# Development and Validation of a Simple-to-Use Nomogram of In-Hospital Heart Failure in Patients with Acute Myocardial Infarction

## TL;DR

This study creates a simple tool to predict heart failure risk in patients with heart attacks, helping doctors make better treatment decisions.

## Contribution

A novel nomogram is developed and validated for predicting in-hospital heart failure in acute myocardial infarction patients.

## Key findings

- The nomogram includes six predictors such as age and medical history, with good discrimination and calibration.
- It achieved a C-index of 0.68 in training and 0.67 in validation, showing reliable performance.

## Abstract

Background: Patients with acute myocardial infarction (AMI) who experience in-hospital heart failure (HF) would present a higher risk for fatal events. This study aims to develop and validate a simple-to-use diagnostic nomogram to identify high-risk individuals for in-hospital HF in patients with AMI. Methods: Using data from CCC-ACS (Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome) project (2014–2019), this study included 74,697 patients with ST elevation myocardial infarction (STEMI) or non-STEMI (NSTEMI) who admitted within 24 h after symptom onset, without HF, cardiac arrest, or cardiac shock at admission. Independent predictors were identified through univariate logistic regression analyses and least absolute shrinkage and selection operator (LASSO) regression. A nomogram was subsequently constructed based on multivariate logistic regression. The model’s performance was evaluated by its discrimination and calibration, assessed using Harrell’s C-index and calibration curves with Hosmer–Lemeshow goodness-of-fit tests, respectively. Results: Six predictors were selected for the final nomogram, including age, heart rate, history of atrial fibrillation, history of chronic obstructive pulmonary disease, history of chronic HF, and history of chronic kidney disease. The nomogram demonstrated a C-index of 0.68 (95% CI: 0.66–0.69) in the training cohort and 0.67 (95% CI: 0.66–0.69) in the validation cohort. The calibration curves of the nomogram showed a strong calibration, as Hosmer–Lemeshow goodness-of-fit tests yielded chi-squares of 11.00 (p = 0.21) and 8.48 (p = 0.39) for the training and validation cohort, respectively. Conclusions: This simple-to-use nomogram for effectively predicting the risk for in-hospital HF may be used as a helpful tool in clinical decision-making during treatment and management in patients with AMI.