Korean Journal of Clinical Pharmacy (한국임상약학회지)

Korean College Of Clinical Pharmacy (한국임상약학회)
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Predictors of Mortality in Patients with COVID-19: A Systematic Review and Meta-analysis

코로나바이러스감염증-19 (COVID-19) 환자들의 사망관련 인자에 대한 연구: 체계적 문헌고찰 및 메타분석

  • Kim, Woorim (College of Pharmacy, Chungbuk National University) ;
  • Han, Ji Min (College of Pharmacy, Chungbuk National University) ;
  • Lee, Kyung Eun (College of Pharmacy, Chungbuk National University)
  • Received : 2020.08.12
  • Accepted : 2020.09.03
  • Published : 2020.09.30
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Abstract

Background: Most meta-analyses of risk factors for severe or critical outcomes in patients with COVID-19 only included studies conducted in China and this causes difficulties in generalization. Therefore, this study aimed to systematically evaluate the risk factors in patients with COVID-19 from various countries. Methods: PubMed, Embase, and Web of Science were searched for studies published on the mortality risk in patients with COVID-19 from January 1 to May 7, 2020. Pooled estimates were calculated as odds ratio (OR) with 95% confidence interval (CI) using the random-effects model. Results: We analyzed data from seven studies involving 26,542 patients in total in this systematic review and meta-analysis. Among the patients, 2,337 deaths were recorded (8.8%). Elderly patients and males showed significantly higher mortality rates than young patients and females; the OR values were 3.6 (95% CI 2.5-5.1) and 1.2 (95% CI 1.0-1.3), respectively. Among comorbidities, hypertension (OR 2.3, 95% CI 1.1-4.6), diabetes (OR 2.2, 95% CI 1.2-3.9), cardiovascular disease (OR 3.1, 95% CI 1.5-6.3), chronic obstructive pulmonary disease (OR 4.4, 95% CI 1.7-11.5), and chronic kidney disease (OR 4.2, 95% CI 2.0-8.6) were significantly associated with increased mortalities. Conclusion: This meta-analysis, involving a huge global sample, employed a systematic method for synthesizing quantitative results of studies on the risk factors for mortality in patients with COVID-19. It is helpful for clinicians to identify patients with poor prognosis and improve the allocation of health resources to patients who need them most.

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