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. 2024 Jul-Sep;14(3):169-173.
doi: 10.4103/ijabmr.ijabmr_238_24. Epub 2024 Aug 24.

Exploring Ultra-short Heart Rate Variability Metrics in Patients with Diabetes Mellitus: A Reliability Analysis

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Exploring Ultra-short Heart Rate Variability Metrics in Patients with Diabetes Mellitus: A Reliability Analysis

Shival Srivastav et al. Int J Appl Basic Med Res. 2024 Jul-Sep.

Abstract

Objectives: Ultra-short heart rate variability (HRV) metrics represent autonomic tone parameters derived using small epochs of interbeat interval data. These measures have risen in popularity with the advent of wearable devices that can capture interbeat interval data using electrocardiography (ECG) or photoplethysmography. Autonomic neuropathy in diabetes mellitus (DM) is well established, wherein 5-min HRV is conventionally used. Ultra-short measures have the potential to serve as markers of reduced autonomic tone in this patient population.

Methods: Data of patients with Type I and Type II DM who had presented to our laboratory for autonomic neuropathy assessment were chosen for analysis. One-minute and 2-min epochs were chosen from 5 min of ECG data using standard software. Time domain, frequency domain, and nonlinear measures were computed from 1 to 2 min epochs, and reliability was compared with measures derived from 5-min HRV using intraclass correlation coefficients (ICCs).

Results: Data of 131 subjects (79 males, 52 females; mean age = 53.3 ± 12.16 years) were analyzed. All ultra-short HRV measures derived from 1 min to 2 min data showed good to excellent reliability (median ICC values ranging from 0.83 to 0.94) when compared with 5-min metrics. The notable exception was very low frequency (VLF) power, which showed poor reliability (median ICC = 0.43).

Conclusions: Ultra-short HRV metrics derived from 1 to 2 min epochs of ECG data can be reliably used as predictors of autonomic tone in patients with DM. VLF power is poorly reproducible in these small epochs, probably due to variability in respiratory rates. Our findings have implications for ultra-short HRV estimation using short epochs of ECG data.

Keywords: Autonomic nervous system; autonomic neuropathy; diabetes complications; diabetes mellitus; electrocardiography; heart rate.

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Conflict of interest statement

There are no conflicts of interest.

Figures

Figure 1
Figure 1
Division of electrocardiography (ECG) signal into epochs for analysis. Representative record for 5-min Lead II ECG signal used for epoch-based heart rate variability (HRV) analysis. X axis represents time and Y axis represents signal amplitude. The ECG signal was divided into 5 epochs of 1 min each (a1–e1, ranging from 0 to 1 min, 1 to 2 min, 2 to 3 min, 3 to 4 min, and 4 to 5 min, respectively; shown in upper panel). For the analysis of 2-min epochs, the ECG signal was divided into epochs a2–d2 (ranging from 0 to 2 min, 1 to 3 min, 2 to 4 min, and 3 to 5 min, respectively; shown in lower panel). The dotted rectangle depicts a representative segment of ECG signal whose magnified view is shown in the dialogue box. These segment notations (a1–e1 and a2–d2) were put into validated software for randomization and a series was generated for HRV analysis of the study subjects

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