# Prediction of Non-Cardiac Organ Failure in Acute Myocardial Infarction Patients with Arrhythmia: A Retrospective Case–Control Study

## TL;DR

This study identifies risk factors for non-cardiac organ failure in heart attack patients with arrhythmia to improve early risk assessment.

## Contribution

A predictive model with interpretable risk factors for non-cardiac organ failure in AMI patients with arrhythmia is developed.

## Key findings

- Five independent risk factors were identified for non-cardiac organ failure in AMI patients with arrhythmia.
- The predictive model showed good discriminative ability with an area under the curve of 0.790.
- Internal validation confirmed strong predictive accuracy with a calibration slope of 0.953 and Brier score of 0.067.

## Abstract

Background: Non-cardiac organ failure is a severe complication following acute myocardial infarction (AMI), particularly among patients with concomitant arrhythmia. This study aimed to identify risk factors at admission that were associated with in-hospital non-cardiac organ failure. Methods: This case–control study enrolled AMI patients hospitalized for treatment with any type of arrhythmia. Patients were divided into the complication group and the control group based on the development of non-cardiac organ failure. Relaxed least absolute shrinkage and selection operator (LASSO) logistic regression and multivariate logistic regression were performed to identify risk factors, which were subsequently used to develop a predictive model. Shapley Additive Explanation (SHAP) values were applied to enhance model interpretability. Results: A total of 668 patients were enrolled, including 59 individuals in the complication group. After LASSO-logistic and multivariate logistic regression, five independent risk factors were identified and ranked by their SHAP values: Killip class III/IV [odds ratio (OR)] = 2.409, 95% confidence interval (CI): 1.246–4.657, p = 0.009], fibrin degradation products [OR = 1.029, 95% CI: 1.009–1.049, p = 0.003], N-terminal pro-B-type natriuretic peptide [OR = 1.000, 95% CI: 1.000–1.000, p = 0.002], type 2 diabetes mellitus [OR = 1.888, 95% CI: 1.005–3.546, p = 0.048], and cardiogenic shock [OR = 3.443, 95% CI: 1.463–8.089, p = 0.005]. The model demonstrated good discriminative ability with an area under the curve of 0.790 (95% CI: 0.720–0.861). Internal validation showed a calibration slope of 0.953 and a Brier score of 0.067, indicating strong overall predictive accuracy. Conclusions: This study identified five independent risk factors associated with in-hospital non-cardiac organ failure in AMI patients with arrhythmia. The nomogram might assist in early risk stratification, ultimately improving clinical outcomes in high-risk AMI patients with arrhythmia.