Risk prediction in ACS remains clinically challenging. In a retrospective study published in BMC Cardiovascular Disorders, a multivariable nomogram was developed to estimate risk in patients with ACS and coexisting hypertension.

The analysis included 980 patients diagnosed with ACS between 2018 and 2023. Diagnoses followed national guideline criteria for ST-segment elevation myocardial infarction (STEMI), non–ST-segment elevation myocardial infarction (NSTEMI), and unstable angina (UA). Demographic characteristics, history of hypertension, baseline laboratory parameters, and cardiac Doppler ultrasonography findings were collected. Least absolute shrinkage and selection operator (LASSO) regression identified candidate predictors, which entered multivariable logistic regression to construct the nomogram.

Unstable angina (UA) accounted for 592 cases (60.4%). A history of hypertension was present in 682 patients (69.59%), with a mean age of 64.93 ± 9.51 years. Significant differences were observed across patient subgroups for sex (P = 0.001), age (P < 0.001), ACS subtype (P < 0.001), creatinine (P < 0.001), left ventricular ejection fraction (LVEF; P = 0.049), left ventricular posterior wall thickness (LVPW; P = 0.003), creatine kinase–MB (CK-MB; P = 0.019), aspartate aminotransferase (AST; P = 0.028), total cholesterol (TC; P = 0.035), low-density lipoprotein cholesterol (LDL-C; P = 0.007), and apolipoprotein B (APOB; P = 0.005).

Nine variables were retained in the final model. Calibration curves, the Hosmer–Lemeshow test, receiver operating characteristic (ROC) analysis, decision curve analysis, and clinical impact curves all demonstrated strong model performance.

This nomogram provides a structured approach for risk stratification in ACS with coexisting hypertension and supports early risk assessment and prognostic evaluation.