Can we improve the accuracy of electrocardiographic algorithms for accessory pathway location in children?

Background: Predicting an accessory pathway location is extremely important in pediatric patients. Aims: We designed a study to compare previously published algorithms by Arruda, Boersma, and Chiang. Methods: This multicenter study included patients who had undergone successful ablation of one accessory pathway. Analysis of resting 12-lead electrocardiograms was carried out. An aggregated prediction score was constructed on the basis of algorithm agreement, and a structured workflow approach was proposed. Results: The total population was 120 patients (mean age, 12.7 [± 3.6] years). The algorithm by Boersma had the highest accuracy (71.7%). The inter-rater agreement among the 3 reference algorithms, according to left-sided accessory pathway (AP) identification, was good between Boersma and Chiang (κ = 0.611; 95% confidence interval [CI], 0.468–0.753) but moderate between Arruda and Chiang and between Arruda and Boersma (κ = 0.566; 95% CI, 0.419–0.713 and κ = 0.582; 95% CI, 0.438–0.727, respectively). Regarding locations at risk of atrioventricular (AV) block, agreement was fair between Arruda and Chiang and between Boersma and Chiang (κ = 0.358; 95% CI, 0.195–0.520 and κ = 0.307; 95% CI, 0.192–0.422, respectively) but moderate between Arruda and Boersma (κ = 0.45; 95% CI, 0.304–0.597). On applying a first-step diagnostic evaluation, when concordance was achieved, we were able to correctly identify left-sided or non-left-sided ablation sites in 96.4% (n = 80) of cases. When concordance was achieved, correct prediction of risk/no risk of AV block was achieved in 92.2% (n = 59) of cases. Conclusions: An aggregated prediction score based on 3 reference algorithms proved able to predict an accessory pathway location very precisely and could be used to plan safely invasive procedures.