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

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

50 is the new 70: Short ventriculoatrial times are common in children with atrioventricular reciprocating tachycardia.

BACKGROUND: One of the basic electrophysiological principles of atrioventricular reciprocating tachycardia (AVRT) is that ventriculoatrial (VA) times during tachycardia are >70 ms. We hypothesized, however, that children may commonly have VA times <70 ms in AVRT. OBJECTIVE: This study sought to determine the incidence and characteristics associated with short-VA AVRT in children. METHODS: A retrospective single-center review of children with AVRT from 2000 to 2014 was performed. All patients ≤18 years of age with AVRT at electrophysiology study were included. Patients with persistent junctional reciprocating tachycardia, atrioventricular nodal reentry tachycardia, and tachycardia not unequivocally proven to be AVRT were excluded. VA time was defined as the time between earliest ventricular activation and earliest atrial activation in any lead and was confirmed by 2 electrophysiologists. Patients with VA times <70 ms (SHORT-VA) and those with standard VA times ≥70 ms (STD-VA) were compared. Logistic regression analysis identified characteristics of SHORT-VA patients. RESULTS: A total of 495 patients with AVRT were included (mean age 11.7 ± 4.1 years). There were 265 patients (54%) with concealed accessory pathways (APs) and 230 (46%) with Wolff-Parkinson-White syndrome. AP location was left-sided in 301 patients (61%) and right-sided in 194 (39%). The mean VA time in AVRT was 100 ± 33 ms. A total of 63 patients (13%) had VA times <70 ms (SHORT-VA). The shortest VA time during AVRT was 50 ms. There was no difference in age, AV nodal block cycle, or body surface area between SHORT-VA and STD-VA patients, but SHORT-VA patients had lower weight (43 ± 17 vs 51 ± 23 kg, P = .02), lower AV nodal effective refractory period (AVNERP; 269 ± 50 vs 245 ± 52 ms, P < .01), and more left-sided APs (50 [79%] vs 251 [58%]; P < .01]. On multivariate logistic regression, factors associated with SHORT-VA included left-sided AP (odds ratio [OR] 5.79, confidence interval [95% CI] 2.21-15.1, P < .01), shorter AVNERP (OR 0.99, CI 0.98-0.99, P < .01), and lower weight (OR 0.97, CI 0.95-0.99, P < .01). CONCLUSIONS: Children with AVRT can frequently have VA times <70 ms, with 50 ms being the shortest VA time. This finding debunks the classic electrophysiology principle that VA times in AVRT must be >70 ms. SHORT-VA AVRT was more common in children with left-sided APs.