Asymptomatic WPW Pattern Detected by School ECG Screening: Prevalence, Phenotype, and Automated Interpretation Errors

Background/Objectives: The Wolff–Parkinson–White (WPW) pattern is characterized by ventricular preexcitation due to an accessory atrioventricular pathway. Population-based data on the prevalence of asymptomatic WPW patterns in children are limited, and automated ECG interpretation may be misleading in the setting of preexcitation. Our aim was to determine the prevalence of the WPW pattern in a large cohort of asymptomatic Romanian school children and to describe electrocardiographic characteristics, ECG-based accessory pathway localization, and automated ECG interpretation errors. Methods: We performed a retrospective cross-sectional analysis of 12-lead ECGs obtained during a school-based screening program in Romania (May–December 2015). After exclusion of duplicates, technical errors, and participants outside the prespecified age range, 24,112 unique children aged 6–18 years were included. The WPW pattern was adjudicated by pediatric electrophysiologists. Prevalence was estimated using the Wilson score method. Sex differences were assessed using Fisher’s exact test. Results: The WPW pattern was identified in 18/24,112 children, yielding a prevalence of 0.075% (0.75 per 1000). The WPW pattern was more frequent in boys than girls (12/11,858 (0.10%) vs. 6/12,255 (0.048%), p = 0.18). Most cases demonstrated mild preexcitation, with only a minority showing marked QRS widening. ECG-based algorithms suggested a predominance of left-sided accessory pathways. Automated ECG interpretation frequently produced misleading diagnostic statements, including bundle branch block/intraventricular conduction delay (5/18; 27.8%) and pseudo-infarction/ischemia patterns (1/18; 5.6%), and did not explicitly identify WPW/preexcitation. Conclusions: In a large school-based screening cohort of asymptomatic Romanian children, WPW pattern prevalence was 0.074%, with a trend toward male predominance. Most cases exhibited mild preexcitation. Automated ECG interpretation commonly misclassified preexcitation-related ECG findings, highlighting the importance of expert ECG review in pediatric screening programs.