MedRxiv 2020.11.11

Following news that the Pfizer and BioNTech COVID-19 vaccine achieved “more than 90%” efficacy in an interim analysis, the world is starting to focus on the limited initial supplies of COVID vaccines. A new medRxiv preprint looks at over 500,000 Medicare beneficiaries to identify individuals at highest risk of COVID-19 death, which could help guide the necessary vaccine rationing.

MedPage Today Editor-in-Chief and preprint co-author Marty Makary, MD, MPH, of Johns Hopkins University in Baltimore, speaks with Harlan Krumholz, MD, of Yale University, about the new data as well as the importance of sharing information like this in real-time via preprints during a pandemic.

Medicare claims data was used to identify patients age 65 years or older with diagnosis of COVID-19 between April 1, 2020 and August 31, 2020. Demographic characteristics, chronic medical conditions, and other patient risk factors that existed before the advent of COVID-19 were identified. A random forest model was used to empirically explore factors associated with COVID-19 death. The independent impact of factors identified were quantified using multivariate logistic regression with random effects.

We identified 534,023 COVID-19 patients of whom 38,066 had an inpatient death. Demographic characteristics associated with COVID-19 death included advanced age (85 years or older: aOR: 2.07; 95% CI, 1.99-2.16), male sex (aOR, 1.88; 95% CI, 1.82-1.94), and non-white race (Hispanic: aOR, 1.74; 95% CI, 1.66-1.83). Leading comorbidities associated with COVID-19 mortality included sickle cell disease (aOR, 1.73; 95% CI, 1.21-2.47), chronic kidney disease (aOR, 1.32; 95% CI, 1.29-1.36), leukemias and lymphomas (aOR, 1.22; 95% CI, 1.14-1.30), heart failure (aOR, 1.19; 95% CI, 1.16-1.22), and diabetes (aOR, 1.18; 95% CI, 1.15-1.22).

Conclusion: We created a personalized risk prediction calculator to identify candidates for early vaccine and therapeutics allocation (www.predictcovidrisk.com). These findings may be used to protect those at greatest risk of death from COVID-19.

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