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Electrocardiographic Diagnosis of Biventricular Pacing in Patients with Nonapical Right Ventricular Leads
Author(s) -
JASTRZEBSKI MAREK,
KUKLA PIOTR,
FIJOREK KAMIL,
SONDEJ TOMASZ,
CZARNECKA DANUTA
Publication year - 2012
Publication title -
pacing and clinical electrophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.686
H-Index - 101
eISSN - 1540-8159
pISSN - 0147-8389
DOI - 10.1111/j.1540-8159.2012.03476.x
Subject(s) - medicine , qrs complex , cardiology , electrocardiography , ventricular pacing , lead (geology) , cardiac pacing , algorithm , heart failure , computer science , geomorphology , geology
Background: Assessment of left ventricular (LV) capture is of paramount importance in patients with biventricular (BiV) pacing. Our goal was to identify electrocardiographic features that differentiate between BiV and right ventricular (RV)‐only pacing in patients with nonapical RV leads.Methods: The study enrolled 300 consecutive patients with BiV devices and nonapical RV leads, and obtained from them 558 electrocardiograms with either BiV pacing (n = 300) or RV‐only pacing (n = 258). RV pacing served as a surrogate for loss of LV capture. Electrocardiograms from the first 150 patients were used to identify BiV‐specific features, and to construct an algorithm to differentiate between BiV and RV‐only pacing. Electrocardiograms from the second 150 patients were used to validate the algorithm.Results: The following electrocardiographic features typical of BiV pacing were identified: QS in lead V6 (specificity = 98.7%, sensitivity = 54.7%), dominant R in lead V1 (specificity = 100%, sensitivity = 23.3%), q in lead V6 (specificity = 96%, sensitivity = 22.7%), and a QRS < 160 ms (specificity = 100%, sensitivity = 66.0%). The algorithm based on those features was found to have an overall diagnostic accuracy of 95.0%, a specificity of 96.0%, and a sensitivity of 93.5%.Conclusions: The study identified QRS features that were very specific for BiV pacing in patients with nonapical RV leads. Sequential arrangement of those features resulted in an algorithm that was very accurate for differentiating between BiV pacing and loss of LV capture. (PACE 2012; 35:1199–1208)