Nomogram-based risk stratification model for non-ST-elevation acute coronary syndrome patients with concomitant mild-to-moderate aortic regurgitation: insights from a multicenter cohort study

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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Journal
European journal of medical research
Published
2026-08-03
DOI
https://doi.org/10.1186/s40001-026-04999-1
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
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article
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article

Nomogram-based risk stratification model for non-ST-elevation acute coronary syndrome patients with concomitant mild-to-moderate aortic regurgitation: insights from a multicenter cohort study

Tongjian Zhu, Bowen Zhou, Peng Zhao, Wenqiang Fang et al.
European journal of medical research
Inflammatory Biomarkers in Disease Prognosis
article

Nomogram-based risk stratification model for non-ST-elevation acute coronary syndrome patients with concomitant mild-to-moderate aortic regurgitation: insights from a multicenter cohort study

Tongjian Zhu, Bowen Zhou, Peng Zhao, Wenqiang Fang, Jun Wang, Hui Li, Jinjun Liu, Bing Wu
article en

Abstract

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.

European journal of medical research
Hubei University of Medicine (CN), Bengbu Medical College (CN), Xiangyang Central Hospital (CN), First Affiliated Hospital of Bengbu Medical College (CN), The Fifth People’s Hospital of Suzhou (CN)
Peace, Justice and strong institutions, Reduced inequalities
Openalex Percentile: Top 12%
Inflammatory Biomarkers in Disease Prognosis
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