Comparison of Fast Fourier Transform and Autoregressive Spectral Analysis for the Study of Heart Rate Variability in Diabetic Patients

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Comparison of Fast Fourier Transform and Autoregressive Spectral Analysis for the Study of Heart Rate Variability in Diabetic Patients International Journal of Cardiology 104 (2005) 307–313 www.elsevier.com/locate/ijcard Comparison of fast Fourier transform and autoregressive spectral analysis for the study of heart rate variability in diabetic patients Denis ChemlaT, Jacques Young, Fabio Badilini, Pierre Maison-Blanche, He´le`ne Affres, Yves Lecarpentier, Philippe Chanson Service de Physiologie Cardio-Respiratoire and Service d’Endocrinologie, Centre Hospitalo-Universitaire de Biceˆtre, Assistance Publique-Hopitaux de Paris, Universite´ Paris Sud 11, 78 rue du Ge´ne´ral Leclerc, 94 275 Le Kremlin Biceˆtre, France Unite´ Propre de l’Enseignement Supe´rieur 2705, Universite´ Paris-Sud 11, 92 141 Clamart, France Received 8 June 2004; received in revised form 13 September 2004; accepted 7 December 2004 Available online 21 February 2005 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 (49F12 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-hb100 ms and b50 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 (F5%) 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. D 2005 Elsevier Ireland Ltd. All rights reserved. Keywords: Heart rate; Autonomic tone; Autonomic neuropathy 1. Introduction The critical evaluation of HRV tests is therefore important if one considers: i) the high incidence of diabetes in the Cardiovascular autonomic neuropathy is a complication normal population; ii) the high incidence (~20%) of of diabetes which results from damage to the autonomic abnormal cardiovascular autonomic function in diabetes; nerve fibers that innervate the heart and blood vessels, thus and iii) the association between impaired HRVand increased leading to decreased heart rate variability (HRV) and risk of life-threatening cardiovascular events in these abnormal blood pressure control. Indexes of HRV are useful patients [7,16,35]. to detect the early impairment in autonomic tone at a time Two HRV methods are most often applied, namely when dysautonomia is not yet clinically patent [6,15,35]. bedside tests and the 24-h ambulatory electrocardiogram. The complete battery of classic autonomic tests is of great value but is long to perform and requires good cooperation T Corresponding author. Tel.: +331 45 21 25 63; fax: +331 45 21 37 78. from the patient, and it only examines short-term HRV in E-mail address: [email protected] (D. Chemla). the time-domain [16]. As the 24-h ambulatory ECG 0167-5273/$ - see front matter D 2005 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.ijcard.2004.12.018 308 D. Chemla et al. / International Journal of Cardiology 104 (2005) 307–313 examines both short-term and long-term HRV in both the ous system status were assessed by a physician unaware time- and frequency-domain, this simple and sensitive after the HRV results. Sixteen patients had peripheral method is increasingly used in diabetic patients [5]. The neuropathy and four patients had clinical signs of recommendation to use standardized duration of recordings dysautonomia. for HRV assessment has been proposed to enable comparisons of research studies [34]. The 24-h standard 2.2. Data acquisition and analysis deviation of normal RR intervals (SDNN) provides a simple and sensitive scale of cardiovascular risk, while the Ambulatory electrocardiographic recordings were spectral analysis of HRV over 5 min helps to quantify the acquired with a dual-lead analog Holter recorder (SEER, sympathovagal balance alterations which play an important Marquette-Helige, GE Medical Systems, Velizy, France). role in the pathophysiology and prognosis of the disease Holter was positioned in the morning. A 10-min resting [23,25,34]. period was performed at the onset of the recording period In the frequency-domain, HRV is described as the sum of in all patients. In a subset of twelve patients, a 10-min elementary oscillatory components defined by their fre- resting period was also performed at the end of the quency and amplitude (power). Physiological mechanisms recording period in order to test the day-to-day reprodu- responsible for power components cannot be considered cibility of the measurements. Patients were instructed to stationary during the 24-h period, and short-term analyses behave in a normal manner during 24 h. Analog data were under controlled conditions are therefore recommended (i.e., digitized at 200 Hz and edited by a cardiologist on a Mars 5 min at rest) [34]. Two spectral methods can be used, 8000 Laser Holter station (Marquette-Helige, GE Medical namely the fast Fourier transform (FFT) [2] and the Systems, Velizy, France). The validation procedure con- autoregressive (AR) methods [19,25,28]. Spectral frequency sisted of beat labeling and tagging of noisy regions. Both components are either integrals of power spectrum density ECG raw data and annotation were transferred to a over specific bands (FFT) or components automatically personal computer for dedicated HRV analysis [3,4].In determined by autoregressive algorithms (AR). As recently an attempt to rule out the hypothesis that potential pointed out, a study comparing the two methods is differences between FFT and AR results would be due to important for the proper interpretation of spectral data in technical limitations or specific features of the Holter terms of physiologic and pathologic processes [22], and recordings, only sinus rhythm, high-quality recordings previous studies have compared the two methods in healthy were selected for entering the final analysis. Exclusion subjects [3,29] and in hypertensives [4]. In diabetic patients, criteria related to recording characteristics included: noisy both the FFT method [8–11,20,21,36] and the AR method regions with absence of at least one good quality lead [6,7,13,31,32] have been used, but up to now no study has (n=11), N2% ectopic beats or ectopic beats occurring compared the results of the two methods. during the 10-min resting period (n=9), a duration b24 h The aim of the present study was to compare short-term (n=1), previously unrecognized atrioventricular block spectral HRV measurements obtained by FFT and AR (n=1), and movements during the resting period (n=1). methods in diabetic patients. We tested whether or not the two methods provide interchangeable estimates of spectral 2.3. Heart rate and heart rate variability HRV in diabetic patients. Time- and frequency-domain HRV variables were calculated as previously described [3,4].Time-domain 2. Material and methods variables included: mean sinus heart rate (HR), average RR interval (NN), standard deviation of the RR intervals 2.1. Study population (SDNN), percentage of normal consecutive RR intervals differing by N50 ms (pNN-50), and root mean of squared The subjects included in this prospective study were successive differences (RMSSD). From a theoretical point diabetic patients hospitalized in our diabetes care unit. of view, spectral analysis requires rigorous stationary Informed consent was obtained for each patient and the conditions which are unknown to biology and medical study protocol conformed to the ethical guidelines of the science [23]. Short-term analyses under controlled condi- 1975 Declaration of Helsinki as reflected in a priori tions are therefore recommended, and it is now admitted that approval by the Institution’s human research committee. the analysis of 5-min resting ECG offers a reasonable, Patients with known cardiovascular diseases or rhythm practical compromise [22,34]. Editing of the tachograms disturbances were excluded from the study and all patients may also help eliminate the runs with step changes of major were free of any cardiovascular medication. Thirty trends in the tachogram [23,34], as performed in the present diabetic subjects aged 49F12 years, 19 men and 11 study. The FFT power spectra were calculated with the women, 18 with insulin-dependent type 1 diabetes and 12 method of average periodogram, also called the Walch with non-insulin dependent type 2 diabetes, were recruited periodogram, as previously described [3,4] and recommen- consecutively. Neurological status and autonomous nerv- ded [34]. The AR power spectra were obtained as D. Chemla et al. / International Journal of Cardiology 104 (2005) 307–313 309 Table 1 reference T0 period, namely T0À15 sec, T0 and T0+15 Time domain heart rate variability parameters at rest over a 5-min period sec. Coefficient of variation was calculated as [(S.D./ (n=30) mean)Â100]. The measurements at onset and end of the F Mean S.D. Range recording (n=12) were compared using paired t test and NN (ms) 822F127 600–1120 calculation of the mean bias. A P valueb0.05 was F SDNN (ms) 31 24 5–125 considered statistically significant.
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