From Beat to Risk: How Heart Rate Variability Predicts Arrhythmias in Type 2 Diabetes

TL;DR

Heart rate variability in type 2 diabetes patients can predict arrhythmia risk, offering a non-invasive way to detect autonomic dysfunction.

Contribution

This paper highlights HRV as a novel, non-invasive predictor of arrhythmia risk in type 2 diabetes patients.

Findings

Reduced HRV indices like SDNN and RMSSD indicate autonomic dysfunction in type 2 diabetes.

Nonlinear HRV indices provide additional prognostic value beyond traditional analyses.

Lower HRV correlates with severe autonomic neuropathy and poor diabetes control.

Abstract

Type 2 diabetes mellitus is associated with major cardiovascular complications, including cardiac autonomic neuropathy, which contributes to sympathetic–parasympathetic imbalance and increases susceptibility to arrhythmias and sudden cardiac death. Heart rate variability, assessed through R–R intervals on electrocardiography and 24 h Holter monitoring, represents a sensitive, non-invasive marker of autonomic dysfunction and arrhythmogenic risk. In patients with type 2 diabetes mellitus, chronic hyperglycaemia, oxidative stress, and metabolic inflammation lead to early impairment of the autonomic nervous system, manifested by consistent reductions in SDNN, RMSSD, pNN50, total power, and the high-frequency component, indicating diminished parasympathetic tone and sympathetic predominance. Nonlinear HRV indices demonstrate a loss of complexity and fractal organisation, providing additional prognostic value beyond conventional time- and frequency-domain analyses. Reduced HRV correlates with the severity of cardiac autonomic neuropathy, duration of diabetes, and poor glycaemic control, identifying patients with increased arrhythmogenic vulnerability. HRV analysis enables prediction of arrhythmic risk, facilitating the identification of high-risk individuals and guiding personalised interventions. The integration of HRV assessment into routine clinical practice may improve the early detection of subclinical autonomic neuropathy and optimise cardiovascular risk stratification and management in patients with type 2 diabetes mellitus.

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