Journal of the American Heart Association · 2026
Role of Social Determinants of Health in Risk Prediction Models for ST-Segment-Elevation Myocardial Infarction Death: A Registry-Based Study.
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Pliakos Elina E, Shultz Kaitlyn, Reddy Kriyana P, Eberly Lauren A, Khatana Sameed A M, Fanaroff Alexander C, Groeneveld Peter W, Giri Jay, Nathan Ashwin S
Аннотация
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.
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.