Development and Validation of a Nomogram to Predict Ventricular Fibrillation During Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction

Background: Ventricular fibrillation (VF) is a life-threatening complication of acute myocardial infarction (AMI), particularly in patients undergoing percutaneous coronary intervention (PCI). Early identification of high-risk patients is crucial for implementing preventive measur...

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Main Authors: Ruifeng Liu, Xiangyu Gao, Jihong Fan, Huiqiang Zhao
Format: Article
Language:English
Published: IMR Press 2025-07-01
Series:Reviews in Cardiovascular Medicine
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Online Access:https://www.imrpress.com/journal/RCM/26/7/10.31083/RCM37301
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author Ruifeng Liu
Xiangyu Gao
Jihong Fan
Huiqiang Zhao
author_facet Ruifeng Liu
Xiangyu Gao
Jihong Fan
Huiqiang Zhao
author_sort Ruifeng Liu
collection DOAJ
description Background: Ventricular fibrillation (VF) is a life-threatening complication of acute myocardial infarction (AMI), particularly in patients undergoing percutaneous coronary intervention (PCI). Early identification of high-risk patients is crucial for implementing preventive measures and improving outcomes. Methods: This retrospective study analyzed clinical, laboratory, and angiographic data from 155 AMI patients to identify predictors of VF during PCI. Variable selection was performed using least absolute shrinkage and selection operator (LASSO) regression, elastic net regression, and random forest. Independent predictors were identified through multivariable logistic regression, and a nomogram was developed and validated to predict VF risk. Model performance was assessed using receiver operating characteristic (ROC) and calibration curves. Results: Independent predictors of VF included diabetes (OR = 3.676 (1.365–10.668); p = 0.012), neutrophil-to-lymphocyte ratio (NLR) (odds ratio (OR) = 1.149 (1.053–1.265); p = 0.002), right coronary artery (RCA) intervention (OR = 3.185 (1.088–9.804); p = 0.037), Gensini score (OR = 1.020 (1.007–1.033); p = 0.003), and absence of beta blockers (OR = 0.168 (0.054–0.472); p = 0.001). The nomogram, incorporating these predictors, demonstrated a strong discriminative ability with an area under the ROC curve (AUC) of 0.882 (0.825–0.939) and good calibration (Hosmer–Lemeshow test, p = 0.769). The calibration curve showed a strong alignment between predicted probabilities and observed outcomes, with a mean absolute error of 0.033. Conclusions: This study identified diabetes, NLR, RCA intervention, Gensini score, and absence of beta-blocker use as key predictors of VF during PCI in AMI patients. A nomogram incorporating these factors showed strong predictive performance, aiding clinicians in identifying high-risk patients for targeted preventive strategies.
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spelling doaj-art-fb947cb58f5d4ca98b715b6bf34980c82025-08-20T04:02:12ZengIMR PressReviews in Cardiovascular Medicine1530-65502025-07-012673730110.31083/RCM37301S1530-6550(25)01839-3Development and Validation of a Nomogram to Predict Ventricular Fibrillation During Percutaneous Coronary Intervention in Patients With Acute Myocardial InfarctionRuifeng Liu0Xiangyu Gao1Jihong Fan2Huiqiang Zhao3Department of Cardiology, Beijing Friendship Hospital Affiliated to Capital Medical University, 100050 Beijing, ChinaDepartment of Cardiology, Beijing Friendship Hospital Affiliated to Capital Medical University, 100050 Beijing, ChinaDepartment of Cardiology, Beijing Friendship Hospital Affiliated to Capital Medical University, 100050 Beijing, ChinaDepartment of Cardiology, Beijing Friendship Hospital Affiliated to Capital Medical University, 100050 Beijing, ChinaBackground: Ventricular fibrillation (VF) is a life-threatening complication of acute myocardial infarction (AMI), particularly in patients undergoing percutaneous coronary intervention (PCI). Early identification of high-risk patients is crucial for implementing preventive measures and improving outcomes. Methods: This retrospective study analyzed clinical, laboratory, and angiographic data from 155 AMI patients to identify predictors of VF during PCI. Variable selection was performed using least absolute shrinkage and selection operator (LASSO) regression, elastic net regression, and random forest. Independent predictors were identified through multivariable logistic regression, and a nomogram was developed and validated to predict VF risk. Model performance was assessed using receiver operating characteristic (ROC) and calibration curves. Results: Independent predictors of VF included diabetes (OR = 3.676 (1.365–10.668); p = 0.012), neutrophil-to-lymphocyte ratio (NLR) (odds ratio (OR) = 1.149 (1.053–1.265); p = 0.002), right coronary artery (RCA) intervention (OR = 3.185 (1.088–9.804); p = 0.037), Gensini score (OR = 1.020 (1.007–1.033); p = 0.003), and absence of beta blockers (OR = 0.168 (0.054–0.472); p = 0.001). The nomogram, incorporating these predictors, demonstrated a strong discriminative ability with an area under the ROC curve (AUC) of 0.882 (0.825–0.939) and good calibration (Hosmer–Lemeshow test, p = 0.769). The calibration curve showed a strong alignment between predicted probabilities and observed outcomes, with a mean absolute error of 0.033. Conclusions: This study identified diabetes, NLR, RCA intervention, Gensini score, and absence of beta-blocker use as key predictors of VF during PCI in AMI patients. A nomogram incorporating these factors showed strong predictive performance, aiding clinicians in identifying high-risk patients for targeted preventive strategies.https://www.imrpress.com/journal/RCM/26/7/10.31083/RCM37301acute myocardial infarction (ami)ventricular fibrillation (vf)percutaneous coronary intervention (pci)nomogram
spellingShingle Ruifeng Liu
Xiangyu Gao
Jihong Fan
Huiqiang Zhao
Development and Validation of a Nomogram to Predict Ventricular Fibrillation During Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction
Reviews in Cardiovascular Medicine
acute myocardial infarction (ami)
ventricular fibrillation (vf)
percutaneous coronary intervention (pci)
nomogram
title Development and Validation of a Nomogram to Predict Ventricular Fibrillation During Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction
title_full Development and Validation of a Nomogram to Predict Ventricular Fibrillation During Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction
title_fullStr Development and Validation of a Nomogram to Predict Ventricular Fibrillation During Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction
title_full_unstemmed Development and Validation of a Nomogram to Predict Ventricular Fibrillation During Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction
title_short Development and Validation of a Nomogram to Predict Ventricular Fibrillation During Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction
title_sort development and validation of a nomogram to predict ventricular fibrillation during percutaneous coronary intervention in patients with acute myocardial infarction
topic acute myocardial infarction (ami)
ventricular fibrillation (vf)
percutaneous coronary intervention (pci)
nomogram
url https://www.imrpress.com/journal/RCM/26/7/10.31083/RCM37301
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