Completeness of reporting for COVID-19 case reports, January to April 2020: a meta-epidemiologic study

CMAJ Open. 2021 Mar 30;9(1):E295-E301. doi: 10.9778/cmajo.20200140. Print 2021 Jan-Mar.

Abstract

Background: The quality of case reports, which are often the first reported evidence for a disease, may be negatively affected by a rush to publication early in a pandemic. We aimed to determine the completeness of reporting (COR) for case reports published on coronavirus disease 2019 (COVID-19).

Methods: We conducted a systematic search of the PubMed database for all single-patient case reports of confirmed COVID-19 published from Jan. 1 to Apr. 24, 2020. All included case reports were assessed for adherence to the CARE (Case Report) 31-item checklist, which was used to create a composite COR score. The primary outcome was the mean COR score assessed by 2 independent raters. Secondary outcomes included whether there was a change in overall COR score with certain publication factors (e.g., publication date) and whether there was a linear relation between COR and citation count and between COR scores and social media attention.

Results: Our search identified 196 studies that were published in 114 unique journals. We found that the overall mean COR score was 54.4%. No one case report included all of the 31 CARE checklist items. There was no significant correlation between COR with either citation count or social media attention.

Interpretation: We found that the overall COR for case reports on COVID-19 was poor. We suggest that journals adopt common case-reporting standards to improve reporting quality.

MeSH terms

  • Bibliography of Medicine
  • Bibliometrics
  • COVID-19 / diagnosis
  • COVID-19 / epidemiology*
  • COVID-19 / virology
  • Checklist / standards*
  • Data Management
  • Epidemiologic Studies
  • Ethics
  • Guideline Adherence
  • Humans
  • Outcome Assessment, Health Care
  • Publishing / standards*
  • Research Report / standards*
  • Research Report / trends
  • SARS-CoV-2 / genetics
  • SARS-CoV-2 / isolation & purification
  • Social Media / statistics & numerical data