Construction and validation of a nomogram prediction model for the risk of new-onset atrial fibrillation following percutaneous coronary intervention in acute myocardial infarction patients

Abstract

Objective

The objective of this study was to investigate risk factors for new-onset atrial fibrillation (NOAF) post-percutaneous coronary intervention (PCI) in patients with acute myocardial infarction (AMI), aiming to develop a predictive nomogram for NOAF risk.

Methods

A retrospective cohort study involving 397 AMI patients who underwent PCI at a tertiary hospital in Anhui, China, from January 2021 to July 2022 was performed. Patients were divided into NOAF (n = 63) and non-NOAF (n = 334) groups based on post-PCI outcomes. Clinical data were extracted from the hospital information system (HIS) and analyzed using univariate and multivariate logistic regression to identify independent risk factors. A nomogram was generated utilizing R software (version 3.6.1), with its performance evaluated through receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and Bootstrap resampling.

Results

Independent risk factors for NOAF included age, left atrial diameter (LAD), Gensini score, N-terminal pro-B-type natriuretic peptide (NT-proBNP), alanine transaminase (ALT), low-density lipoprotein cholesterol (LDL-C), left ventricular end-systolic diameter (LVESD), and ventricular rate (P < 0.05). The nomogram’s ROC curve demonstrated an area under the curve (AUC) of 0.925 (95% CI: 0.887–0.963), supported by a Bootstrap-verified AUC of 0.924 (95% CI: 0.883–0.954), reflecting strong discriminative capability. The calibration curve indicated a mean absolute error (MAE) of 0.031 and 0.017 prior to and following Bootstrap verification, respectively, signifying robust calibration. The DCA curve illustrated that the nomogram offered optimal clinical net benefit for patients with a threshold probability of NOAF ranging from 0.01 to 0.99.

Conclusion

The nomogram developed from independent risk factors for NOAF exhibits significant predictive accuracy and clinical relevance for evaluating the risk of NOAF in AMI patients following PCI, thereby enabling the identification of high-risk individuals for targeted interventions.