Abstract

Introduction: It is well-documented that COVID-19 patients with pre-existing cardiovascular-related disorders are at higher risk of a complicated course. It would be valuable to integrate individual risk factors into overall risk scores for hospitalization and death from COVID-19. Methods: The Intermountain Healthcare medical record database was searched for all individuals tested for SARS-CoV-2 infection up to June 8, 2020. Data from test-positive patients (pts) was analyzed to determine the characteristics of pts requiring hospitalization. From these data, 2 risk scores for hospitalization were derived using multi-variable modeling: of only demographic and risk-factor data, or also including concurrent medications. The risk scores were also applied to predict the risk of dying from COVID-19. Results: Of 104,018 people tested at Intermountain Healthcare for SARS-CoV-2, 5505 (5.3%) were positive. Of test-positive pts, 451 (8.2%) were hospitalized, and 37 (0.7%) died. Using a demographic/risk factor only score, 1.4, 7.0, and 36.6% of low-, moderate-, and high-risk groups, respectively, were hospitalized (AUC=0.826). Using demographic risk-factors and medications, 1.4, 5.6, and 40.3% of low-, moderate-, and high-risk patients were hospitalized (AUC=0.854, Table 1). The demographic/risk factor-score was also predictive of the risk of dying, with 0%, 0.9% and 4.5% in low-, moderate-, and high-risk groups dying (AUC=0.918). Adding medications to the risk-factors model further improved the prediction of death with 0.1, 0.04, and 4.9% in the low-, moderate-, and high-risk groups dying (AUC=0.942, Table 2). Conclusions: We demonstrate the derivation of highly predictive risk scores for COVD-19 patients at low, moderate, and high risks of hospitalization or death. Pending appropriate validation in another cohort, application of these risk-scores may allow healthcare systems to risk-stratify COVID-19 patients requiring variable intensity of care.

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