Construction of a Nomogram Prediction Model for Mortality Risk Within 14 Days in Patients with Acute Myocardial...

Area of Science:

• Cardiology
• Medical Prediction Models
• Critical Care Medicine

Background:

• Acute myocardial infarction (AMI) with ventricular septal rupture (VSR) is a severe complication with high mortality.
• Predicting short-term mortality is crucial for timely intervention and resource allocation.

Purpose of the Study:

• To develop and validate a nomogram prediction model for 14-day in-hospital mortality in patients with AMI-VSR.
• To identify independent predictors of short-term mortality in this patient cohort.

Main Methods:

• Retrospective analysis of clinical data from 86 hospitalized AMI-VSR patients.
• Utilized Lasso and multivariable logistic regression to identify significant predictors.
• Constructed a nomogram incorporating identified predictors and validated its performance.

Main Results:

• White blood cell (WBC) count, D-dimer level, early revascularization, ventilatory support, and infection were identified as independent predictors.
• The nomogram demonstrated strong predictive accuracy with an AUC of 0.866.
• The model showed good calibration and clinical utility through decision curve analysis.

Conclusions:

• A clinically interpretable nomogram was successfully developed to predict 14-day in-hospital mortality in AMI-VSR patients.
• This tool offers a robust method for estimating short-term mortality risk.
• The nomogram can aid clinicians in risk stratification and management decisions for AMI-VSR patients.