Publication Details

AFRICAN RESEARCH NEXUS

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medicine

Severity Scores in COVID-19 Pneumonia: a Multicenter, Retrospective, Cohort Study

Journal of General Internal Medicine, Volume 36, No. 5, Year 2021

Background: Identification of patients on admission to hospital with coronavirus infectious disease 2019 (COVID-19) pneumonia who can develop poor outcomes has not yet been comprehensively assessed. Objective: To compare severity scores used for community-acquired pneumonia to identify high-risk patients with COVID-19 pneumonia. Design: PSI, CURB-65, qSOFA, and MuLBSTA, a new score for viral pneumonia, were calculated on admission to hospital to identify high-risk patients for in-hospital mortality, admission to an intensive care unit (ICU), or use of mechanical ventilation. Area under receiver operating characteristics curve (AUROC), sensitivity, and specificity for each score were determined and AUROC was compared among them. Participants: Patients with COVID-19 pneumonia included in the SEMI-COVID-19 Network. Key results: We examined 10,238 patients with COVID-19. Mean age of patients was 66.6 years and 57.9% were males. The most common comorbidities were as follows: hypertension (49.2%), diabetes (18.8%), and chronic obstructive pulmonary disease (12.8%). Acute respiratory distress syndrome (34.7%) and acute kidney injury (13.9%) were the most common complications. In-hospital mortality was 20.9%. PSI and CURB-65 showed the highest AUROC (0.835 and 0.825, respectively). qSOFA and MuLBSTA had a lower AUROC (0.728 and 0.715, respectively). qSOFA was the most specific score (specificity 95.7%) albeit its sensitivity was only 26.2%. PSI had the highest sensitivity (84.1%) and a specificity of 72.2%. Conclusions: PSI and CURB-65, specific severity scores for pneumonia, were better than qSOFA and MuLBSTA at predicting mortality in patients with COVID-19 pneumonia. Additionally, qSOFA, the simplest score to perform, was the most specific albeit the least sensitive. © 2021, Society of General Internal Medicine.
Statistics
Citations: 32
Authors: 5
Affiliations: 16
Identifiers
Research Areas
Covid
Health System And Policy
Noncommunicable Diseases
Violence And Injury
Study Design
Cohort Study
Study Approach
Quantitative