SARS2: Simplified scores to estimate risk of hospitalization and death among patients with COVID-19
The capability of predicting severity of COVID-19 illness in a fast and efficient manner would help healthcare workers to distinguish high risk patients. We utilized MGB EHR data of patients with COVID-19 to design simplified models for predicting hospitalization risk and also risk of mortality among hospitalized patients, where the model requires only demographic variables (age, sex, race, median household income) and smoking status of the 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. The model is named SARS2 (Sex, Age, Race, Socioeconomic, Smoking status), and is available online (https://dashti.bwh.harvard.edu/sars2/).
Aspirin-Guide (App)
This free mobile app and online tool for shared decision making regarding aspirin use for primary prevention. App developers are Samia Mora, MD, MHS, JoAnn E. Manson, MD, DrPH, and Jeffrey M. Ames, BS, MEng. The medical software website imedicalapps.com gave it a perfect score and called it “truly a contender for medical app of the year [2016]”. SteadyHealth described it as “an app that every primary care provider or anyone who prescribes aspirin to patients for primary prevention of cardiovascular disease should have. It’s simple, but effective tool that makes difficult and complicated decisions much easier.” The app was released in June 2016 and has received >20,000 downloads world-wide in the first two years.
Available at
http://www.aspiringuide.com.
https://appsto.re/us/emRMcb.i