176-30: Performance of the SA-VA difference to differentiate atrioventricular nodal reentrant tachycardia from orthodromic reentrant tachycardia in a large cohort of consecutive patients

Abstract

Background: The SA-VA difference represents a simple diagnostic maneuver to distinguish between atrioventricular nodal reentrant tachycardia (AVNRT) and orthodromic reentrant tachycardia (ORT) during electrophysiology study. However, its usefulness has largely been studied in selected patient subgroups. Objective: The purpose of this study was to evaluate the performance of the SA-VA difference against commonly used diagnostic maneuvers in a large cohort of consecutive patients. Methods: Consecutive patients with inducible supraventricular tachycardia and successful entrainment through pacing trains from right ventricular apex during an electrophysiological study were included. Atrial tachycardias were excluded. The following intervals were calculated for each patients: SA-VA difference; his potential and atrial electrogram during entrainment minus his potential and atrial electrogram during tachycardia (ΔHA); and the corrected return cycle (cPPI-TCL). Results: A total of 456 patients fulfilled the inclusion criteria, of which electrophysiological study revealed 265 typical AVNRT, 38 atypical AVNRT, 54 and 108 ORT through a septal and free-wall accessory pathway, respectively. An SA-VA difference >99 ms identified AVNRT in all patients with sensitivity, specificity, positive and negative predictive values of 97.7%, 96.9%, 98.3%, and 95.7%, respectively. Conclusions: This study confirms the high ability to distinguish AVNRT from ORT using the SA-VA difference, not only in selected patient subgroups, but as whole when a cutoff of >99 ms is used. Comparison of pacing maneuvers for AVNRT vs. ORT AUC = area under ROC curve (95% CI); NPC = negative predictive value; PPV = positive predictive value. Comparison of pacing maneuvers for AVNRT vs. ORT AUC = area under ROC curve (95% CI); NPC = negative predictive value; PPV = positive predictive value.