Background: ECG left ventricular hypertrophy (LVH) is a well-known predictor of cardiovascular disease. However, no prior study has characterized patterns of presence/absence of ECG LVH ("ECG LVH trajectories") across the adult lifespan in both sexes and across ethnicities. We examined: (1) correlates of ECG LVH trajectories; (2) the association of ECG LVH trajectories with incident coronary heart disease, transient ischemic attack, ischemic stroke, hemorrhagic stroke, and heart failure; and (3) reclassification of cardiovascular disease risk using ECG LVH trajectories.
Methods And Results: We performed a cohort study among 75 412 men and 107 954 women in the Northern California Kaiser Permanente Medical Care Program who had available longitudinal exposures of ECG LVH and covariates, followed for a median of 4.8 (range <1-9.3) years. ECG LVH was measured by Cornell voltage-duration product. Adverse trajectories of ECG LVH (persistent, new development, or variable pattern) were more common among blacks and Native American men and were independently related to incident cardiovascular disease with hazard ratios ranging from 1.2 for ECG LVH variable pattern and transient ischemic attack in women to 2.8 for persistent ECG LVH and heart failure in men. ECG LVH trajectories reclassified 4% and 7% of men and women with intermediate coronary heart disease risk, respectively.
Conclusions: ECG LVH trajectories were significant indicators of coronary heart disease, stroke, and heart failure risk, independently of level and change in cardiovascular disease risk factors, and may have clinical utility.
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http://dx.doi.org/10.1161/JAHA.116.004954 | DOI Listing |
Int J Cardiol Congenit Heart Dis
June 2024
Division of Cardiology, Department of Medicine, University of British Columbia, Vancouver, Canada.
Background: Surgically repaired Tetralogy of Fallot (rTOF) is associated with progressive right ventricular hypertrophy (RVH) and dilation (RVD). Accurate estimation of RVH/RVD is vital for the ongoing management of this patient population. The utility of the ECG in evaluating patients with rTOF with pre-existing right bundle branch block (RBBB) has not been studied.
View Article and Find Full Text PDFIEEE Open J Eng Med Biol
November 2024
Department of Electronics, Information and Bioengineering (DEIB)Politecnico di Milano 20133 Milano Italy.
Despite the high incidence of left ventricular hypertrophy (LVH), clinical LVH-electrocardiography (ECG) criteria remain unsatisfactory due to low sensitivity. We propose an automatic LVH detection method based on ECG-extracted features and machine learning. ECG features were automatically extracted from two publicly available databases: PTB-XL with 2181 LVH and 9001 controls, and Georgia with 1012 LVH and 1387 controls.
View Article and Find Full Text PDFInt J Cardiol
December 2024
University of North Carolina School of Medicine, Chapel Hill, NC, United States of America; Division of Cardiology, University of North Carolina at Chapel Hill, NC, United States of America. Electronic address:
BMC Geriatr
November 2024
Department of Anesthesia, Hawassa University, Hawassa, Ethiopia.
medRxiv
October 2024
Department of Cardiovascular Medicine, The University of Kansas Medical Center, Kansas City, Kansas.
Background: Traditional ECG criteria for left ventricular hypertrophy (LVH) have low diagnostic yield. Machine learning (ML) can improve ECG classification.
Methods: ECG summary features (rate, intervals, axis), R-wave, S-wave and overall-QRS amplitudes, and QRS/QRST voltage-time integrals (VTIs) were extracted from 12-lead, vectorcardiographic X-Y-Z-lead, and root-mean-square (3D) representative-beat ECGs.
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