Id: 4349493 Sinus Rhythm Ecg During Blanking Period Predicts Zero Recurrence in Persistent Af: a Machine Learning Approach
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Clinical atrial fibrillation (AF) progression from atrial high-rate episodes (AHREs) poses significant clinical risks.Objective: This study aimed to develop a scoring system to predict clinical AF progression.Methods: Patients with documented AHRE but no prior clinical AF were enrolled.A simplified scoring system was developed to predict subsequent clinical AF progression using multivariable logistic regression.Results: Among 182 patients with documented AHRE but no prior clinical AF, 22 (12%) developed clinical AF, confirmed by 12-lead electrocardiogram.Multivariate analysis identified several key predictors for the progression of AHRE to clinical AF (Figure A): CHA 2 DS 2 _VAS score .5 (odds ratio [OR]: 2.811, 95% confidence interval [CI]: 1.114-7.094),left atrial (LA) diameter .46mm (OR: 3.894, 95% CI: 1.499-10.114),and the duration of AHRE, which were strongly correlated with increased progression risk.Based on these factors, a scoring model was developed, assigning points as follows: CHA 2 DS 2 _-VAS score .5 (1 point), LA diameter .46mm (1 point), AHRE duration .6 minutes (1 point), .6 hours (2 points), and .24hours (3 points).The accumulating score (range 0-5) achieved an area under the receiver-operating characteristic curve (AUC) of 0.78 (95% CI: 0.65-0.89),which was superior to CHA 2 DS 2 _VAS score alone (AUC: 0.639, 95% CI: 0.503-0.774)(Figure B) and an accumulated score of ≥4 was associated with a 50% risk of clinical AF progression (Figure C).Conclusion: This simplified scoring system demonstrated high predictive value, effectively stratifying patients by AF progression risk and offering a reliable clinically applicable tool for identifying high-risk individuals.
Source: Heart Rhythm O2
Authors: Michel Abou Khalil, Yishi Jia, Chanho Lim, Christian M. Massad, Mayana Bsoul, Ghassan Bidaoui, Hadi Younes, Mohammad Montaser Atasi, Abboud Hassan, Yara Menassa, Yingshuo Liu, Ala Assaf, Abdel Hadi El Hajjar, Charbel Noujaim, Lilas Dagher, Mario Mekhael, Estelle Taki, Chenguang Zhang, Swati Rao, Omar Kreidieh, Amitabh C. Pandey, Han Feng, Nassir F. Marrouche
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,150
OpenAlex ID: W4413963564