Title Validity of spectral analysis based on heart rate variability from 1-minute or less ECG recordings.
Author Takahashi, Naomi; Kuriyama, Akira; Kanazawa, Hoshinori; Takahashi, Yoshimitsu; Nakayama, Takeo
Journal Pacing Clin Electrophysiol Publication Year/Month 2017-Sep
PMID 28594089 PMCID -N/A-
Affiliation + expend 1.Department of Health Informatics, Kyoto University School of Public Health, Kyoto, Japan.

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.

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