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

Journal article

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.

Authors: Scaffidi, MA; Gimpaya, N; Li, J; Bansal, R; Verma, Y

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Joule
• Journal: CMAJ Open
• Volume: 9
• Issue: 1
• Pages: E295-E301
• Publication date: 2021-03-30
• DOI: 10.9778/cmajo.20200140
• ISSN: 2291-0026
• Language: English
• Keywords: 2019-20 coronavirus outbreak; Disease; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medicine; MEDLINE; Outbreak; Mathematics; Pandemic; Completeness (order theory); Pathology; Coronavirus disease 2019 (COVID-19); Infectious disease (medical specialty); Meta-analysis; Coronavirus; Virology; Political science