Circadian and ultradian rhythms in heart rate variability

Aim: Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian...

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Published inBiomedizinische Technik Vol. 51; no. 4; pp. 155 - 158
Main Authors Stein, Phyllis K., Domitrovich, Peter P., Lundequam, Eric J., Duntley, Stephen P., Freedland, Kenneth E., Carney, Robert M.
Format Journal Article
LanguageEnglish
Published Germany Walter de Gruyter 01.10.2006
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ISSN0013-5585
1862-278X
DOI10.1515/BMT.2006.026

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Abstract Aim: Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV. Materials and methods: HR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58±10 years (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency. Results: Ultradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons. Conclusion: Each HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology.
AbstractList Aim: Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV. Materials and methods: HR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58±10 years (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency. Results: Ultradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons. Conclusion: Each HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology.
Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV.AIMHeart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV.HR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58+/-10 years (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency.MATERIALS AND METHODSHR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58+/-10 years (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency.Ultradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons.RESULTSUltradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons.Each HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology.CONCLUSIONEach HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology.
Aim: Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV.Materials and methods: HR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58A-10ANByears (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency.Results: Ultradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons.Conclusion: Each HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology.
Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV. HR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58+/-10 years (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency. Ultradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons. Each HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology.
Author Duntley, Stephen P.
Domitrovich, Peter P.
Stein, Phyllis K.
Freedland, Kenneth E.
Carney, Robert M.
Lundequam, Eric J.
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Cites_doi 10.1146/annurev.med.50.1.249
10.1016/0013-4694(92)90009-7
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Snippet Aim: Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While...
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SubjectTerms Age Factors
Arrhythmias, Cardiac - physiopathology
Biological Clocks
Circadian Rhythm
Computer Simulation
Electrocardiography - methods
Female
Heart Conduction System - physiopathology
Heart Rate
heart rate variability
Humans
Male
Middle Aged
Models, Cardiovascular
Oscillometry - methods
Sex Factors
Sleep Apnea Syndromes - physiopathology
ultradian rhythms
Title Circadian and ultradian rhythms in heart rate variability
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