Nikhil Patel1, Wesley T O'Neal2, S Patrick Whalen1, Elsayed Z Soliman1,3. 1. Section of Cardiology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA. 2. Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA. 3. Department of Epidemiology and Prevention, Epidemiological Cardiology Research Center (EPICARE), Wake Forest School of Medicine, Winston-Salem, NC, USA.
Abstract
BACKGROUND: Although left ventricular hypertrophy (LVH) detected by electrocardiography (ECG-LVH) and echocardiography (echo-LVH) independently predict cardiovascular disease events, it is unclear if ECG-LVH and echo-LVH independently predict atrial fibrillation (AF). METHODS: This analysis included 4,904 participants (40% male; 85% white) from the Cardiovascular Health Study who were free of baseline AF and major intraventricular conduction delays. ECG-LVH was defined by Minnesota Code Classification from baseline ECG data. Echo-LVH was defined by sex-specific left ventricular mass values >95th sex-specific percentiles. Incident AF events were identified during the annual study ECGs and from hospitalization discharge data. Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (CI) for the association of ECG-LVH and echo-LVH with incident AF, separately. RESULTS: ECG-LVH was detected in 224 (4.6%) participants and echo-LVH was present in 231 (4.7%) participants. Over a median follow-up of 11.9 years, a total of 1,430 AF events were detected. In a multivariable Cox model adjusted for age, sex, race, education, income, smoking, systolic blood pressure, diabetes, body mass index, total cholesterol, high-density lipoprotein cholesterol, aspirin, antihypertensive medications, and cardiovascular disease, ECG-LVH (HR = 1.50; 95% CI = 1.18, 1.90) and echo-LVH (HR = 1.39; 95% CI = 1.09, 1.78) were independently associated with AF. When ECG-LVH (HR = 1.47, 95% CI = 1.16, 1.87) and echo-LVH (HR = 1.36, 1.07, 1.75) were included in the same model, both were predictive of incident AF. CONCLUSION: The association of ECG-LVH with AF is not dependent on left ventricular mass detected by echocardiography, suggesting that abnormalities in cardiac electrophysiology provide a distinct profile in the prediction of AF.
BACKGROUND: Although left ventricular hypertrophy (LVH) detected by electrocardiography (ECG-LVH) and echocardiography (echo-LVH) independently predict cardiovascular disease events, it is unclear if ECG-LVH and echo-LVH independently predict atrial fibrillation (AF). METHODS: This analysis included 4,904 participants (40% male; 85% white) from the Cardiovascular Health Study who were free of baseline AF and major intraventricular conduction delays. ECG-LVH was defined by Minnesota Code Classification from baseline ECG data. Echo-LVH was defined by sex-specific left ventricular mass values >95th sex-specific percentiles. Incident AF events were identified during the annual study ECGs and from hospitalization discharge data. Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (CI) for the association of ECG-LVH and echo-LVH with incident AF, separately. RESULTS: ECG-LVH was detected in 224 (4.6%) participants and echo-LVH was present in 231 (4.7%) participants. Over a median follow-up of 11.9 years, a total of 1,430 AF events were detected. In a multivariable Cox model adjusted for age, sex, race, education, income, smoking, systolic blood pressure, diabetes, body mass index, total cholesterol, high-density lipoprotein cholesterol, aspirin, antihypertensive medications, and cardiovascular disease, ECG-LVH (HR = 1.50; 95% CI = 1.18, 1.90) and echo-LVH (HR = 1.39; 95% CI = 1.09, 1.78) were independently associated with AF. When ECG-LVH (HR = 1.47, 95% CI = 1.16, 1.87) and echo-LVH (HR = 1.36, 1.07, 1.75) were included in the same model, both were predictive of incident AF. CONCLUSION: The association of ECG-LVH with AF is not dependent on left ventricular mass detected by echocardiography, suggesting that abnormalities in cardiac electrophysiology provide a distinct profile in the prediction of AF.
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