Very Low Frequency Power of Heart Rate Variability is a Powerful Predictor of Clinical Prognosis in Patients With Congestive Heart Failure

Hadase, Mitsuyoshi; Azuma, Akihiro; Zen, Kan; Asada, Satoshi; Kawasaki, Tatsuya; Kamitani, Takeshi; Kawasaki, Shingo; Sugihara, Hiroki; Matsubara, Hiroaki

doi:10.1253/circj.68.343

Cited by 171 publications

(127 citation statements)

References 38 publications

(30 reference statements)

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“…15,16 HRV obtained from Holter monitoring as indices of ANA is known to be reproducible and reliable measure. 21,[23][24][25] Longitudinal studies are expected to show the features of age-related change more precisely and in more detail than cross-sectional studies, especially in a small population. Thus, to characterize the age-related changes of ANA in elderly patients, we analyzed the longitudinal age-related changes in HR, HRV, and their circadian rhythms over 15 years in 15 healthy elderly patients at a mean age of 70 years, and assessed the age-related changes in the dynamics of ANA in the morning.…”

Section: Discussionmentioning

confidence: 99%

Long-Term Follow-up of the Circadian Rhythm of Heart Rate and Heart Rate Variability in Healthy Elderly Patients

Tasaki

Serita

Ueyama

et al. 2006

Circ J

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Section: Discussionmentioning

confidence: 99%

Long-Term Follow-up of the Circadian Rhythm of Heart Rate and Heart Rate Variability in Healthy Elderly Patients

Tasaki

Serita

Ueyama

et al. 2006

Circ J

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“…However, no study has examined whether anemia is associated with HRV in patients who have heart disease. Several studies have shown that low HRV independently predicts sudden cardiac death and overall mortality in patients who have heart disease, [5][6][7][8][9][10] suggesting that low HRV may contribute to the adverse cardiac outcomes associated with anemia. We hypothesized that anemia is associated with an imbalance of cardiac autonomic tone as measured by low HRV in patients who have coronary heart disease (CHD).…”

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confidence: 99%

“…This finding is in accordance with previous studies that have shown depressed very-low frequency, lowfrequency, and wideband frequency power but not high-frequency power to be predictive of ventricular tachycardia and cardiac events. 8,9,19 Low-frequency power is believed to reflect the modulation of sympathetic and parasympathetic tones, 16 whereas high-frequency power is believed to reflect pure parasympathetic tone. 17 Although the precise physiologic meaning of very-low-frequency power is not completely understood, it has been suggested that very-lowfrequency power is influenced by thermoregulation, fluctuation in the renin-angiotensin axis, function of peripheral chemoreceptors, and physical activity, 9 all of which may be associated with adverse cardiovascular outcomes.…”

mentioning

confidence: 99%

“…8,9,19 Low-frequency power is believed to reflect the modulation of sympathetic and parasympathetic tones, 16 whereas high-frequency power is believed to reflect pure parasympathetic tone. 17 Although the precise physiologic meaning of very-low-frequency power is not completely understood, it has been suggested that very-lowfrequency power is influenced by thermoregulation, fluctuation in the renin-angiotensin axis, function of peripheral chemoreceptors, and physical activity, 9 all of which may be associated with adverse cardiovascular outcomes. Proportion of participants who had HRV in the lowest quartile according to presence (hemoglobin ≤ 12 g/dl, n = 90) (dark gray bars) and absence (n = 784) (light gray bars) of anemia.…”

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confidence: 99%

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Relation of Anemia to Low Heart Rate Variability in Patients With Coronary Heart Disease (from the Heart and Soul Study)

Gehi¹,

Ix²,

Shlipak³

et al. 2005

The American Journal of Cardiology

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We examined the association between anemia (hemoglobin ≤12 g/dl) and 6 indexes of heart rate variability (HRV) as measured by 24-hour ambulatory electrocardiography in a cross-sectional study of 874 outpatients who had stable coronary heart disease. Of 90 participants who had anemia, 29% to 41% had low HRV, defined as the lowest quartile of each HRV index, compared with 23% to 25% of the 784 participants who did not have anemia (comparison p values <0.05 for all HRV indexes except high-frequency power). With the exception of high-frequency power, each 1 g/dl decrease in hemoglobin was associated with increased odds of having low HRV. This association remained strong after adjustment for potential confounding variables, including ischemia, left ventricular mass, left ventricular ejection fraction, and diastolic dysfunction. Thus, anemia is associated with low HRV in ambulatory patients who have stable coronary heart disease. Low HRV could potentially mediate the association of anemia with increased cardiac risk.Several small studies have associated anemia due to vitamin B12 deficiency, 1,2 thalassemia, 3 and sickle cell anemia 4 with low heart rate variability (HRV). However, no study has examined whether anemia is associated with HRV in patients who have heart disease. Several studies have shown that low HRV independently predicts sudden cardiac death and overall mortality in patients who have heart disease, [5][6][7][8][9][10] suggesting that low HRV may contribute to the adverse cardiac outcomes associated with anemia. We hypothesized that anemia is associated with an imbalance of cardiac autonomic tone as measured by low HRV in patients who have coronary heart disease (CHD). To determine whether anemia is associated with HRV, we measured hemoglobin and HRV in a cross-sectional study of 874 ambulatory patients who had stable CHD.The Heart and Soul Study is a prospective cohort study of psychosocial factors and health outcomes in patients who have CHD. Details regarding our methods have been previously published. 11 Outpatients who had documented CHD were recruited from 2 veterans affairs medical centers (San Francisco VA Medical Center, San Francisco, California, and the VA Palo Alto Health Care System, Palo Alto, California), 1 university medical center (University of California, San Francisco, California), and 9 public health clinics in the Community Health Network of San Francisco. Patients were eligible to participate if they had ≥1 of the following: a history of myocardial infarction, angiographic evidence of ≥50% stenosis in ≥1 coronary vessel, previous evidence of exercise-induced ischemia by treadmill or nuclear testing, a history of coronary revascularization, or a diagnosis of CHD by an internist or cardiologist (based on NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript a positive angiographic or exercise treadmill test result in >98% of cases). Patients were excluded if they were unable to walk 1 block or were planning to move from the local area within 3 years.Betw...

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“…In [19], frequency domain parameters, namely Very Low Frequency (VLF), Low Frequency (LF), High Frequency (HF), total power and the ratio of LF to HF powers, are computed from the HRV signals. The VLF power is found to be an independent risk predictor in CHF patients.…”

Section: Introductionmentioning

confidence: 99%

Use of Accumulated Entropies for Automated Detection of Congestive Heart Failure in Flexible Analytic Wavelet Transform Framework Based on Short-Term HRV Signals

Kumar

Pachori

Acharya

2017

Entropy

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Abstract:In the present work, an automated method to diagnose Congestive Heart Failure (CHF) using Heart Rate Variability (HRV) signals is proposed. This method is based on Flexible Analytic Wavelet Transform (FAWT), which decomposes the HRV signals into different sub-band signals. Further, Accumulated Fuzzy Entropy (AFEnt) and Accumulated Permutation Entropy (APEnt) are computed over cumulative sums of these sub-band signals. This provides complexity analysis using fuzzy and permutation entropies at different frequency scales. We have extracted 20 features from these signals obtained at different frequency scales of HRV signals. The Bhattacharyya ranking method is used to rank the extracted features from the HRV signals of three different lengths (500, 1000 and 2000 samples). These ranked features are fed to the Least Squares Support Vector Machine (LS-SVM) classifier. Our proposed system has obtained a sensitivity of 98.07%, specificity of 98.33% and accuracy of 98.21% for the 500-sample length of HRV signals. Our system yielded a sensitivity of 97.95%, specificity of 98.07% and accuracy of 98.01% for HRV signals of a length of 1000 samples and a sensitivity of 97.76%, specificity of 97.67% and accuracy of 97.71% for signals corresponding to the 2000-sample length of HRV signals. Our automated system can aid clinicians in the accurate detection of CHF using HRV signals. It can be installed in hospitals, polyclinics and remote villages where there is no access to cardiologists.

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Very Low Frequency Power of Heart Rate Variability is a Powerful Predictor of Clinical Prognosis in Patients With Congestive Heart Failure

Cited by 171 publications

References 38 publications

Long-Term Follow-up of the Circadian Rhythm of Heart Rate and Heart Rate Variability in Healthy Elderly Patients

Long-Term Follow-up of the Circadian Rhythm of Heart Rate and Heart Rate Variability in Healthy Elderly Patients

Relation of Anemia to Low Heart Rate Variability in Patients With Coronary Heart Disease (from the Heart and Soul Study)

Use of Accumulated Entropies for Automated Detection of Congestive Heart Failure in Flexible Analytic Wavelet Transform Framework Based on Short-Term HRV Signals

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