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Total cholesterol variability and risk of atrial fibrillation: A nationwide population-based cohort study.
PloS One 2019
BACKGROUND: Long-term variability of cardiometabolic risk factors have been suggested as the risk factors for cardiovascular disease and mortality. However, the effect of long-term variability of total cholesterol (TC) on incident atrial fibrillation (AF) has not been examined.
METHODS AND FINDINGS: We explored whether visit-to-visit TC variability are associated with the risk of incident AF in 160,165 Korean adults, using the population-based Korean National Health Insurance Service-Health Screening Cohort (NHIS-HEALS) database, over a median duration of 8.4 years. TC variability was measured as coefficients of variance (TC-CV), standard deviation (TC-SD), and variability independent of the mean (TC-VIM). Kaplan-Meier analysis demonstrated a decreased disease-free probability in the highest quartile group of TC variability compared to that in the other groups. In the multivariate Cox proportional hazard analysis, the risk of AF increased significantly in the highest quartile group of TC variability. After multivariate adjustment for confounding variables including mean TC levels, the hazard ratio for incident AF was 1.15 (95% confidence interval 1.05-1.25; P = 0.0035) when comparing the highest with the lowest TC variability quartile (TC-CV). These relationships were consistent with TC variability defined using TC-SD or TC-VIM. Subgroup analyses, including age, sex, body mass index, and cardiometabolic disorders, showed similar results.
CONCLUSIONS: The present study is the first to demonstrate that high TC variability was associated with an increased risk of AF.
METHODS AND FINDINGS: We explored whether visit-to-visit TC variability are associated with the risk of incident AF in 160,165 Korean adults, using the population-based Korean National Health Insurance Service-Health Screening Cohort (NHIS-HEALS) database, over a median duration of 8.4 years. TC variability was measured as coefficients of variance (TC-CV), standard deviation (TC-SD), and variability independent of the mean (TC-VIM). Kaplan-Meier analysis demonstrated a decreased disease-free probability in the highest quartile group of TC variability compared to that in the other groups. In the multivariate Cox proportional hazard analysis, the risk of AF increased significantly in the highest quartile group of TC variability. After multivariate adjustment for confounding variables including mean TC levels, the hazard ratio for incident AF was 1.15 (95% confidence interval 1.05-1.25; P = 0.0035) when comparing the highest with the lowest TC variability quartile (TC-CV). These relationships were consistent with TC variability defined using TC-SD or TC-VIM. Subgroup analyses, including age, sex, body mass index, and cardiometabolic disorders, showed similar results.
CONCLUSIONS: The present study is the first to demonstrate that high TC variability was associated with an increased risk of AF.
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