External validation of a clinical risk score to predict hospital admission and in-hospital mortality in COVID-19 patients. (1st January 2021)

• Record Type: Journal Article
• Authors: Halalau, Alexandra; Imam, Zaid; Karabon, Patrick; Mankuzhy, Nikhil; Shaheen, Aciel; Tu, John; Carpenter, Christopher
• Is Part Of: Annals of medicine. Volume 53:Number 1(2021)
• Page Start: 78
• Page End: 86
• Publication Date: 2021-01-01
• Subjects: Mortality -- internal medicine -- emergency medicine -- COVID-19 -- corona virus -- triage -- hospitalization -- admission; Medicine -- Periodicals; 610
• DOI: 10.1080/07853890.2020.1828616
• Languages: English
• ISSNs: 0785-3890

Abstract

Abstract: Background: Identification of patients with novel coronavirus disease 2019 (COVID-19) requiring hospital admission or at high-risk of in-hospital mortality is essential to guide patient triage and to provide timely treatment for higher risk hospitalized patients. Methods: A retrospective multi-centre (8 hospital) cohort at Beaumont Health, Michigan, USA, reporting on COVID-19 patients diagnosed between 1 March and 1 April 2020 was used for score validation. The COVID-19 Risk of Complications Score was automatically computed by the EHR. Multivariate logistic regression models were built to predict hospital admission and in-hospital mortality using individual variables constituting the score. Validation was performed using both discrimination and calibration. Results: Compared to Green scores, Yellow Scores (OR: 5.72) and Red Scores (OR: 19.1) had significantly higher odds of admission (both p < .0001). Similarly, Yellow Scores (OR: 4.73) and Red Scores (OR: 13.3) had significantly higher odds of in-hospital mortality than Green Scores (both p < .0001). The cross-validated C-Statistics for the external validation cohort showed good discrimination for both hospital admission ( C = 0.79 (95% CI: 0.77–0.81)) and in-hospital mortality ( C = 0.75 (95% CI: 0.71–0.78)). Conclusions: The COVID-19 Risk of Complications Score predicts the need for hospital admission and in-hospital mortality patients with COVID-19. Key points: Can an electronic health record generated risk score predict the risk of hospital admission and in-hospital mortality in patients diagnosed with coronavirus disease 2019 (COVID-19)? In both validation cohorts of 2, 025 and 1, 290 COVID-19, the cross-validated C-Statistics showed good discrimination for both hospital admission (C = 0.79 (95% CI: 0.77–0.81)) and in-hospital mortality (C = 0.75 (95% CI: 0.71–0.78)), respectively. The COVID-19 Risk of Complications Score may help predict the need for hospital admission if a patient contracts SARS-CoV-2 infection and in-hospital mortality for a hospitalized patient with COVID-19.