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Electrocardiographic parameters associated with pacemaker induced cardiomyopathy.
Zak Loring1, Anna Giczewska2, Paul Hofmann2
1Duke Clinical Research Institute, Durham, NC, USA; Division of Cardiology, Department of Medicine, Duke University, Durham, NC, USA.
Journal of Electrocardiology
|December 22, 2022
Summary
Identifying patients at risk for pacemaker-induced cardiomyopathy (PiCM) is challenging. This study found that standard electrocardiogram (ECG) data, including advanced features, offered limited predictive value for PiCM development in patients with right ventricular pacing.
Area of Science:
- Cardiology
- Biomedical Engineering
- Medical Diagnostics
Background:
- Chronic right ventricular (RV) pacing can lead to left ventricular (LV) dyssynchrony.
- This dyssynchrony may result in pacemaker-induced cardiomyopathy (PiCM).
- Current methods for identifying patients at risk for PiCM are limited.
Purpose of the Study:
- To identify predictors of PiCM in patients receiving RV-only permanent pacemakers (PPMs).
- To evaluate the utility of pre- and post-pacing electrocardiograms (ECGs), including advanced ECG (A-ECG) parameters, in predicting PiCM.
Main Methods:
- Retrospective analysis of 404 patients with normal baseline ejection fractions (EFs) receiving RV-only PPMs.
- Primary endpoint defined as a decrease in EF, death, or cardiac transplant without competing cause.
- Analysis of scalar ECG measurements (e.g., lead one ratio) and A-ECG features.
Main Results:
- 140 patients (35%) met the primary endpoint in the pre-PPM ECG analysis.
- Predictors included female sex, T' wave in V6, P' wave in aVL, and estimated glomerular filtration rate.
- In post-PPM ECGs, predictors included female sex, age, and history of congestive heart failure.
- Neither lead one ratio nor A-ECG parameters were strong predictors of PiCM.
Conclusions:
- Baseline and paced ECG data offer limited insight into predicting PiCM.
- Further research is needed to identify robust predictors of pacemaker-induced cardiomyopathy.
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