A novel ECG algorithm for accurate localization of manifest accessory pathways in both children and adults: SMART-WPW.

BACKGROUND

Accessory pathway (AP) ablation is an established therapy for patients with Wolff-Parkinson-White (WPW) syndrome. An accurate 12-lead electrocardiogram (ECG)-based identification of the AP location is crucial for an optimized risk assessment and ablation.

OBJECTIVE

This study aimed to develop and validate a simplified 12-lead ECG algorithm for accurate localization of AP in WPW syndrome, to improve procedural risk assessment, ablation planning, and outcomes.

METHODS

In this multicenter study, 260 patients with a single manifest AP undergoing WPW ablation were enrolled. The SMART-WPW algorithm was developed and prospectively tested and compared with established Pambrun and Arruda algorithms. The novel SMART-WPW algorithm allows for a stepwise localization of 12 ablation targets, which are displayed on a clock representation.

RESULTS

SMART-WPW algorithm correctly identified the AP in 253 of 260 patients (97%) (mean age 34 ± 19 years; 51% female), with a sensitivity of 96%, specificity of 100%, positive predictive value of 95%, and negative predictive value of 100%. High accuracy was achieved for right-sided APs between 4 and 8 o'clock (100% sensitivity and specificity) and for left-sided APs between 5 and 8 o'clock (100% sensitivity and specificity). The SMART-WPW algorithm outperformed the Pambrun (97% vs 90%, P = .015) and Arruda algorithms (97% vs 73%, P < .001). In a subgroup of children younger than 18 years (n = 76; mean age 14 ± 3 years; 61% female), the algorithm showed higher accuracy than the Arruda algorithm (97% vs 62%, P < .001).

CONCLUSION

The SMART-WPW algorithm is an accurate, efficient, and reproducible tool for 12-lead ECG-based AP localization. Its use may enhance preprocedural assessment and ablation planning in WPW syndrome.