What question did this study set out to answer?

To investigate how heart rate variability (HRV) can predict arrhythmias in individuals with type 2 diabetes.

March 25, 2026Open Access

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

Key Result

Reduced heart rate variability in patients with type 2 diabetes correlates with autonomic neuropathy and poor glycemic control, identifying individuals at increased risk for arrhythmias.

Key Points

To investigate how heart rate variability (HRV) can predict arrhythmias in individuals with type 2 diabetes.
Assessment of heart rate variability through R–R intervals and 24-hour Holter monitoring
Analysis of nonlinear HRV indices to evaluate autonomic dysfunction
Correlation of HRV with cardiac autonomic neuropathy and glycaemic control
Reduced HRV correlates with increased severity of cardiac autonomic neuropathy.
Chronic hyperglycaemia and oxidative stress lead to diminished parasympathetic tone.
HRV analysis identifies individuals at higher risk for arrhythmias, suggesting targeted interventions.

Structured PICO

Does heart rate variability assessment predict arrhythmias in patients with type 2 diabetes mellitus?

Population

Patients with type 2 diabetes mellitus

Intervention

Heart rate variability (HRV) assessment

Outcome

Arrhythmogenic risk and sudden cardiac death

Heart rate variability assessment serves as a sensitive, non-invasive marker to predict arrhythmic risk and autonomic dysfunction in patients with type 2 diabetes.

Main Result

Absolute Event Rate: 0% vs 0%

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.