SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19.

Although models have been developed for predicting severity of COVID-19 from the medical history of patients, simplified 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 records were queried (02/26-07/14/2020) to construct derivation and validation cohorts. The derivation cohort was used to fit generalized linear models for estimating risk of hospitalization within 30 days of COVID-19 diagnosis and mortality within approximately 3 months for the hospitalized patients. In the validation cohort, the model resulted in c-statistics of 0.77 [95% CI 0.73-0.80] for hospitalization, and 0.84 [95% CI 0.74-0.94] 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 models can be applied to predict the absolute risks of hospitalization and mortality, and could aid in individualizing the decision making when detailed medical history of patients is not readily available.

SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19.

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.

Clinical Characteristics and Severity of COVID-19 Disease in Patients from Boston Area Hospitals.

We summarize key demographic, clinical, and medical characteristics of patients with respect to the severity of COVID-19 disease using Electronic Health Records Data of 4,140 SARS-CoV-2 positive subjects from several large Boston Area Hospitals. We found that prior use of antihypertensive medications as well as lipid lowering and other cardiovascular drugs (such as direct oral anticoagulants and antiplatelets) all track with increased severity of COVID-19 and should be further investigated with appropriate adjustment for confounders such as age and frailty. The three most common prior comorbidities are hyperlipidemia, hypertension, and prior pneumonia, all associated with increased severity.