Why the study?
The long-term prognosis of patients with non-ST-elevation acute coronary syndrome with concomitant mild-to-moderate aortic regurgitation remains poorly understood in contemporary cardiovascular practice.
Cohort (n=719)
Yes
A multimodal data-derived nomogram incorporating diabetes, NLR, NT-proBNP, and coronary stenosis severity demonstrated robust predictive accuracy for 2- and 3-year MACE in NSTE-ACS patients with mild-to-moderate aortic regurgitation.
May aid MACE risk stratification in NSTE-ACS with mild-to-moderate AR; leaves open need for prospective validation before clinical adoption.
The long-term prognosis of patients with non-ST-elevation acute coronary syndrome (NSTE–ACS) with concomitant mild-to-moderate aortic regurgitation (AR) remains poorly understood in contemporary cardiovascular practice. Consequently, we aimed to develop and externally validate a novel prognostic model for predicting Major Adverse Cardiovascular Events (MACE) in NSTE–ACS patients. This multicenter retrospective cohort study involved 719 patients with a confirmed diagnosis of NSTE–ACS complicated with mild-to-moderate AR across four tertiary cardiovascular centers between January 2018 and December 2020. The primary endpoint was MACE occurrence during follow-up. Based on institutional enrollment, the subjects were stratified into two groups: training ( n = 466) and independent external validation ( n = 253) cohorts. The predictive model was developed using four independent predictors [diabetes mellitus (DM), neutrophil-to-lymphocyte ratio (NLR), N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels, and number of coronary arteries with ≥ 50% stenosis], which were identified through a two-step screening process involving LASSO regression and Boruta algorithm analysis, and multivariable Cox regression analysis. The prognostic nomogram also exhibited favorable predictive performance with good discrimination, calibration, and potential clinical utility, with corresponding Area Under the Receiver Operating Characteristic values of 0.784 (95% CI 0.663–0.904) and 0.786 (95% CI 0.705–0.868). Calibration plots and decision curve analysis suggested good agreement between predicted and observed risks and indicated potential clinical usefulness across relevant threshold probabilities. An interactive tool was further developed to facilitate individualized risk estimation. Our multimodal data-derived nomogram demonstrated robust predictive accuracy for 2- and 3-year MACE occurrence in NSTE–ACS patients with concomitant mild-to-moderate AR.
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Zhao et al. (2026) conducted a cohort in Non-ST-Elevation Acute Coronary Syndrome with mild to moderate Aortic Regurgitation (n=719). Nomogram-based risk stratification model was evaluated on Major Adverse Cardiovascular Events (MACE) occurrence during follow-up.
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