Working Paper Article Version 1 This version is not peer-reviewed

Distribution of Symptoms, Comorbidities, and Severity Among Patients with COVID-19 by Age Groups, Countries, and Stages of Outbreak: A Systematic Review and Meta-Analysis

Version 1 : Received: 14 January 2021 / Approved: 15 January 2021 / Online: 15 January 2021 (12:44:59 CET)

How to cite: Chen, K.; Yunusa, I.; Liu, S.; Wu, C.; Yeh, C.; Han, S.; Mao, C.; Harika, D.; Rothman, R.; Pekosz, A. Distribution of Symptoms, Comorbidities, and Severity Among Patients with COVID-19 by Age Groups, Countries, and Stages of Outbreak: A Systematic Review and Meta-Analysis. Preprints 2021, 2021010290 Chen, K.; Yunusa, I.; Liu, S.; Wu, C.; Yeh, C.; Han, S.; Mao, C.; Harika, D.; Rothman, R.; Pekosz, A. Distribution of Symptoms, Comorbidities, and Severity Among Patients with COVID-19 by Age Groups, Countries, and Stages of Outbreak: A Systematic Review and Meta-Analysis. Preprints 2021, 2021010290

Abstract

Study objective Since December 2019, the coronavirus disease (COVID-19) pandemic has caused over a million deaths and resulted in adverse socio-economic impacts worldwide. However, predictability and prognostication of clinical features vary among different populations. Methods We search PubMed, EMBASE, Cochrane Library, Google Scholar, and WHO Global Health Library from December 2019 to April 2020 for studies reporting the risk factors, clinical features, and outcomes. The random-effect models for transformed prevalence (single-arm) or bivariate random-effect models (sensitivity and specificity) for correlated performance indicators. Results Among the 189 included studies representing 53,659 patients, the most sensitive predictor for COVID-19 infection was fever in adults (83%, 95% confidence interval [CI]:73–90%), and the most specific predictor was fatigue (96%, 95% CI: 80–99%). Fever was the most sensitive symptom in predicting the severity (89%, 95% CI:83–92%), followed by cough (71%, 95% CI:63–78%). The most specific predictor of severe COVID-19 was a chronic obstructive pulmonary disease (99%, 95% CI:98–99%). The stage of the outbreak and age significantly affect the prevalence of fever, fatigue, cough, and dyspnea. Fever, cough, fatigue, hypertension, and diabetes mellitus combined have a 3.06 positive likelihood ratio (PLR) and a 0.59 negative likelihood ratio (NLR) in the diagnosis. Additionally, fever, cough, sputum production, myalgia, fatigue, and dyspnea combined have a 10.44 PLR and a 0.16 NLR in predicting severe COVID-19. Conclusions Understanding the different distribution of predictors essential for screening potential COVID-19 infection and severe outcomes and the combination of symptoms could improve the pre-test probability.

Keywords

COVID-19; sensitivity; specificity; diagnosis; prognosis

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.