Autonomic regulation and cardiovascular risk: how comorbidities shape holter ECG metrics in ischemic cardiomyopathy

Abstract Background Cardiovascular diseases often coexist with various comorbid conditions such as diabetes, hypertension, and chronic kidney disease. These comorbidities can significantly impact autonomic regulation, myocardial function, and electrical conduction, potentially altering electrocardiographic (ECG) parameters recorded through ambulatory Holter monitoring. Holter ECG is a valuable tool for detecting arrhythmias, heart rate variability (HRV) changes, and other electrophysiological alterations that may indicate an increased risk of adverse cardiac events. Purpose This study aims to investigate the impact of common comorbidities on key Holter ECG metrics in patients with ischemic cardiomyopathy, providing insights into their potential prognostic significance in clinical practice. Methods In this prospective study conducted from May 2023 to January 2024, we enrolled 120 consecutive patients diagnosed with chronic heart failure due to ischemic cardiomyopathy. Holter ECG recordings were analyzed to extract HRV parameters, with a particular focus on the triangular index, acceleration capacity (AC), and deceleration capacity (DC). Standard HRV metrics, including time-domain and frequency-domain indices, were also evaluated for comparison. Patients were stratified based on HRV parameter distributions, and statistical analyses were performed to determine associations between HRV metrics and comorbidities. Results Specific conditions such as renal dysfunction, lipid metabolism disorders, and diabetes show significant associations with HRV, particularly affecting DC and frequency-domain parameters. Reduced creatinine clearance is correlated with lower RMSSD (Spearman’sρ = -0,211; p = 0,012), PNN50, and HF (Spearman’s ρ = -0,207; p = 0,014). In terms of lipid metabolism, higher LDL cholesterol levels are negatively correlated with AC (Spearman’s ρ = -0,220; p = 0,009) and positively with DC. Among diabetic patients, RMSSD, PNN50, AC, and DC (p <0,001) are significantly reduced. Furthermore, LDL cholesterol is the only significant predictor of T-wave alternans, suggesting that hyperlipidemia may contribute to ventricular instability. These findings emphasize the role of metabolic and renal function in the autonomic regulation of CHF patients and suggest that DC may serve as a valuable marker for cardiovascular risk, particularly in individuals with diabetes and hyperlipidemia. Conclusions While most comorbidities have a limited impact on Holter ECG parameters, renal dysfunction, lipid metabolism disorders, and diabetes significantly affect HRV, particularly DC. Reduced renal function correlates with impaired autonomic regulation, while elevated LDL cholesterol and diabetes are linked to autonomic dysfunction and ventricular instability. DC emerges as a key marker of cardiovascular risk, highlighting the need for individualized assessment and targeted management in patients with ischemic cardiomyopathy.Correlations uric acid and LDL  Comparations diabetes