The 2012 Biomedical Engineering International Conference (BMEiCON-2012)
Increased Sample Entropy in Atrial Fibrillation Relates to Cardiac Autonomic Dysfunction Determined by Heart Rate Variability: A Preliminary Study Rattapong Sungnoon, Sombat Muengtaweepongsa, Peerapong Kitipawong, Kesorn Suwanprasert Faculty of Medicine, Thammasat University (Rangsit Campus) Pathumthani, Thailand
[email protected] Abstract—Introduction: Atrial fibrillation (AF) is the most common cardiac arrhythmia associated with an increased risk of left atrial thrombosis as well as ischemic stroke. In this study, we have evaluated the characteristics of paroxysmal AF (PAF) and persistent AF using sample entropy (SampEn), a new biosignal parameter for determining degree of AF signal complexity in atrial activities extracted from surface ECG, including heart rate variability (HRV) to test the hypothesis that increased atrial signal irregularity in AF patients relates to cardiac autonomic dysfunction compared with control subjects. Methods: PAF patients with normal sinus rhythm (n = 12), persistent AF patients (n = 11), and control subjects (patient controls; n = 8, and healthy controls; n = 13) were recruited. The ECG recordings (sampling rate of 1000 Hz, 5-minute long) were performed, then standard short-term HRV and SampEn were analyzed by software algorithms. Results: SampEn values from lead V1 in patients with persistent AF were significantly higher than those in healthy controls (0.14±0.02 vs. 0.10±0.04). Although there was no SampEn difference between PAF patients and the other three groups, the PAF SampEn was in between persistent AF and control values. For HRV analysis, low-frequency to highfrequency (LF/HF) power ratio in both PAF and persistent AF patients were significantly decreased compared to healthy controls (0.75±0.52 and 0.44±0.09 vs. 1.56±0.77, respectively). Conclusion: There was an impairment of cardiac autonomic function in both PAF (with normal sinus rhythm) and persistent AF patients consistent with an increased atrial signal irregularity. Index Terms—Atrial fibrillation, sample entropy, heart rate variability.
I. INTRODUCTION Atrial fibrillation (AF) is the most common cardiac arrhythmia associated with an increased risk of ischemic stroke. In Thailand, the prevalence of AF is 5 per 100,000 populations [1], and the mortality risk due to systemic embolization including ischemic stroke increases to 1.5-1.9 compared to healthy populations in the same age group [2]. Meanwhile, stroke incidence increases continuously worldwide including Thailand [3], and approximately 15-21%
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Tachapong Ngarmukos Faculty of Medicine Ramathibodi Hospital, Mahidol University Bangkok, Thailand
of stroke patients have AF [4]. Currently, it has been still unclear about mechanisms causing AF, nonetheless one of the widely accepted theories of AF genesis associates with an inhomogeneity of electrical signals in atrial chamber. These signals propagate in an irregular pattern called multiple reentry which consists of several reentrant circuits, and a chance of these reentrant circuits to convert into normal sinus rhythm (NSR) is inversely proportional to the number of reentrant waves in atrial wall [5, 6]. Many researchers have explored the relationship between a regularity of AF electrical signal pattern (AF signal pattern organization) and the number of reentrant waves in atrial chamber in order to predict AF recurrence after treatment with direct current shock by external electrical cardioversion (ECV) as well as predict the behavior of paroxysmal AF (PAF). This could be done by direct atrial signal recording during cardiac catheterization, then specific algorithms, which may be non-linear analysis (sample entropy or SampEn) or frequency domain analysis (atrial fibrillatory rate) would further be used to transform the atrial signals to study AF pattern characterization [2, 5, 6]. The autonomic nervous system plays an important role in cardiac control loops, which comprises sympathetic and parasympathetic innervation. Sympathetic nerve fibers are located subepicardially and distribute homogenously along the routes of the major coronary arteries, whereas the parasympathetic or vagal nerve is subendocardial and distributes rather irregularly [7]. These neuroanatomic connections between the brain and the heart provide links that allow cardiac arrhythmias to occur both experimentally and clinically, for example, stroke, epilepsy, and environmental stress [8]. Therefore, the insights in these brain-heart interactions may play a major role in treatment and prevention of both PAF as well as persistent AF. It has been known that heart rate variability (HRV) determines cardiac autonomic function. The analysis of HRV provides useful information about disturbances in autonomic regulation in several cardiac diseases including AF [9, 10]. The reduced HRV was found in chronic AF [11], whereas increased
HRV spectral parameter, i.e., low-frequency to high-frequency power (LF/HF) ratio, correlated to early recurrence of AF after ECV [12]. Moreover, the application of surface ECG signal processing techniques, especially SampEn, representing the degrees of AF signal irregularity, has currently provided a new determinant for AF treatment in many studies, for example, the use of SampEn for predicting AF recurrence after ECV [5, 6] as well as prediction of the behavior of PAF [2]. In this study, we aim to evaluate HRV, and SampEn in both types of AF patients (PAF with NSR and persistent AF) compared to those in control subjects to test the hypothesis that impairment of cardiac autonomic control relates to increased AF signal irregularity. II. METHODS A.
Study Patients This study enrolled a total of 44 subjects including 12 PAF patients with NSR episode, 11 persistent AF patients, 8 patient controls (control patients without AF) and 13 healthy controls (control healthy subjects). Subject or patient care followed appropriate standard of Human Ethics Committee, Faculty of Medicine, Thammasat University. B.
Data Acquisition and Signal Analysis The ECG recordings were acquired with a sampling rate of 1000 Hz using lead II and V1 for 5-minute long duration within 24 hours after admission or at the OPD visit. All recordings were made in similar conditions with subjects maintained at rest and in a comfortable position. The ECG recording files were further tested in a blinded fashion. All subjects gave their written informed consent to participate in the study. The study was approved by the local Ethical Committee. C.
Heart Rate Variability The standard procedure and interpretation of HRV analyses were defined in 1996 (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996) [13]. HRV is categorized into high, low, and very low frequency power ranges or HF, LF, and VLF, respectively. HF is equivalent to the respiratory sinus arrhythmia and represents vagal control of the heart. LF is a joint contribution by both vagal and sympathetic nerves, such that the LF/HF ratio is considered to reflect sympathovagal balance [14]. The physiological explanation of the VLF component is much less defined and the existence of a specific attributable physiologic process may even be questioned [14]. Most studies of HRV have used 24 hour Holter recorded ECGs, which are often not feasible for wide scale epidemiological studies, and may be unnecessary. Therefore, five minute recordings or standard short-term HRV analysis has been proved for its stability and consistency with time [15]. In this study, we used specific standard program software for analysis of short-term HRV. D.
Sample Entropy
SampEn examines a time series for similar epochs and assigns a non-negative number to the sequence, with larger values corresponding to more irregularity in the data [2]. Two input parameters, the run length m and the tolerance window r, must be specified for entropy to be computed. SampEn (m, r) is the negative logarithm of the conditional probability that two sequences similar during m points remain similar at the next point, in which recent study has showed that the optimal m and r values are m = 2 and r = 0.25 [2]. According to the analysis of surface ECG from AF patients, the most prominent atrial signals in lead V1 are usually selected [16]. In this study, at least 1-minute long ECGs from lead V1 were proceeded to extract TQ interval or atrial activity by cancellation of QRS-T complex using software algorithms developed by our group, thereafter the SampEn analysis was accomplished from the 10-second long consecutive TQ interval. E.
Statistical Analysis Values were expressed as mean + standard deviation, and compared between groups using unpaired Student’s t-test for continuous variables and χ2 test or Fisher’s exact test for categoric variables. A value of P < 0.05 was considered statistically significant. III. RESULTS The demographic data among PAF, persistent AF patients, and control subjects are presented in Table I. In spite of the differences between control healthy subjects and the other three groups, most of the parameters among the latter, i.e., in PAF, persistent AF, and control (non-AF) patients were not different. TABLE I. COMPARISON OF THE BASELINE CHARACTERISTICS OF PATIENTS AND CONTROLS Paroxysmal AF patients (N = 12)
Persistent AF patients (N = 11)
Patient controls (N = 8)
Healthy controls (N = 13)
Age, years
74 + 9.0*
66 + 11.7*
68 + 13.0*
21 + 0.4
Female, n (%)
6 (50)
5 (45)
3 (38)
3 (23)
CHF, n (%)
1 (8)
4 (36)*
1 (12)
0 (0)
HT, n (%)
9 (75)*
5 (45)*
7 (88)*
0 (0)
DM, n (%)
4 (33)*
0 (0)§
3 (38)*
0 (0)
Vascular diseases, n (%)
0 (0)
0 (0)
2 (25)
0 (0)
Previous stroke, n (%)
11 (92)*
7(64)*
6(75)*
0 (0)
* P
