Validation of a novel automated signal analysis tool for ablation of Wolff-Parkinson-White Syndrome

White (mutation)
DOI: 10.1371/journal.pone.0217282 Publication Date: 2019-06-26T17:29:53Z
ABSTRACT
Background In previous pilot work we demonstrated that a novel automated signal analysis tool could accurately identify successful ablation sites during Wolff-Parkinson-White (WPW) at single center. Objective We sought to validate and refine this in larger multi-center cohort of children with WPW. Methods A retrospective review was performed data from WPW who underwent two pediatric arrhythmia centers 2008–2015. All patients ≤ 21 years invasive electrophysiology study signals available for were included. Signals excluded if temperature or power delivery inadequate lesion time < 5 seconds. Ablation lesions reviewed each patient. classified as there loss antegrade retrograde accessory pathway (AP) conduction unsuccessful did not eliminate AP conduction. Custom software analyzed intracardiac electrograms amplitudes, high low frequency components, integrated area, timing components create score. validated the previously published score threshold 3.1 larger, more diverse explored additional scoring options. Logistic regression lasso regularization using Youden’s index criterion cost-benefit thresholds considered refinement Results 347 (141 successful, 206 unsuccessful) 144 pts [mean age 13.2 ± 3.9 years, 96 (67%) male, 66 (45%) left sided APs]. The correctly identified 276/347 (80%) 3.1. performance other significantly improve predictive ability. provided following diagnostic accuracy distinguishing signal: sensitivity 83%, specificity 77%, PPV 71%, NPV 87%. Conclusions An reliably distinguished versus when large, cohort. Refining tools an alternative statistical method original This effective across multiple operators may be
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