ArticleCureus2025
Understanding 30-Day Mortality After First STEMI Through DAGs: Unravelling Epidemiological Cause-Effect Links.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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10 authors.
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Abstract
BACKGROUND AND
aimTraditional statistical tests have limitations in analyzing cause-and-effect relationships. Directed acyclic graphs (DAGs) offer a structured representation of causality. This study aimed to utilize DAGs to explore the causal impact of epidemiological factors on 30-day mortality among patients following their first acute ST-elevation myocardial infarction (STEMI).
methodThe study employs data from the North India (NORIN)-STEMI study registry, comprising 3,192 first-time STEMI patients collected prospectively from two tertiary care hospitals in Delhi, India. Continuous optimization structure learning using the Non-combinatorial Optimization via Trace Exponential and Augmented Lagrangian for Structure Learning (NOTEARS) method is applied to learn the DAG. Additionally, a permutation testing framework is proposed for the statistical validation of the links of the DAG.
resultsAmong 2,946 first-time STEMI patients, 246 (7.7%) experienced mortality during the study period. A t-test revealed that age was significantly different between the survival and mortality groups within 30 days post-STEMI (p<0.0001). Patients who died within 30 days had a higher mean age (59.90±13.89 years). Furthermore, the study identified a statistically significant association between mortality and HbA1c, triglycerides, smoking, sex, education, occupation, socioeconomic status, physical activity, overall stress, and hypertension.
conclusionOur DAG reveals causal relationships and identifies confounding variables affecting mortality after STEMI. Sex is identified as a significant factor influencing mortality both directly and indirectly. This influence occurs through its effects on age, alcohol consumption, stress, hypertension, and socioeconomic status. Additionally, sex is recognized as a confounding factor whose impact on mortality is modified by other factors.
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