Which criteria were used to describe patients with COVID-19? A systematic review and meta analysis of clinical, laboratory, and imaging features

Background: The unknowingness of COVID-19 compared to other respiratory diseases and gaining an overview of its diagnostic criteria led to this study, which was designed to summarize the signs and symptoms along with the clinical tests that described these patients. Methods: PubMed/MEDLINE, Web of Science, Core Collection, Scopus, and Google Scholar were systematically searched on September 27, 2020. After screening, we selected 56 articles based on clinical characteristics and laboratory and imaging findings in confirmed COVID-19 patients as eligibility criteria. To evaluate risk of bias, the Newcastle Ottawa scale, for publication bias, Egger’s test, and for heterogeneity, I2 and tau test were used; and finally, random-effects models were used for pooled estimation. Results: Pooled estimates for frequently clinical symptoms were as follows: fever (78% [95% CI, 74-82]), cough (60% [95% CI, 57- 63]), and fatigue (31% [95% CI, 26-36]); and they were as follows for laboratory findings in lymphocyte (1.02 [95% CI, 0.92-1.12]), CRP (19.64 [95% CI, 13.96- 25.32]), and platelet count (175.2 [95% CI, 165.2-185.2]); they were as follows for imaging findings in bilateral pneumonia (64% [95% CI, 56-72]), and ground glass opacity (60% [95% CI, 48-7]). Also, in the subgroup analysis, bilateral pneumonia with 18% and fatigue with 15%, had the highest difference in values between the groups. Conclusion: According to Forest plots, the CI and dispersion among studies were smaller in laboratory findings than in symptom and imaging findings, which might indicate a high alignment in the laboratory findings among studies.