For this project, I led the data pipeline from cohort assembly through statistical analysis. I extracted and cleaned EHR data, constructed the analytic dataset, and conducted logistic regression to identify predictors of GDMT use and optimal dosing. I addressed challenges like missing data and multicollinearity and presented results across seven medication classes. I also contributed to interpreting the findings and co-writing the manuscript.
Most HFrEF patients received at least one GDMT class, but fewer than half reached target doses. Use of newer therapies and vasodilators (for Black patients) was low. Older age and comorbidities predicted lower use, while higher BMI, Black race, and cardiac devices were linked to greater use.
There are major gaps in GDMT use and dosing in real-world care, especially among older and medically complex patients. Tailored strategies are needed to improve equitable, guideline-aligned treatment.
Read more about the study: "Guideline-directed medical therapy rates in heart failure patients with reduced ejection fraction in a diverse cohort"