Work

Construction of a Nomogram Prediction Model for Mortality Risk Within 14 Days in Patients with Acute Myocardial Infarction and Ventricular Septal Rupture

Year: 2026

Type: article

Abstract: Objective: This study aimed to develop a nomogram prediction model for predicting 14-day in-hospital mortality in patients with acute myocardial infarction (AMI) and ventricular septal rupture (VSR). Methods: Clinical data of 86 hospitalized patients (44 survivors and 42 non-survivors within 14 days) were retrospectively collected in Nanjing First Hospital from 1 March 2015 to 7 August 2025. Lasso regression and multivariable logistic regression were used to identify predictors, which were subsequently incorporated into the nomogram development. The model performance was assessed using area under the receiver operating characteristic curve (AUC), calibration plots, decision curve analysis (DCA), and clinical impact curves, with internal validation via 1000 bootstrap resamples. Results: Analysis of lasso regression and multivariable logistic regression analysis identified WBC count (OR = 1.31, 95% CI: 1.01–1.28, p = 0.040), D-dimer level (OR = 1.18, 95% CI: 1.01–1.38, p = 0.043), early revascularization (OR = 0.22, 95% CI: 0.06–0.88, p = 0.032), ventilatory support (OR = 3.48, 95% CI: 1.07–11.29, p = 0.038), and infection (OR = 3.97, 95% CI: 1.02–15.42, p = 0.047) as independent predictors of 14-day mortality for patients. Based on the results, a prediction nomogram model was constructed. The model achieved an area under the receiver operating characteristic curve (AUC) of 0.866 (95% CI: 0.785–0.946), with sensitivity of 0.857 (95% CI: 0.751–0.963) and specificity of 0.818 (95% CI: 0.704–0.932). Calibration plots demonstrated acceptable agreement between predicted and observed probabilities; decision curve analysis (DCA) and clinical impact curve further confirmed its net benefit and clinical utility. By 1000 bootstrap resampling iterations, the model demonstrated an apparent AUC of 0.864, 95% CI: 0.776–0.938, confirming reasonable discriminative performance. Conclusions: In summary, this study developed a clinical interpretable nomogram to estimate short-term (14-day) in-hospital mortality risk in patients with AMI-VSR; it provides a robust and interpretable tool for predicting short-term in-hospital mortality.

Source: Journal of Clinical Medicine

DOI: 10.3390/jcm15082919