Why the study?
There is no gold standard to predict recurrence after catheter ablation of paroxysmal atrial fibrillation, prompting the development of a prognostic tool.
Can a novel prognostic nomogram predict the recurrence of paroxysmal atrial fibrillation after first-time catheter ablation?
Can a novel prognostic nomogram predict the recurrence of paroxysmal atrial fibrillation after first-time catheter ablation?
A novel 5-factor nomogram using baseline clinical, echocardiographic, and electrocardiographic parameters can effectively predict the risk of arrhythmia relapse after first-time catheter ablation for paroxysmal AF.
May aid post-PAF ablation risk stratification; leaves open prospective validation before clinical use.
There is no gold standard to tell frustrating outcomes after the catheter ablation of paroxysmal atrial fibrillation (PAF). The study aims to construct a prognostic tool. We retrospectively analyzed 315 patients with PAF who underwent first-time ablation at the Second Xiangya Hospital of Central South University. The endpoint was identified as any documented relapse of atrial tachyarrhythmia lasting longer than 30 s after the three-month blanking period. Univariate Cox regression analyzed eleven preablation parameters, followed by two supervised machine learning algorithms and stepwise regression to construct a nomogram internally validated. Five factors related to ablation failure were as follows: female sex, left atrial appendage emptying flow velocity ≤31 cm/s, estimated glomerular filtration rate <65.8 mL/(min·1.73 m2), P wave duration in lead aVF ≥ 120 ms, and that in lead V1 ≥ 100 ms, which constructed a nomogram. It was correlated with the CHA2DS2-VASc score but outperformed the latter evidently in discrimination and clinical utility, not to mention its robust performances in goodness-of-fit and calibration. In addition, the nomogram-based risk stratification could effectively separate ablation outcomes. Patients at risk of relapse after PAF ablation can be recognized at baseline using the proposed five-factor nomogram.
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Huang et al. (2023) studied this question.
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