Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

medicine

A Single-lead ECG algorithm to differentiate right from left manifest accessory pathways: A reappraisal of the P-Delta interval

Journal of Cardiovascular Electrophysiology, Volume 34, No. 3, Year 2023

Introduction: Despite numerous ECG algorithms being developed to localize the site of manifest accessory pathways (AP), they often require stepwise multiple-lead analysis with variable accuracy, limitations, and reproducibility. The study aimed to develop a single-lead ECG algorithm incorporating the P-Delta interval (PDI) as an adjunct criterion to discriminate between right and left manifest AP. Methods: Consecutive WPW patients undergoing electrophysiological study (EPS) were retrospectively recruited and split into a derivation and validation group (1:1 ratio). Sinus rhythm ECG analysis in lead V1 was performed by three independent investigators blinded to the EPS results. Conventional ECG parameters and PDI were assessed through the global cohort. Results: A total of 140 WPW patients were included (70 for each group). A score-based, single-lead ECG algorithm was developed through derivation analysis incorporating the PDI, R/S ratio, and QRS onset polarity in lead V1. The validation group analysis confirmed the proposed algorithm's high accuracy (95%), which was superior to the previous ones in predicting the AP side (p < 0.05). A score of ≤+1 was 96.5% accurate in predicting right AP while a score of ≥+2 was 92.5% accurate in predicting left AP. The new algorithm maintained optimal performance in specific subgroups of the global cohort showing an accuracy rate of 90%, 92%, and 96% in minimal pre-excitation, posteroseptal AP, and pediatric patients, respectively. Conclusions: A novel single-lead ECG algorithm incorporating the PDI interval with previous conventional criteria showed high accuracy in differentiating right from left manifest AP comprising pediatric and minimal pre-excitation subgroups in the current study.
Statistics
Citations: 12
Authors: 12
Affiliations: 3
Identifiers
Study Design
Cohort Study