HEART RATE VARIABILITY PATTERNS IN PATIENTS WITH COMMON CHRONIC DISEASES: A COMPREHENSIVE ANALYSIS

Introduction: Heart rate variability (HRV) reflects autonomic nervous system function and may provide insights into cardiovascular health in chronic diseases. This study aimed to characterize and compare HRV patterns across common chronic conditions and identify disease-specific autonomic signatures. Methods: This cross-sectional analytical study was conducted at Department of Physiology, Vyas Medical College & Hospital, Jodhpur, India over 6 months. We recruited 400 participants (80 each with hypertension, diabetes mellitus, COPD, coronary artery disease, and healthy controls) using stratified random sampling. Short-term (10-minute) and 24-hour HRV recordings were obtained. Time-domain, frequency-domain, and non-linear parameters were analyzed. Correlations between HRV indices and clinical variables were examined, and multiple regression analysis was performed to identify independent predictors of HRV reduction. Results: All patient groups demonstrated significantly reduced HRV compared to controls, with diabetes mellitus showing the most profound impairment (56.5% reduction in SDNN, p<0.001), followed by CAD, hypertension, and COPD. Characteristic patterns included reduced overall HRV, impaired parasympathetic modulation (78.4% reduction in HF power in diabetes), relative sympathetic predominance (highest LF/HF ratio in COPD: 1.72±0.48), decreased complexity (lowest entropy in diabetes), and blunted circadian variations. Disease duration, glycemic parameters, inflammatory markers, and cardiac stress indicators correlated significantly with HRV reduction. Multiple regression identified disease type, age, disease duration, and glycemic control as independent predictors of autonomic dysfunction. Conclusion: Distinct autonomic profiles exist across different chronic diseases, reflecting disease-specific pathophysiological mechanisms with important implications for risk stratification and targeted interventions. Integration of HRV assessment into clinical evaluation of chronic disease patients could enhance early detection of autonomic dysfunction and guide personalized therapeutic strategies.

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Publication Details

Published
2025-04-21
DOI
https://doi.org/10.53555/pav78d52
Primary Topic
Heart Rate Variability and Autonomic Control
Type
article
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article

HEART RATE VARIABILITY PATTERNS IN PATIENTS WITH COMMON CHRONIC DISEASES: A COMPREHENSIVE ANALYSIS

Kirti Gupta
Heart Rate Variability and Autonomic Control
article

HEART RATE VARIABILITY PATTERNS IN PATIENTS WITH COMMON CHRONIC DISEASES: A COMPREHENSIVE ANALYSIS

Kirti Gupta
article en

Abstract

Introduction: Heart rate variability (HRV) reflects autonomic nervous system function and may provide insights into cardiovascular health in chronic diseases. This study aimed to characterize and compare HRV patterns across common chronic conditions and identify disease-specific autonomic signatures. Methods: This cross-sectional analytical study was conducted at Department of Physiology, Vyas Medical College & Hospital, Jodhpur, India over 6 months. We recruited 400 participants (80 each with hypertension, diabetes mellitus, COPD, coronary artery disease, and healthy controls) using stratified random sampling. Short-term (10-minute) and 24-hour HRV recordings were obtained. Time-domain, frequency-domain, and non-linear parameters were analyzed. Correlations between HRV indices and clinical variables were examined, and multiple regression analysis was performed to identify independent predictors of HRV reduction. Results: All patient groups demonstrated significantly reduced HRV compared to controls, with diabetes mellitus showing the most profound impairment (56.5% reduction in SDNN, p<0.001), followed by CAD, hypertension, and COPD. Characteristic patterns included reduced overall HRV, impaired parasympathetic modulation (78.4% reduction in HF power in diabetes), relative sympathetic predominance (highest LF/HF ratio in COPD: 1.72±0.48), decreased complexity (lowest entropy in diabetes), and blunted circadian variations. Disease duration, glycemic parameters, inflammatory markers, and cardiac stress indicators correlated significantly with HRV reduction. Multiple regression identified disease type, age, disease duration, and glycemic control as independent predictors of autonomic dysfunction. Conclusion: Distinct autonomic profiles exist across different chronic diseases, reflecting disease-specific pathophysiological mechanisms with important implications for risk stratification and targeted interventions. Integration of HRV assessment into clinical evaluation of chronic disease patients could enhance early detection of autonomic dysfunction and guide personalized therapeutic strategies.

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Heart Rate Variability and Autonomic Control
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