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

• Published in: BMC cardiovascular disorders 2024-11, Vol.24 (1), p.642-11, Article 642
• Main Authors: Zhang, Li-Xiang, Cao, Jiao-Yu, Zhou, Xiao-Juan
• Format: Article
• Language: English
• Subjects: Acute myocardial infarction; Age; Aged; Alanine transaminase; Angioplasty; Atrial fibrillation; Atrial Fibrillation - diagnosis; Atrial Fibrillation - physiopathology; Blood pressure; Brain natriuretic peptide; Cardiac arrhythmia; Cardiovascular disease; China - epidemiology; Cholesterol; Coronary vessels; Decision Support Techniques; Diabetes; Female; Fibrillation; Heart; Heart attack; Heart attacks; Hemoglobin; High density lipoprotein; Hospitalization; Humans; Hypertension; Information processing; Intervention; Lipoproteins; Low density lipoprotein; Low density lipoproteins; Male; Medical research; Medicine, Experimental; Metabolic disorders; Middle Aged; Myocardial infarction; Myocardial Infarction - diagnosis; Myocardial Infarction - etiology; Myocardial Infarction - therapy; Natriuretic peptides; New-onset atrial fibrillation; Nomogram; Nomograms; Patients; Percutaneous Coronary Intervention - adverse effects; Prediction model; Prediction models; Predictive Value of Tests; Regression analysis; Reproducibility of Results; Retrospective Studies; Risk Assessment; Risk Factors; Software; Time Factors; Transluminal angioplasty; Treatment Outcome; Type 2 diabetes; Variables; Vein & artery diseases; Ventricle
• ISSN: 1471-2261; 1471-2261
• DOI: 10.1186/s12872-024-04326-8

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. 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. 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