Comparison of fast Fourier transform and autoregressive spectral analysis for the study of heart rate variability in diabetic patients

Abstract

Introduction: Impaired heart rate variability (HRV) is associated with poor outcome in diabetic patients. The present prospective study compared spectral components of HRV obtained by either fast Fourier transform (FFT) or autoregressive (AR) analyses in diabetic patients.

Methods: Thirty patients (49+/-12 years; 11 F/19 M; 60% with insulin-dependent type 1 diabetes) underwent 24-h ambulatory electrocardiographic recordings which comprised a 10-min resting period at the onset (n=30) and end (n=12) of the monitoring. Spectral analysis was applied to 5-min sequences at rest, and the total power and power spectra integrated over the very low (VLF), low (LF), and high (HF) frequency bands were obtained.

Results: Fifteen patients had moderately depressed HRV and two patients had highly depressed HRV (standard deviation of the RR intervals over 24-h<100 ms and <50 ms, respectively). Both raw data and ln-transformed data were significantly different between FFT and AR. All spectra component were obtained in each patient using FFT. Using AR, the LF/HF ratio could not be estimated or was zero in 4 and 11 patients, respectively. The AR results were more sensitive than FFT results to minor changes (+/-5%) in the timing of the onset of analysis. The day-to-day reproducibility of FFT was better than that of AR. Finally, using FFT, the LF/HF ratio, LFnu, and HFnu were essentially redundant (nu=normalized units).

Conclusions: The spectral components of short-term HRV calculated by using the FFT and AR methods were not interchangeable and FFT analysis must be preferred in diabetic patients.