What question did this study set out to answer?

To develop and evaluate a computational method for identifying and characterizing ultradian cycles in heart rate and heart rate variability from overnight electrocardiographic recordings.

October 1, 2006Biomedical Engineering / Biomedizinische Technik

Circadian and ultradian rhythms in heart rate variability

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Why the study?

Can ultradian patterns of heart rate variability be quantified using a curve-fitting algorithm from overnight ECGs?

Population

113 subjects, aged 58+/-10 years (65 male, 48 female), including patients with and without severe sleep apnea.

Design

Cross-sectional

Follow-up

overnight

Authors

PSPhyllis K. SteinElectrophysiology PDPeter P. DomitrovichCleveland Clinic ELEric J. LundequamUniversity of Washington

Discussion

Member takes

Implication

Variable ultradian HRV patterns warrant no clinical adoption; hypothesis-generating for autonomic rhythm research.

Key Points

To develop and evaluate a computational method for identifying and characterizing ultradian cycles in heart rate and heart rate variability from overnight electrocardiographic recordings.
Analyzed overnight polysomnographic ECGs from 113 subjects (aged 58 ± 10 years; 65 male, 48 female) divided into 2-minute normal-to-normal interbeat intervals.
Calculated heart rate, SDNN2, high-frequency power, and low-to-high frequency power ratios using a MATLAB curve-fitting algorithm to quantify cyclic patterns across age, sex, sleep apnea severity, and sleep efficiency groups.
Ultradian cyclic patterns varied substantially across distinct heart rate variability parameters, indicating that no single index can serve as a surrogate marker for another.
Parameter variations differed across subgroups categorized by age, sex, sleep apnea status, and sleep efficiency, though no individual marker showed consistent alterations across all clinical comparisons.

Structured PICO

Can ultradian patterns of heart rate variability be quantified using a curve-fitting algorithm from overnight ECGs?

Population

113 subjects, aged 58+/-10 years (65 male, 48 female), including patients with and without severe sleep apnea.

Intervention

Curve-fitting algorithm developed in MatLab to identify cyclic patterns of HR/HRV from overnight polysomnographic ECGs.

Outcome

Ultradian patterns of HR/HRV indices (HR, SDNN2, high-frequency power, LF/HF ratio)surrogate

Quantification of ultradian patterns of heart rate variability is feasible and reveals that each parameter has its own distinct rhythm, providing potential new insights into autonomic physiology.

Cite This Study

Stein et al. (2006) studied this question.

synapsesocial.com/papers/6a73e9cc0e7fa2a8810dd9d1 https://doi.org/10.1515/bmt.2006.026

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Circadian and ultradian rhythms in heart rate variability

Discussion

Member takes

Implication

Key Points

Structured PICO

Cite This Study

Circadian and ultradian rhythms in heart rate variability

Discussion

Member takes

Implication

Key Points

Structured PICO

Cite This Study

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