Objectives The development of a prognostic mortality risk model for hospitalized COVID-19 patients may facilitate patient treatment planning, comparisons of therapeutic strategies, and public health preparations. Methods We retrospectively reviewed the electronic health records of patients hospitalized within a 13-hospital New Jersey USA network between March 1, 2020 and April 22, 2020 with positive polymerase chain reaction results for SARS-CoV-2, with follow-up through May 29, 2020. With death or hospital discharge by day 40 as the primary endpoint, we used univariate followed by stepwise multivariate proportional hazard models to develop a risk score on one-half the data set, validated on the remainder, and converted the risk score into a patient-level predictive probability of 40-day mortality based on the combined dataset. Results The study population consisted of 3123 hospitalized COVID-19 patients; median age 63 years; 60% were men; 42% had >3 coexisting conditions. 713 (23%) patients died within 40 days of hospitalization for COVID-19. From 22 potential candidate factors 6 were found to be independent predictors of mortality and were included in the risk score model: age, respiratory rate ≥25/minute upon hospital presentation, oxygenation <94% on hospital presentation, and pre-hospital comorbidities of hypertension, coronary artery disease, or chronic renal disease. The risk score was highly prognostic of mortality in a training set and confirmatory set yielding in the combined dataset a hazard ratio of 1.80 (95% CI, 1.72, 1.87) for one unit increases. Using observed mortality within 20 equally sized bins of risk scores, a predictive model for an individual’s 40-day risk of mortality was generated as -14.258 + 13.460*RS + 1.585*(RS–2.524)^2–0.403*(RS–2.524)^3. An online calculator of this 40-day COVID-19 mortality risk score is available at www.HackensackMeridianHealth.org/CovidRS . Conclusions A risk score using six variables is able to prognosticate mortality within 40-days of hospitalization for COVID-19. Trial registration Clinicaltrials.gov Identifier: NCT04347993 .
【초록키워드】 COVID-19, public health, SARS-CoV-2, Mortality, Hospitalization, hospital, Comorbidity, risk, hypertension, Electronic health record, Coronary artery disease, Probability, comparison, Therapeutic strategies, death, age, dataset, Follow-up, prognostic, USA, hospitalized COVID-19 patient, COVID-19 mortality, respiratory rate, Oxygenation, Predictive, Risk scores, Factor, 95% CI, study population, hazard ratio, Increases, median age, hospital discharge, chronic renal disease, positive, hospitalized COVID-19, variable, patient treatment, objective, polymerase chain, Result, develop, facilitate, conditions, New, calculator, independent predictor, mortality risk model, patients died, patients hospitalized, the primary endpoint, yielding, 【제목키워드】 prognostic, development, hospitalized patient, mortality risk model, with COVID-19,