducted a detailed look at his responses to the vaccines, finding that while some aspects of his protection were stronger, on the whole, his immune responses were functionally similar to those from people who had far fewer doses. Vaccine-spurred antibody levels in his blood rose after a new dose but then began declining, similar to what was seen in the controls.

His antibodies' ability to neutralize SARS-CoV-2 appeared to be between fivefold and 11-fold higher than in controls, but the researchers noted that this was due to a higher quantity of antibodies, not more potent antibodies. Specific subsets of immune cells, namely B-cells trained against SARS-CoV-2's spike protein and T effector cells, were elevated compared with controls. But they seemed to function normally. As another type of control, the researchers also looked at the man's immune response to an unrelated virus, Epstein-Barr, which causes mononucleosis. They found that the unbridled immunizations did not negatively impact responses to that virus, suggesting there were no ill effects on immune responses generally.

Last, multiple types of testing indicated that the man has never been infected with SARS-CoV-2. But the researchers were cautious to note that this may be due to other precautions the man took beyond getting 217 vaccines.

"In summary, our case report shows that SARS-CoV-2 hypervaccination did not lead to adverse events and increased the quantity of spike-specific antibodies and T cells without having a strong positive or negative effect on the intrinsic quality of adaptive immune responses," the authors concluded. "Importantly," they added, "we do not endorse hypervaccination as a strategy to enhance adaptive immunity."

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Case-control study of patient characteristics, knowledge of the COVID-19 disease, risk behaviour and mental state in patients visiting an emergency room with COVID-19 symptoms in the Netherlands

J. p. m. van der valk.

1 Department of Pulmonary Medicine, Franciscus Gasthuis & Vlietland, Rotterdam, The Netherlands

F. W. J. Heijboer

H. van middendorp.

2 Department of Health, Medical and Neuropsychology, Leiden University, Leiden, The Netherlands

A. W. M. Evers

J. c. c. m. in ‘t veen, associated data.

All relevant data are within the manuscript and its Supporting information files.

Coronavirus disease 2019 is a serious respiratory virus pandemic. Patient characteristics, knowledge of the COVID-19 disease, risk behaviour and mental state will differ between individuals. The primary aim of this study was to investigate these variables in patients visiting an emergency department in the Netherlands during the COVID-19 pandemic and to compare the “COVID-19 suspected” (positive and negative tested group) with the “COVID-19 not suspected” (control group) and to compare in the “COVID-19 suspected” group, the positive and negative tested patients.

Consecutive adult patients, visiting the emergency room at the Franciscus Gasthuis & Vlietland, Rotterdam, the Netherlands, were asked to fill out questionnaires on the abovementioned items on an iPad. The patients were either “COVID-19 suspected” (positive and negative tested group) or “COVID-19 not suspected” (control group).

This study included a total of 159 patients, 33 (21%) tested positive, 85 (53%) negative and 41 (26%) were COVID-19 not suspected (control group). All patients in this study were generally aware of transmission risks and virulence and adhered to the non-pharmaceutical interventions. Working as a health care professional was correlated to a higher risk of SARS-Cov-2 infection (p- value 0.04). COVID-19 suspected patients had a significantly higher level of anxiety compared to COVID-19 not suspected patients (p-value < 0.001). The higher the anxiety, the more seriously hygiene measures were followed. The anxiety scores of the patients with (pulmonary) comorbidities were significantly higher than without comorbidities.

This is one of the first (large) study that investigates and compares patient characteristics, knowledge, behaviour, illness perception, and mental state with respect to COVID-19 of patients visiting the emergency room, subdivided as being suspected of having COVID-19 (positive or negative tested) and a control group not suspected of having COVID-19. All patients in this study were generally aware of transmission risks and virulence and adhered to the non-pharmaceutical interventions. COVID-19 suspected patients and patients with (pulmonary) comorbidities were significantly more anxious. However, there is no mass hysteria regarding COVID-19. The higher the degree of fear, the more carefully hygiene measures were observed. Knowledge about the coping of the population during the COVID-19 pandemic is very important, certainly also in the perspective of a possible second outbreak of COVID-19.

Introduction

Coronavirus disease 2019 (COVID-19) is caused by the SARS-Cov-2 virus and constitutes the most serious respiratory virus pandemic since the 1918 H1N1 influenza pandemic. COVID-19 is characterized by fever and respiratory symptoms like cough, sneeze, and shortness of breath [ 1 ]. SARS-Cov-2 virus spreads by transmission of respiratory (small) droplets containing the virus particles from person to person, mostly in close contact [ 2 ]. Symptomatic patients spread the virus very fast. The SARS-Cov-2 virus can also be transmitted by asymptomatic persons and by contact with contaminated surfaces. Occasionally, the virus can be transmitted from humans to animals and vice versa [ 3 ]. Prevention of transmission is very important in the absence of an effective COVID-19 vaccine or treatment.

Non-pharmaceutical interventions (NPIs) to avoid transmission of SARS-Cov-2 involve hygiene measures, limitation of human contact, and social distancing. The Dutch National Institute for Public Health and Environment (RIVM) recommends washing hands thoroughly and frequently, coughing and sneezing in the inside of the elbow, avoiding shaking hands, keeping a distance of 1.5 meters (2 arms’ lengths) from others, and staying at home as much as possible.

Knowledge of contamination risks, severity of SARS-Cov-2 infection, the chance of recovery and long-term consequences of the disease will differ between individuals, including those individuals with and without a SARS-Cov-2 infection, and might influence the (risk) behaviour of people. Also, the mental state and comorbidities of people may influence (risk) behaviour and consequently the chance of SARS-Cov-2 contamination. Knowledge about the coping of the population during the COVID-19 pandemic is very important, certainly also in the perspective of a possible second outbreak of COVID-19.

The present report concerns an observational study on patient characteristics and knowledge of the disease, risk behaviour, illness perception, and mental state (at the time of assessment) of patients visiting an emergency room in the Netherlands, subdivided as “COVID-19 suspected” (positive and negative tested group) or “COVID-19 not suspected” (control group).

These variables were measured for three groups: those tested positive for SARS-Cov-2, those tested negative, and the control group. The degree of anxiety in the total group has also been correlated to comorbidities and the hygiene measures, human contact, and social distancing.

Material and method

Study design and patient selection.

This study was designed as an observational questionnaire study and registered in the Dutch Trial Register as PA tient’s knowledge and behaviour o N the COVID-19 disease and as D eter MI nants of C ontamination (PANDEMIC) study (trial number NL8563). The study was submitted to the medical ethical review board and was considered not subject to the Medical Research Involving Human Subjects Act (WMO; W20.075). We adhered to the methods and procedures of the Strengthening the Reporting of Observational Studies in Epidemiology (STOBE) guidelines for reporting this study. It was not possible to involve patients or the public in the design, or conduct, or reporting, or dissemination plans of our research, because of the very fast procedure in the COVID-19 crisis.

Consecutive adult patients (>18 years of age) visiting the emergency room at the Franciscus Gasthuis & Vlietland, Rotterdam, the Netherlands, were asked to participate in this study (n> 200). The patients were “COVID-19 suspected” or “COVID-19 not suspected” (control group). All patients with upper- or lower respiratory symptoms were considered as possible COVID-19 positive. Before completing the survey, participants gave their written informed consent. Reasons for non-participation were patients with a language barrier or patients who could not operate an iPad or who had a severe medical condition (direct transfer to intensive care) or lack of iPads due to the large number of patients arriving at the emergency room at the same time.

A total of 164 patients were included in the period between April 10 th and June 20 th , 2020. Patients were asked to fill out their general patient characteristics and answer questions on their knowledge of the disease, risk behaviour, illness perception, and mental status on an iPad with disposable cover to respect hygiene measures. Of these 164 patients, 5 patients did not complete the questionnaires because of logistic–or personal reasons ( Fig 1 ). General patient characteristics and information consisted of year of birth, sex, the number of people in their household, and profession type (if applicable). Vital professions were defined as those in sectors necessary to keeping society running during the COVID-19 crisis, for example: health care, policing, food, waste, and transport. Comorbidities were derived from the electronic patient files.

An external file that holds a picture, illustration, etc.
Object name is pone.0249847.g001.jpg

Patients’ knowledge of SARS-Cov-2 was investigated with a self-developed questionnaire on the severity of the disease, route of contamination, and the importance of government measures. Illness perception was measured with questions on the patient’s perception of COVID-19 with respect to their specific situation. For example: ‘ If you are infected with SARS-Cov-2 , do you think that you could die from this infection ? ’ (Attachment 1).

A second questionnaire concerned risk behaviour in terms of hygiene, human contact, and social distancing. The questionnaire was designed to study whether patients adhered to the measures imposed by the Dutch National Institute for Public Health and Environment. For example: Do you wash your hands frequently; do you avoid group gatherings; do you maintain a 1 . 5-meter distance between yourself and others ? (Attachment 2).

The last 6-item questionnaire was the validated State-Trait Anxiety Inventory–short (STAI-s) survey [ 4 ] to measure the mental state of the COVID-19 suspected patients from the beginning of the COVID-19 crisis (1st of March 2020) to the time of administering the questionnaires.

The questionnaires were filled out before test results (COVID-19 negative/positive) were known. Three patients did not complete the second questionnaire and 5 patients did not complete the third questionnaire. These data were not part of the analysis.

Patients with a positive nasal Polymerase chain reaction (PCR) swab to SARS-Cov-2 or having SARS-Cov-2 antibodies were considered to be COVID-19 positive.

A comparison is made between the “COVID-19 suspected” (positive and negative tested group) with the “COVID-19 not suspected” (control group) and in the “COVID-19 suspected” group, the positive and negative tested patients.

Statistical analysis

Patient characteristics were reported in terms of mean, ranges, and proportions. Knowledge, risk behaviour, and illness perception of COVID-19 were reported descriptively. The differences in terms of these factors were compared between 3 groups (those tested positive for SARS-Cov-2, those tested negative, and the control group) using the Kruskal-Wallis test, and were described with p-values. P-values <0.05 were considered as significant.

Mental state was measured by the STAI-s score questionnaire. The sum of the 6 questions was calculated. This score was multiplied by 20/6 to be compared with the long version of the STAI. The One-Way ANOVA test was used to compare the mean scores on anxiety of the 3 groups. A cut off point of 39–40 has been suggested to detect clinically significant anxiety symptoms.

The STAI-s scores were correlated with the risk behaviour score for the areas of hygiene, human contact, and social distancing using linear logistic regression analysis. The risk behaviour score was the sum of the questions divided by the number of questions. The score on a 5-point Likert scale was: 0 points = no risk to 4 points = most risk and on a 2-point Likert scale: 1 point = no risk and 3 points = most risk). The outcomes of the regression analysis were reported with the regression standardized coefficient (ß), and the CI and p-values. Also, the mean STAI-s score was related to comorbidities with linear logistic regression analysis. Statistical analyses were done using SPSS statistics 24.

Study population

This study included a total of 159 patients including 118 COVID-19 suspected patients and 41 COVID-19 not suspected patients (control group). The mean age of all the patients (inclusive control group) was 50.42 years (range 19–86 years), with 70 males (44%) and 89 females (56%) ( Table 1 ). The patients were referred to the Franciscus Gasthuis and Vlietland, Rotterdam, by their general practitioner or taken to hospital directly by ambulance. Of the COVID-19 suspected patients in this study, 33 (21%) patients tested positive and 85 (53%) tested negative for COVID-19.

The average household was 2.76 people (range 1–7) in the total group and was similar for the positive and the negative group. Patient characteristics are summarized in Table 1 . Of the SARS-Cov-2 positive cases, 16 patients (48%) had a vital profession (and this differed significantly (p-value 0.04) compared to 23 (26%) in the negative tested group ( Fig 2A ). More than 60% of these patients worked in the medical sector, mostly in nursing homes or care institutions (56%) ( Fig 2B , Table 1 ). Some of these patients worked with COVID-19 patients and a substantial part worked with colleagues also infected with Sars-Cov2.

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Significantly more patients infected with SARS-Cov-2 work in a vital profession compared to uninfected patients and the control group (p-value 0.04), and most of them work in the medical sector.

Knowledge/Illness perception

COVID-19 was seen as a severe disease: almost 90% of the total study population believe the disease is worse than influenza. Ninety-eight percent of patients knew that contaminations most frequently occur through person to person contact. Approximately 18% of the patients considered wearing face masks useful in the prevention of SARS-Cov-2 infection. Ninety-four percent of patients thought that adhering to NPIs helps to prevent infection. There was no difference between the positive-tested, negative-tested, and control group with respect to knowledge about COVID-19 ( Table 2 ).

Group comparison for non-pharmaceutical interventions (NPIs) and SARS-Cov-2 infection in the positive-tested, negative-tested (COVID-19 suspected), and control group (COVID-19 not suspected) analyses by the Kruskal-Wallis test.

In this study population (COVID-19 suspected and control group), 32% believed they would not be infected by SARS-Cov-2, 37% did not expect to become seriously ill and 42% did not expect to die from the infection. Of all the patients, 20% did not consider the virus to be contagious. The illness perception scores did not differ between the 3 tested groups.

Risk behaviour

For all patients (COVID-19 suspected- and control group), 43% washed their hands more than 10 times a day and approximately 81% reported washing their hands always/almost always for more than 20 seconds. More than 90% of patients reported using the inside of their elbow to cough and sneeze. Only 11% of patients reported wearing a face mask for protection. Almost all patients indicated always/almost always keeping a 1.5-meter distance from others (95%), however the control group reported adhering less to this 1.5- meter measure (p-value 0.02). There was no significant difference between the positive-tested, negative-tested, and control group in terms of other abovementioned risk behaviour ( Table 2 ).

In this total study population, 72% reported always/almost always staying home during the COVID-19 pandemic; however, the control group reported staying home significantly less (p- value < 0.001). Thirty percent of all patients reported visiting shops (beyond the basic necessities of life) and 14% reported visiting markets, parks or beaches. The positive-tested group reported visiting markets, parks or beaches less often than the negative-tested group and control group (p-value 0.07). Approximately 16% and 9% of the study population reported visiting people older than 60 years and/or receiving visits from people aged 60 year or older, respectively. Attending group gatherings (> 6 people) was reported by 1% of the total study population.

Mental state

The mean anxiety score was 48.56 points (range 23–67) in the negative-tested group and 50.10 points (range 27–77) in the positive-tested group (not significantly different). These anxiety scores of these COVID-19 suspected patients (mean 49.01, range 23.33–76.67) were significantly higher (p-value < 0.001) than the anxiety score of the control group (mean 39.00, range 20–70).

The anxiety scores of all patients were significantly inversely correlated to risk behaviour in the hygiene domain (ß 0.20, CI 0.93–7.62, p-value 0.01). The domains human contact and distancing were not significantly related to the anxiety scores in study group overall, with p-values of 0.87 and 0.89, respectively. The anxiety scores of the patients without comorbidities (mean 41.25, range 20–70) were significantly lower (ß 0.28, CI 3.47–11.79, p-value < 0.001) than the patients with comorbidities (48.88, range 23–77). Patients with a history of respiratory disease had significantly higher (ß 0.23, CI 1.83–10.42, p-value 0.05) anxiety scores (corrected for other comorbidities) than those without comorbidities.

The primary aim of this study was to investigate patient characteristics, knowledge of contamination risks, the severity of the disease, illness perception, and mental state in patients visiting an emergency department in the Netherlands during the COVID-19 pandemic. The “COVID-19 suspected” (positive and negative tested group) was compared with the “COVID-19 not suspected” (control group) and in the “COVID-19 suspected” group, the positive and negative tested patients were compared.

The mean STAI-s score, which represents anxiety, was significantly higher in the COVID-19 suspected patients compared to the general population requiring emergency care. No significant difference in the anxiety score was observed in the positive-tested and negative-tested patients. Moreover, COVID-19 suspected patients and patients with (pulmonary) comorbidities were significantly more anxious, and the higher the degree of fear, the more seriously the hygiene measures were followed.

Remarkably, more than 50% of the positive-tested patients worked in health care and most of them in the medical sector. The percentage of the SARS-Cov-2 positive-tested group who reported having visited public places was lower than in the other two groups. The control group reported adhering less to the 1.5- meter measure and stayed at home less.

Furthermore, the severity of SARS-Cov-2 infection, the risk of contamination and the importance of NPIs were well understood by all patients, and the measures were therefore properly observed in the positive-tested, negative-tested, and control group. The age of the patients in this study was quite young (mean age of 50.42 years).

Significantly higher anxiety was observed in the COVID-19 suspected patients than reported in the control group and the average research population [ 5 ]. This is in line with the large degree of fear that was previously reported by Liu et al., stating that patients with COVID-19 experienced high levels of anxiety (mean STAI score of 58) and low sleep quality [ 6 ]. The current study adds to these findings that this anxiety is already present in suspected patients and not only in diagnosed patients or in the total population. There was thus no mass hysteria regarding COVID-19. In line with our study, Motta Zanin et al. investigated the public Italian perception of health risk through the administration of a questionnaire in more and less COVID-19 effected regions. They demonstrated that the participants mainly expressed uncertainty, fear, and sadness in the more effected regions [ 7 ]. Mainly, patients with (pulmonary) comorbidities were significantly more anxious in our study, and the higher the fear, the better hygiene measures were followed.

The percentage of SARS-Cov-2 infected health care professionals in our study is higher than that reported by Heinzerling et al. [ 8 ]. In that study involving 121 hospital health care workers who were exposed to COVID-19 patients in a Hospital in California, 36% developed symptoms during 14 days after exposure and only 3 people tested positive. Another study demonstrated that 92% of the health care personnel in the United States had at least one symptom (fever, cough, or shortness of breath) after exposure to SARS-Cov-2-infected patients, however this was not proven to be COVID-19-related [ 9 ]. Barrett et al. demonstrated that the prevalence of SARS-CoV-2 infection was higher among health care workers (7.3%) than in non-health care workers (0.4%) [ 10 ].

The severity of SARS-Cov-2 infection, the risk of contamination and the importance of NPIs were well understood by all patients and the measures to prevent infection were (therefore) reported as being adhered to in this study. In line with our study, a cross-sectional survey in Hong Kong with 765 participants demonstrated that the overall knowledge and understanding of COVID-19 was good and most respondents agreed that NPIs could reduce the transmission of COVID-19 [ 11 ].

There was clear communication from the Dutch government about the importance of NPIs to prevent transmission of SARS-Cov-2. The study of Gesser-Edelsburg et al. underscores this importance of the public trust in adhering to NPIs to prevent transmission of SARS-Cov-2. They showed in an online survey in the Israeli public with 1056 participants that the higher the public trust and evaluation of crisis management was, the greater the compliance of the public with the government guidelines [ 12 ].

The percentage who reported using a face mask in this study was much lower compared to a study in China, which found 97% wore face masks [ 13 ]. At the beginning of the COVID-19 period, face masks were not compulsory and often even not available in nursing homes and care institutions in the Netherlands.

The lower average age in this study compared to the SARS-Cov-2-infected populations reported in other studies can be explained by the selection criteria for referring patients to the hospital in the Netherlands. General practitioners refer patients with relatively severe symptoms and patients for whom health improvements could reasonably be expected, per the Dutch referral policy. This policy excludes patients with mild symptoms and vulnerable elderly patients not eligible for treatment in the hospital. General practitioners and nursing home doctors take into account whether medical treatment is desirable and useful in respect to the quality of life of each individual patient. This approach is in contrast to a retrospective cohort study included 124 patients who required 911 Emergency Medical Services care for COVID-19 in Washington. This study revealed that most patients with COVID-19 presenting to emergency medical services were older and had multiple chronic health conditions [ 14 ].

This is one of the first (large) study that investigates and compares patient characteristics, knowledge, behaviour, illness perception, and mental state with respect to COVID-19 of patients visiting the emergency room, subdivided as being suspected of having COVID-19 (who then tested either positive or negative) and a control group not suspected of having COVID-19. The limitations of this study include the state of COVID-19 testing and measures taken by the population in the Netherlands, which may not be generalizable for other countries. Also, seriously ill patients who were respiratory insufficient, patients with a language barrier, and patients who were not able to handle an iPad were excluded from this study. Finally, the data on risk behaviours were self-reported, which implies that social desirability could have played a role in the low risk behaviours described in this sample.

Regulatory agencies urge adherence to NPIs to reduce SARS-Cov-2 virus contamination [ 15 , 16 ]. In the group suspected of infection, risk behaviour was no greater in the group that tested positive than in the group that tested negative. High exposure to SARS-Cov-2 in the health care sector was probably the most important factor in being infected with COVID-19. This specific patient group should try to prevent infection by using protective material, including face masks. However, at the beginning of the COVID-19 crisis most of the available protective equipment was destined for hospitals and there was a shortage in nursing homes and care institutions. This may explain the high number of infections in nursing homes and care institutions.

However, the disproportionately large number of infections in health care workers may also suggest a super spreading pattern [ 17 ] as observed in church choirs, gyms, and animal slaughterhouses. Health care professionals often work and stay in poorly ventilated rooms, as do workers in nursing homes and care institutions. Furthermore, aerosol generating procedures (tracheal intubation and non-invasive ventilation) increase the risk of transmission of SARS-Cov-2 to health care workers [ 18 ]. The health care workers in this study mainly worked in health care institutions not involved in these procedures.

This is the first (large) study that investigates and compares patient characteristics, knowledge, behaviour, illness perception, and mental state with respect to COVID-19 of patients visiting the emergency room, subdivided as being suspected of having COVID-19 and a control group not suspected of having COVID-19. All patients in this study were generally aware of transmission risks and virulence and adhered to the NPIs. Most patients suspected of having COVID-19 who visited our emergency department had a high degree of anxiety compared to the general population. There is thus no mass hysteria regarding COVID-19, but anxiety was higher among the patients suspected of having COVID-19. Patients with (pulmonary) comorbidities were significantly more anxious and experienced a higher degree of fear, which was correlated with better behaviour as regards hygiene measures. Knowledge about the coping of the population during the COVID-19 pandemic is very important, certainly also in the perspective of a possible second outbreak of COVID-19.

Evidence before this study

We searched PubMed using the keywords “COVID-19”, “2019-nCoV”, “SARS-CoV-2” and “emergency”, “anxiety”, “mental state”, “fear”, “patient characteristics”, “knowledge”, “risk behaviour”. We screened 90 articles (updated 21th of August 2020) and considered 4 studies relevant to our research goal. We also checked references to relevant articles (‘snowballing’).

( COVID-19[Title] OR 2019-nCoV[Title] OR SARS-CoV-2[Title]) AND emergency[Title] AND (anxiety OR mental state OR fear) AND (patient characteristics OR knowledge OR risk behaviour ).

Added value of this study

We investigate patient characteristics, knowledge of contamination risks, the severity of the disease, illness perception, and mental state in patients visiting an emergency department in the Netherlands during the COVID-19 pandemic. We found that the severity of SARS-Cov-2 infection, the risk of contamination and the importance of NPIs were well understood. Most patients suspected of having COVID-19 had a high degree of anxiety compared to the general population. Patients with (pulmonary) comorbidities were significantly more anxious which was correlated with better behaviour as regards hygiene measures. There is thus no mass hysteria regarding COVID-19, but anxiety was higher among the patients suspected of having COVID-19.

Implications of all the available evidence

Clear communication from the government about the importance of NPIs to prevent transmission of SARS-Cov-2 ensures the adherence to NPIs. High degree of anxiety is present in COVID- 19 suspected patients and in the patients with (pulmonary) comorbidities. It is important to pay attention to this psychological aspect of COVID-19 in this particular part of the population. Knowledge about the coping of the population during the COVID-19 pandemic is very important, certainly also in the perspective of a possible second outbreak of COVID-19.

Patient and public involvement

No patient involved.

Supporting information

S1 questionnaire, s2 questionnaire, s1 protocol, s2 protocol, s3 protocol, abbreviations, funding statement.

There was not funding for this study.

Data Availability

  • PLoS One. 2021; 16(4): e0249847.

Decision Letter 0

18 Jan 2021

PONE-D-20-28005

Case- control study of patient characteristics, knowledge of the COVID-19 disease, risk behaviour and mental state in patients visiting an emergency room with COVID-19 symptoms in the Netherlands

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Reviewer #1: Partly

Reviewer #2: No

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Reviewer #1: Important note: This review pertains only to ‘statistical aspects’ of the study and so ‘clinical aspects’ [like medical importance, relevance of the study, ‘clinical significance and implication(s)’ of the whole study, etc.] are to be evaluated [should be assessed] separately/independently. Further please note that any ‘statistical review’ is generally done under the assumption that (such) study specific methodological [as well as execution] issues are perfectly taken care of by the investigator(s). This review is not an exception to that and so does not cover clinical aspects {however, seldom comments are made only if those issues are intimately / scientifically related & intermingle with ‘statistical aspects’ of the study}. Agreed that ‘statistical methods’ are used as just tools here, however, they are vital part of methodology [and so should be given due importance].

COMMENTS: It is (being KAP type cross-sectional survey only) a fairly simple [and so straight forward] study as ‘The primary aim of this study was to investigate “Patient characteristics, knowledge of the COVID-19 disease, risk behaviour and illness perception in patients visiting an emergency department in the Netherlands during the COVID-19 pandemic”. However, as said in (lines 63-64) ‘Abstract-Conclusion’ that “This is the first (large) study that investigates these’ is not true. But in any case, I request the authors to consider/note following points:

It may please be noted {kindly confirm from field experts} that patients having SARS-Cov-2 antibodies are not capable to spread the disease [unless IgM result shows status of infection]. If that is so, then how correct is to combine them? with ‘Patients with a positive nasal Polymerase chain reaction (PCR) swab to SARS-Cov-2’ which are real ‘COVID-19 positive’.

Though measures/tools used as “Indicators/Measures of knowledge, risk behaviour, and illness perception of COVID-19” (lines 155-56), are appropriate, most of them yield data that are in [most likely] ‘ordinal’ level of measurement [and not in ratio level of measurement for sure {as the score two times higher does not indicate presence of that parameter/phenomenon as double}]. Then application of suitable non-parametric test(s) is/are indicated/advisable [even if distribution may be ‘Gaussian’ (i.e. normal) in these (such) cases. Therefore, as said in lines 157-8 that ‘differences in terms of these factors were compared between 3 groups (those tested positive for SARS-Cov-2, those tested negative, and the control group) using the One-Way ANOVA test’ is not correct and it is indicated/advisable to use non-parametric ‘One-Way ANOVA’ namely Kruskal-Wallis test.

Please read the following [from famous text book]:

“Inferential statistics (i.e. hypothesis testing + estimation of CI) is built on the population model (i.e. the underlying assumption is that there is a population and we are dealing with random sample(s) drawn from that population). Although in clinical trial (involving at least two groups) we do not really deal with random samples, ‘allocation’ to treatment groups is ‘randomly’ done which enable us to evoke the population model and we can use inferential statistics safely. But when there is only one group or in studies even with two/more groups ‘random allocation’ is out-of- question [like internal grouping as in this case] and with ‘non-random’ selection, it may be questionable to use inferential statistics [even if you have two measurement sets as ‘pre-post’].

By this I do not advice “not to use inferential statistics here”, but just to keep this limitation in mind while interpreting results as there is no guarantee of representation of population {example, line 336: The lower average age in this study compared to the SARS-Cov-2-infected populations reported in other studies}.

Test used to analyse data displayed in Table 2 [Group comparison for non-pharmaceutical interventions (NPIs) and SARS-Cov-2 infection in the positive-tested, negative-tested, and control groups] is not mentioned anywhere and so the question is ‘how ANOVA is applied as most data are categorical’ but if Chi-square is used then ‘how zero frequency (rather all low frequencies are/) is dealt with’ [remember that this a scientific/academic document and so all details should be clearly communicated].

Implications of this study [in backdrop of ‘Added value of this study’ described in lines 396-40] are questionable, in my opinion {though it is true (line 71-72) that ‘Knowledge about the coping of the population during the COVID-19 pandemic is very important, certainly also in the perspective of a possible second outbreak of COVID-19’}. Few things/findings are ‘very obvious’ [ex. Line 186-7: ‘Significantly more patients infected with SARS-Cov-2 work in a vital profession compared to uninfected patients and the control group (p-value 0.04), and most of them work in the medical sector’].

Reviewer #2: This is an ambitious case- control study of patient characteristics, knowledge of the COVID-19 disease, risk behaviour and mental state in patients visiting an emergency room with COVID-19 symptoms and controls in the Netherlands. I admire the intent and work to perform this work, but unfortunately the study population, questionnaire with responses, and analyses require clarification. The study population as it is described decreases the study generalizability. Measuring behaviour by self report in patients with COVID-19 symptoms compared to those without COVID-19 symptoms might be too confounding to say anything about behaviour. Use of the anxiety measure without reference or definition of the meaning of the scoring system decreases its utility. Use of a questionnaire without validation or precision is worrisome. (For example when asked about staying home is that staying home aside from work or inclusive, is it in general (which is what I thought initially) or with symptoms or post exposure (which is what the questionnaire seems to imply ? Analysis of the questionnaire results with binary outcomes when they were measured on a 5 point likert scale is puzzling and very much decreases belief or precision in the results. For example do the essential worker patients, such as those who work in a nursing home really keep a 1.5m distance if they are working with patients? Is going to a park for excersie or to walk the dog an exposure? But similarly the only intervention reported on a 5 point scale was handwashing which I would imagine is very hard to recall correctly.

1) Study population: Consecutive patients presenting at one ED in the Netherlands between April 10 and June 20. Because this is one ED it is important to understand the ED and patient population in order to see the extent to which this study is generalizable. 159 patients were enrolled in approximately 70 days. This is 2.5 patients a day which seems like a very low volume ED or it is a convenience enrollment. In either case, it is important to understand if there was a difference between those that enrolled and those that did not enroll in the study. It would be good to understand the chief complaints/diagnostic categories of the cases and controls as well as their disposition and illness severity. I want to know what are the parameters for testing “covid suspected.” Would it be symptomatic patients or exposed? If so, there are some constellations of symptoms that are more worrisome than others (fever alone, vs. respiratory symptoms and fever.) What was the prevalence in the netherlads at that time?

2) Comparison is really between covid suspected and controls then a subanalysis could be done with positive and negatives.

3) Since this study involves patient recall regarding behavior, it is important to use validated questions /outcome measurements regarding behavior. It is important to understand the Netherlands rules/public health injunctions at this time (Were masks required?) The authors report using a 5 point likert scale but the report their results on a 2 point scale which seems a little blunt

4) Recall bias possible regarding covid suspected and covid positive (were they feeling sicker)

5) Since this is recall, how long of a time period are they asking the patient to recall?

6) Likewise, visiting beaches, markets and parks seems vague. I do not think of beaches and parks as places with increased transmission (in the US we are allowed to go to parks and beaches and out of doors.)

7) If the authors are going to use an anxiety score they should cite it and then describe its use. I had to look it up on the internet. While the authors state that the comparison of anxiety measurements are significantly different, I do not know what this means. My source says that the STAI-s is used to make clinical diagnoses but I don’t think that is the case here. The source I saw on the internet stated that the ranges found here are both “moderate”

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Reviewer #1: No

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Submitted filename: renamed_dec77.docx

Author response to Decision Letter 0

26 Jan 2021

Dear Editor

Thank you very much for giving us the opportunity to revise our article titled: Case- control study of patient characteristics, knowledge of the COVID-19 disease, risk behaviour and mental state in patients visiting an emergency room with COVID-19 symptoms in the Netherlands”

We are very thankful for the commentary of the referees. We would like to respond point by point to the comments. For your convenience, we have written the answers in blue.

COMMENTS – Manuscript PONE-D-20-28005

Title: “Case- control study of patient characteristics, knowledge of the COVID-19 disease, risk behaviour and mental state in patients visiting an emergency room with COVID-19 symptoms in the Netherlands”

Reviewer #1.COMMENTS: It is (being KAP type cross-sectional survey only) a fairly simple [and so straight forward] study as ‘The primary aim of this study was to investigate “Patient characteristics, knowledge of the COVID-19 disease, risk behaviour and illness perception in patients visiting an emergency department in the Netherlands during the COVID-19 pandemic”. However, as said in (lines 63-64) ‘Abstract-Conclusion’ that “This is the first (large) study that investigates these’ is not true.

Thank you for this comment, we agree with you. We changed the sentence to:

‘this is one of the first (large) study that investigates …’

But in any case, I request the authors to consider/note following points:

We agree with you. However, only 3 patients were included only on the SARS-Cov-2 antibodies. All other patients were tested with COVID-19 PCR. Because, this study was performed in the beginning of the pandemic, we assume that these 3 patients had a very recent infection. We think that taking these 3 patients in to account will not influence our study results.

Thank you for this good comment. We agree with you and did the analysis again with the non-parametric One-Way ANOVA test, namely Kruskal-Wallis test. We have adjusted table 2. Fortunately, the new results of this statistical method did not change our conclusions.

Thank you very much for the book suggestion. We have read the book chapter with interest. We used indeed the ANOVA test and as you mentioned, it is better to use the Kruskal-Wallis test. We made this improvement and correct this in the statistical methods. We have also adapted table 2 and noted the statistical method below the table.

Maybe, these conclusions of our study are obvious. However, we think it is important to pay attention to this important sector and therefore, we mentioned this point in our manuscript.

Reviewer #2: This is an ambitious case- control study of patient characteristics, knowledge of the COVID-19 disease, risk behaviour and mental state in patients visiting an emergency room with COVID-19 symptoms and controls in the Netherlands. I admire the intent and work to perform this work, but unfortunately the study population, questionnaire with responses, and analyses require clarification. The study population as it is described decreases the study generalizability. Measuring behaviour by self report in patients with COVID-19 symptoms compared to those without COVID-19 symptoms might be too confounding to say anything about behaviour.

Thank you very much for this extensive comment. The questionnaires were completed before the patients get there COVID-19 PCR result, therefore, there is no confounding in the questionnaire outcomes.

Use of the anxiety measure without reference or definition of the meaning of the scoring system decreases its utility.

We agree with you and added the reference to the manuscript: Marteau TM, Bekker H. The development of a six-item short-form of the state scale of the Spielberger State-Trait Anxiety Inventory (STAI). Br J Clin Psychol. 1992;31(3):301-6.

A cut off point of 39–40 has been suggested to detect clinically significant anxiety symptoms and we clarified this in the manuscript.

Use of a questionnaire without validation or precision is worrisome. (For example when asked about staying home is that staying home aside from work or inclusive, is it in general (which is what I thought initially) or with symptoms or post exposure (which is what the questionnaire seems to imply ? Analysis of the questionnaire results with binary outcomes when they were measured on a 5 point likert scale is puzzling and very much decreases belief or precision in the results. For example do the essential worker patients, such as those who work in a nursing home really keep a 1.5m distance if they are working with patients? Is going to a park for excersie or to walk the dog an exposure? But similarly the only intervention reported on a 5 point scale was handwashing which I would imagine is very hard to recall correctly.

That is a very good comment. At the start of the study we were looking for validated questionnaires about behaviour during infection outbreaks. Unfortunately, validated questionaries don’t exist on this topic. And it is true that these questionnaires have a recall bias. However, the time between the start of the pandemic and completing the interview is only 3.5 month.

Study population: Consecutive patients presenting at one ED in the Netherlands between April 10 and June 20. Because this is one ED it is important to understand the ED and patient population in order to see the extent to which this study is generalizable. 159 patients were enrolled in approximately 70 days. This is 2.5 patients a day which seems like a very low volume ED or it is a convenience enrollment. In either case, it is important to understand if there was a difference between those that enrolled and those that did not enroll in the study. It would be good to understand the chief complaints/diagnostic categories of the cases and controls as well as their disposition and illness severity. I want to know what are the parameters for testing “covid suspected.” Would it be symptomatic patients or exposed?

All patients with upper- or lower respiratory symptoms were considered as possible COVID-positive and were tested with PCR. We added the following sentence to the manuscript:

All patients with upper- or lower respiratory symptoms were considered as possible COVID-19 positive.

If so, there are some constellations of symptoms that are more worrisome than others (fever alone, vs. respiratory symptoms and fever.) What was the prevalence in the netherlads at that time?

The prevalence of COVID-19 suspected patients in our emergency room was among 7 patients a day. There is indeed a selection bias, because the seriously ill patients who were respiratory insufficient, patients with a language barrier, and patients who were not able to handle an iPad were excluded from this study. Unfortunately, that was inevitable. We did mention this in the manuscript.

We have chosen to compare the positive, negative and not suspected COVID-19 positive patients to get a more complete vision of the metal state and behaviour of all patients visiting the emergency room. However, it is possible to get the comparison between the positive and negative patients from the tables.

We choose to report not all details to make it easy for the reader. We think is a more organized and less extensive table. However, it is indeed also possible to give the total overview of all numbers,

That is a good point. That maybe the case. Hoverer, we have not scored the degree of illness in this study.

The recall was maximal 3.5 month.

In the Netherlands it is very busy on the beaches and parks. Therefore, these places are considered as places with a high risk of infection.

We agree with you. We added a reference to the manuscript.

The mean anxiety score was 48.56 points (range 23-67) in the negative-tested group and 50.10 points (range 27-77) in the positive-tested group. The the anxiety score of the control group (mean 39.00, range 20-70). As we mentioned in the manuscript a cut off point of 39–40 has been suggested to detect clinically significant anxiety symptoms. We have clarified this in the text.

We hope we have answered all questions and really hope you will accept our improved manuscript in Plos One. I would like to ask you to take into consideration that it will be very difficult for us to get our article published in another journal after a 4.5 month waiting period for review at Plos one.

Looking forward to hear from you.

Hanna van der Valk

Submitted filename: Letter_reviewer.docx

Decision Letter 1

PONE-D-20-28005R1

Please submit your revised manuscript by Apr 17 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at gro.solp@enosolp . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Reviewer #1: (No Response)

Reviewer #2: (No Response)

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Partly

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

Reviewer #2: I Don't Know

4. Have the authors made all data underlying the findings in their manuscript fully available?

5. Is the manuscript presented in an intelligible fashion and written in standard English?

6. Review Comments to the Author

Reviewer #1: COMMENTS: Since most of the comments made on earlier draft by me (and hopefully by other respected reviewers also) are attended positively/adequately, I am fully satisfied and the manuscript is improved a lot.

While answering my comment, it is said that “Fortunately, the new results of this statistical method did not change our conclusions” is very good but remember that it does not indicate that any will do. Methodology used should be appropriate [always use which is indicated / most desired].

7. PLOS authors have the option to publish the peer review history of their article ( what does this mean? ). If published, this will include your full peer review and any attached files.

Reviewer #1:  Yes:  Dr. Sanjeev Sarmukaddam

Author response to Decision Letter 1

We would like to respond to the comment of the referee.

1. "While answering my comment, it is said that “Fortunately, the new results of this statistical method did not change our conclusions” is very good but remember that it does not indicate that any will do. Methodology used should be appropriate [always use which is indicated / most desired."

I fully agree with you. I am very pleased that you pointed this out to me, and indeed the correct methodology is very important. We want to apologize for the word choice we made.

Submitted filename: Letter_reviewer2.docx

Decision Letter 2

15 Mar 2021

PONE-D-20-28005R2

Please submit your revised manuscript by Apr 29 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at gro.solp@enosolp . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Reviewer #1: COMMENTS: As already said, it being a KAP type cross-sectional survey only [is fairly simple and so straight forward], there is hardly anything to comment, mention/point-out critical observation(s) or suggest few things for further improvement.

However, I just felt that the fact ‘this study also includes comparison between three groups [Negative-tested, Positive-tested, Control] is not adequately mentioned [except line 64 of ‘Abstract-Conclusion’ that “This is one of the first (large) study that investigates and compares patient characteristics”]

Author response to Decision Letter 2

19 Mar 2021

Reviewer #1: COMMENTS: As already said, it being a KAP type cross-sectional survey only [is fairly simple and so straight forward], there is hardly anything to comment, mention/point-out critical observation(s) or suggest few things for further improvement.

We agree with you. As you suggest, we mentioned now more adequately in our manuscript the fact that this study describes the variables in patients visiting an emergency department in the Netherlands during the COVID-19 pandemic and that we also made a comparison between the “COVID-19 suspected” (positive and negative tested group) with the “COVID-19 not suspected” (control group) and in the “COVID-19 suspected” group, the positive and negative tested patients.

We added the following sentences to the manuscript:

Abstract (line 46-49)

The primary aim of this study was to investigate these variables in patients visiting an emergency department in the Netherlands during the COVID-19 pandemic and to compare the “COVID-19 suspected” (positive and negative tested group) with the “COVID-19 not suspected” (control group) and to compare in the “COVID-19 suspected” group, the positive and negative tested patients.

Material and methods (line 160-162)

We clarified this also in the discussion (line 314-317)

The “COVID-19 suspected” (positive and negative tested group) was compared with the “COVID-19 not suspected” (control group) and in the “COVID-19 suspected” group, the positive and negative tested patients were compared.

We really hope -by addressing you comment- that we improved the message of the manuscript. We are looking forward to hear from you.

Submitted filename: Letter_reviewer3.docx

Decision Letter 3

26 Mar 2021

PONE-D-20-28005R3

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Additional Editor Comments (optional):

Reviewer #1: COMMENTS: As already said, it being a KAP type cross-sectional survey is fairly simple and straight forward, therefore there is nothing much to comment as it describes factual information. I think if this info be useful [if at all] for clinicians involved in treating COVID patients, then we should not delay its publication.

Hope, you already have taken note of the fact {which was highlighted on very first occasion by including ‘important note’} that “This review pertains only to ‘statistical aspects’ of the study and so ‘clinical aspects’ [like medical importance, relevance of the study, ‘clinical significance and implication(s)’ of the whole study, etc.] are to be evaluated [should be assessed] separately/independently”.

Acceptance letter

Dear Dr. van der Valk:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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on behalf of

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