Evidence map›Paper›PMID 33397292›Full record

SynthesisBMC medical research methodology2021

COVID-19-related medical research: a meta-research and critical appraisal.

Marc Raynaud, Huanxi Zhang, Kevin Louis, Valentin Goutaudier, Jiali Wang, Quentin Dubourg, Yongcheng Wei, Zeynep Demir, Charlotte Debiais, Olivier Aubert and 9 more

Abstract readSystematic Review
In one paragraph

Synthesis in BMC medical research methodology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 11 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 11 syntheses or guidelines pooled it.

  1. Pooled it
  2. The impact of COVID-19 on the mental health workforce: A rapid review.International journal of mental health nursing · 2023
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  5. Randomized controlled trials in patients with COVID-19: a systematic review and critical appraisal.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
    Pooled it
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  12. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Marc RaynaudParis Translational Research Epidemiology and Biostatistics Department, Hôpital Necker, 149 rue de Sèvres, 75015, Paris, France.
Huanxi ZhangThe First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Kevin LouisParis Translational Research Epidemiology and Biostatistics Department, Hôpital Necker, 149 rue de Sèvres, 75015, Paris, France.
Valentin GoutaudierParis Translational Research Epidemiology and Biostatistics Department, Hôpital Necker, 149 rue de Sèvres, 75015, Paris, France.
Jiali WangThe First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Quentin DubourgPitié-Salpêtrière University Hospital, Assistance Publique-Hôpitaux de Paris, Sorbonne University, Paris, France.
Yongcheng WeiThe First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Zeynep DemirParis Translational Research Epidemiology and Biostatistics Department, Hôpital Necker, 149 rue de Sèvres, 75015, Paris, France.
Charlotte DebiaisParis Translational Research Epidemiology and Biostatistics Department, Hôpital Necker, 149 rue de Sèvres, 75015, Paris, France.
Olivier AubertParis Translational Research Epidemiology and Biostatistics Department, Hôpital Necker, 149 rue de Sèvres, 75015, Paris, France.
Yassine BouatouParis Translational Research Epidemiology and Biostatistics Department, Hôpital Necker, 149 rue de Sèvres, 75015, Paris, France.
Carmen LefaucheurImmunology and Nephrology Department, Saint Louis Hospital, Paris, France.
Patricia JabreCochrane Pre-hospital and Emergency Care, Necker University Hospital, Paris, France.
Longshan LiuThe First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Changxi WangThe First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Xavier JouvenParis Translational Research Epidemiology and Biostatistics Department, Hôpital Necker, 149 rue de Sèvres, 75015, Paris, France.
Peter ReeseParis Translational Research Epidemiology and Biostatistics Department, Hôpital Necker, 149 rue de Sèvres, 75015, Paris, France.
Jean-Philippe EmpanaParis Translational Research Epidemiology and Biostatistics Department, Hôpital Necker, 149 rue de Sèvres, 75015, Paris, France.
Alexandre LoupyParis Translational Research Epidemiology and Biostatistics Department, Hôpital Necker, 149 rue de Sèvres, 75015, Paris, France. alexandre.loupy@inserm.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSince the start of the COVID-19 outbreak, a large number of COVID-19-related papers have been published. However, concerns about the risk of expedited science have been raised. We aimed at reviewing and categorizing COVID-19-related medical research and to critically appraise peer-reviewed original articles.

methodsThe data sources were Pubmed, Cochrane COVID-19 register study, arXiv, medRxiv and bioRxiv, from 01/11/2019 to 01/05/2020. Peer-reviewed and preprints publications related to COVID-19 were included, written in English or Chinese. No limitations were placed on study design. Reviewers screened and categorized studies according to i) publication type, ii) country of publication, and iii) topics covered. Original articles were critically appraised using validated quality assessment tools.

resultsAmong the 11,452 publications identified, 10,516 met the inclusion criteria, among which 7468 (71.0%) were peer-reviewed articles. Among these, 4190 publications (56.1%) did not include any data or analytics (comprising expert opinion pieces). Overall, the most represented topics were infectious disease (n = 2326, 22.1%), epidemiology (n = 1802, 17.1%), and global health (n = 1602, 15.2%). The top five publishing countries were China (25.8%), United States (22.3%), United Kingdom (8.8%), Italy (8.1%) and India (3.4%). The dynamic of publication showed that the exponential growth of COVID-19 peer-reviewed articles was mainly driven by publications without original data (mean 261.5 articles ± 51.1 per week) as compared with original articles (mean of 69.3 ± 22.3 articles per week). Original articles including patient data accounted for 713 (9.5%) of peer-reviewed studies. A total of 576 original articles (80.8%) showed intermediate to high risk of bias. Last, except for simulation studies that mainly used large-scale open data, the median number of patients enrolled was of 102 (IQR = 37-337).

conclusionsSince the beginning of the COVID-19 pandemic, the majority of research is composed by publications without original data. Peer-reviewed original articles with data showed a high risk of bias and included a limited number of patients. Together, these findings underscore the urgent need to strike a balance between the velocity and quality of research, and to cautiously consider medical information and clinical applicability in a pressing, pandemic context. SYSTEMATIC REVIEW REGISTRATION: https://osf.io/5zjyx/.

Indexed as

PandemicsBiomedical ResearchChinaCOVID-19HumansIndiaItalySARS-CoV-2United KingdomUnited StatesCOVID-19Critical appraisalQuality of researchSystematic review

Identifiers

PMID33397292
PMCPMC7780085

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.