ArticleFrontiers in cardiovascular medicine2021
A Simple Logistic Regression Model for Predicting the Likelihood of Recurrence of Atrial Fibrillation Within 1 Year After Initial Radio-Frequency Catheter Ablation Therapy.
Article in Frontiers in cardiovascular medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Predictive Value of Machine Learning for Recurrence of Atrial Fibrillation after Catheter Ablation: A Systematic Review and Meta-Analysis.Reviews in cardiovascular medicine · 2023Pooled it
- Predictors of atrial fibrillation recurrence after catheter ablation: a systematic review.The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology · 2026Review
- Article
- A deep learning model integrating structured data and clinical text for predicting atrial fibrillation recurrence.NPJ digital medicine · 2026Article
- Artificial Intelligence in Cardiac Electrophysiology: A Clinically Oriented Review with Engineering Primers.Bioengineering (Basel, Switzerland) · 2025Review
- Deep learning radiomics of left atrial appendage features for predicting atrial fibrillation recurrence.BMC medical imaging · 2025Article
- Left atrial strain predicts paroxysmal atrial fibrillation recurrence after catheter ablation: a 1-year study using three-dimensional speckle-tracking echocardiography.BMC cardiovascular disorders · 2025Article
- Association between triglyceride-glucose index trajectories and radiofrequency ablation outcomes in patients with stage 3D atrial fibrillation.Cardiovascular diabetology · 2024Article
- Postoperative recurrence prediction model for atrial fibrillation: a meta-analysis.American journal of translational research · 2024Review
- Primer on Machine Learning in Electrophysiology.Arrhythmia & electrophysiology review · 2023Review
- A Novel Prognostic Model for Identifying the Risk of Hepatocellular Carcinoma Based on Angiogenesis Factors.Frontiers in genetics · 2022Article
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe clinical factors associated with the recurrence of atrial fibrillation (Af) in patients undergoing catheter ablation (CA) are still ambiguous to date. PURPOSE: 1. To recognize preoperative serologic factors and clinical features associated with Af recurrence after the first ablation treatment. 2. To Develop a Logical Regression Model for Predicting the Likelihood of Recurrence Within 1 Year After the Initial Radio-Frequency Catheter Ablation (RFCA) Therapy.
methodsAtrial fibrillation patients undergoing RFCA at our institution from January 2016 to June 2021 were included in the analysis (
resultsThe left atrial diameter, albumin, type of Af, whether other arrhythmias were combined, and the duration of Af attack time were associated with Af recurrence in this sample. Some clinically meaningful variables were selected and combined with recognized factors associated with recurrence to construct a logistic regression prediction model for 1-year Af recurrence. The receiver operating characteristic (ROC) curve for this model was 0.8695, and the established prediction model had a C-index of 0.83. The performance was superior to the extreme curve in the decision curve analysis.
conclusionOur study demonstrates that several clinical features and serological markers can predict the recurrence of Af in patients undergoing RFCA. This simple model can play a crucial role in guiding physicians in preoperative evaluation and clinical decision-making.
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