Abstract
Although models have been developed for predicting severity of COVID-19 based on the medical history of patients, simplified risk prediction models with good accuracy could be more practical. In this study, we examined utility of simpler models for estimating risk of hospitalization of patients with COVID-19 and mortality of these patients based on demographic characteristics (sex, age, race, median household income based on zip code) and smoking status of 12,347 patients who tested positive at Mass General Brigham centers. The corresponding electronic health records were queried from 02/26/2020 to 07/14/2020 to construct derivation and validation cohorts. The derivation cohort was used to fit a generalized linear model for estimating risk of hospitalization within 30 days of COVID-19 diagnosis and mortality within approximately 3 months for the hospitalized patients. On the validation cohort, the model resulted in c-statistics of 0.77 [95% CI: 0.73-0.80] for hospitalization outcome, and 0.72 [95% CI: 0.69-0.74] for mortality among hospitalized patients. Higher risk was associated with older age, male sex, black ethnicity, lower socioeconomic status, and current/past smoking status. The model can be applied to predict risk of hospitalization and mortality, and could aid decision making when detailed medical history of patients is not easily available.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
This work was supported in part by the National Heart Lung and Blood Institute (T32 HL007575 to H.D., K24 HL136852 to S.M., and 5K01HL135342 to O.D.), by 17IGMV33860009 from the American Heart Association to O.D., by the BWH Lerner Junior Faculty Research Award to O.D., and by philanthropic support from the Brigham and Women's Hospital COVID fund.
Author Declarations
I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
Yes
The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
All data were obtained from Electronic Health Records Repository maintained by Mass General Brigham (MGB) HealthCare Systems in full compliance with the Institutional Review Board protocols and met all data access requirements. The Partners Healthcare System Institutional Review Board approved the study.
All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.
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Data Availability
The datasets analyzed during the current study are not publicly available. Due to patient privacy concerns, the underlying EHR data are not redistributable to researchers other than those prespecified in the approved Institutional Review Board application.