Enhanced detection of abnormalities in heart rate variability and dynamics by 7-day continuous ECG monitoring

Annals of noninvasive electrocardiology: the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc

article

Junichiro Hayano MD, PhD¹  Emi Yuda DEng, PhD¹ 

[1] Heart Beat Science Lab, Co., Ltd.;Nagoya City University;Center for Data-driven Science and Artificial Intelligence, Tohoku University

关键词: heart rate dynamics;    heart rate variability;    Holter ECG;    long-term ECG monitoring;    day-to-day variation;    intraweek variation;   

DOI  :  10.1111/anec.12897

来源: Wiley

【 摘 要 】

Background The analysis of heart rate variability (HRV) and heart rate (HR) dynamics by Holter ECG has been standardized to 24 hs, but longer-term continuous ECG monitoring has become available in clinical practice. We investigated the effects of long-term ECG on the assessment of HRV and HR dynamics. Methods Intraweek variations in HRV and HR dynamics were analyzed in 107 outpatients with sinus rhythm. ECG was recorded continuously for 7 days with a flexible, codeless, waterproof sensor attached on the upper chest wall. Data were divided into seven 24-h segments, and standard time- and frequency-domain HRV and nonlinear HR dynamics indices were computed for each segment. Results The intraweek coefficients of variance of HRV and HR dynamics indices ranged from 2.9% to 26.0% and were smaller for frequency-domain than for time-domain indices, and for indices reflecting slower HR fluctuations than faster fluctuations. The indices with large variance often showed transient abnormalities from day to day over 7 days, reducing the positive predictive accuracy of the 24-h ECG for detecting persistent abnormalities over 7 days. Conversely, 7-day ECG provided 2.3- to 6.5-fold increase in sensitivity to detect persistent plus transient abnormalities compared with 24-h ECG. It detected an average of 1.74 to 2.91 times as many abnormal indices as 24-h ECG. Conclusions Long-term ECG monitoring increases the accuracy and sensitivity of detecting persistent and transient abnormalities in HRV and HR dynamics and allows discrimination between the two types of abnormalities. Whether this discrimination improves risk stratification deserves further studies.

【 授权许可】

Unknown