Abstract
Background
Social determinants of health (SDOH) are increasingly recognized as contributors to disparities in cardiovascular outcomes. However, their incremental value in risk prediction models for ST‐segment–elevation myocardial infarction (STEMI) death remains uncertain.
Methods
We analyzed hospital admissions for STEMI between 2018 and 2020 using the American Heart Association's GWTG‐CAD (Get With The Guidelines–Coronary Artery Disease) registry. Logistic regression models were constructed: a clinical model including demographic, clinical, and medical history variables, and a full SDOH model that additionally incorporated zip code–level SDOH (college graduation, high school graduation, per‐capita income, poverty, foreign‐born status, and median household income). Discrimination was assessed using the concordance statistic/area under the receiver operating characteristic curve, and incremental value was evaluated with DeLong's test. Missing data were addressed with multiple imputation by chained equations.
Results
The imputed cohort included 749 410 STEMI admissions (median age, 62 years, 72% men). Both the clinical and SDOH models demonstrated excellent discrimination (concordance statistic, 0.95; area under the receiver operating characteristic curve, 0.85), with no meaningful difference in overall predictive performance. In exploratory analyses, the addition of high school graduation, college graduation, per‐capita income, poverty, and foreign‐born status each had a modest statistical improvement in model discrimination, whereas median household income did not.
Conclusions
Incorporating SDOH variables into an already high‐performing clinical risk model for in‐hospital STEMI death did not meaningfully enhance prediction. These findings indicate that short‐term, in‐hospital survival is primarily driven by immediate clinical factors rather than upstream socioenvironmental risks.