Literature DB >> 28594089

Validity of spectral analysis based on heart rate variability from 1-minute or less ECG recordings.

Naomi Takahashi1, Akira Kuriyama1, Hoshinori Kanazawa2, Yoshimitsu Takahashi1, Takeo Nakayama1.   

Abstract

BACKGROUND: To broaden the utility of heart rate variability (HRV) in clinical medicine and mass screening, results based on shorter electrocardiogram (ECG) recordings require validation with those based on standard 5-minute recordings. We investigated the association between HRV variables obtained from 5-minute ECGs with those obtained from ECGs shorter than 5 minutes.
METHODS: Twenty-two participants aged 20-69 years underwent 5-minute resting ECG recordings in the supine position with natural breathing. Spectral analysis using MemCalc method was performed to calculate high-frequency (HF, which required at least 10 seconds) and low-frequency (LF, which required at least 30 seconds) components. Participants were not strictly preconditioned as in previous experimental studies in order to simulate a setting similar to that of a general health checkup. Associations of each variable between the 5-minute ECG recordings and those for shorter recordings were examined by Pearson's correlation coefficients and Bland-Altman plots.
RESULTS: HF and LF components were log-transformed based on their distributions. Correlation coefficients between 5-minute data and shorter recordings in the supine position with natural breathing ranged from 0.80 to 0.91 (HF by 10-second recording, 0.80; LF by 30-second recording, 0.83, respectively). Bland-Altman plots showed that gaps between the values from both methods slightly increased as the HF and LF component values increased.
CONCLUSIONS: Although slight proportional errors were possible, values from standard 5-minute and shorter recordings in the supine position were strongly correlated. Our findings suggest that shorter ECG data without strict preconditioning can be reliably used for spectral analysis.
© 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  autonomic nervous system; electrocardiography; heart rate variability; high frequency; low frequency

Mesh:

Year:  2017        PMID: 28594089     DOI: 10.1111/pace.13138

Source DB:  PubMed          Journal:  Pacing Clin Electrophysiol        ISSN: 0147-8389            Impact factor:   1.976


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