RESUMO
INTRODUCTION: Cardiac Autonomic Dysfunction (CAD) is an overlooked cardiovascular risk factor in individuals with obesity-related hypertension. Despite its clinical significance, there is a notable lack of clarity regarding the pathophysiological correlates involved in its onset and progression. AIM: The present study aimed to identify potential predictors of CAD in obesity-related hypertension. METHODS: A total of 72 participants (34 men and 38 women) were enrolled. Comprehensive evaluations were conducted, including cardiac autonomic function assessments, body composition estimation and biochemical analysis. Participants were categorized as CAD-positive or CAD-negative based on Ewing's criteria for autonomic dysfunction. Univariate logistic regression analysis was performed to identify potential predictors for CAD. Multivariate logistic regression models were further constructed by adjusting clinically relevant covariates to identify independent predictors of CAD. RESULTS: Multivariate logistic regression analysis revealed that resting heart rate (HRrest), (odds ratio, confidence interval: 0.85, 0.78-0.93; p = 0.001) and percentage body fat (BF%), (odds ratio, confidence interval: 0.78, 0.64-0.96; p = 0.018) were significant independent predictors of CAD. Receiver Operating Characteristic curve analysis depicted optimal cut-off values for HRrest and BF% as > 74.1 bpm and > 33.6%, respectively. Multicolinearity analysis showed variance inflation factors (VIF) below the cautionary threshold of 3. CONCLUSIONS: The HRrest and BF% emerged as significant independent predictors of CAD in obesity-related hypertension. Therapeutic strategies should target HRrest < 74.1 bpm and BF% < 33.6% to mitigate CAD risk in this population. Future trials are required to establish causal relationships and may consider additional confounding variables in obesity-related hypertension.
