Background: Pacing-induced cardiomyopathy (PICM) is a frequent complication of right ventricular pacing that often requires reoperation for biventricular or conduction system pacing. Better methods for predicting PICM may inform initial pacing strategy and follow-up monitoring.
Objective: The purpose of this study was to determine whether the spatial ventricular gradient (SVG), a vectorcardiographic marker of ventricular electrical and mechanical heterogeneity, is associated with the subsequent development of PICM.
Methods: This was a retrospective study of patients with pacemakers implanted between 2003 and 2012 at the Hospital of the University of Pennsylvania. Baseline demographic, echocardiographic, and electrocardiographic parameters, including SVG magnitude, elevation, and azimuth, were measured from standard 12-lead electrocardiograms. Adjusted Cox proportional hazards modeling was used to assess the associations between the SVG and the risk of PICM over follow-up.
Results: Of the 203 patients with a median age of 74 years (54% male; median baseline left ventricular ejection fraction 65%), 44 (22%) developed PICM during follow-up. In unadjusted Cox regression, male sex, native QRS duration in patients without bundle branch block, and both native and paced mean adjusted SVG azimuth predicted future PICM. After multivariable adjustment, higher tertile (tertile 3 vs tertiles 1-2) of the mean adjusted SVG azimuth before (adjusted hazard ratio 1.95; P = .047) and immediately after (adjusted hazard ratio 2.55; P=.003) pacemaker implantation remained significant predictors of PICM.
Conclusion: Assessment of the SVG both before and immediately after pacemaker implantation can help identify patients at elevated risk of PICM and may identify a cohort of patients who would be better served with initial biventricular or conduction system pacing.
Keywords: Pacemaker; Pacing-induced cardiomyopathy; Right ventricular pacing; Risk prediction; Spatial ventricular gradient.
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