智能手表得出的心率变异性:与心血管疾病黄金标准的正面比较。

IF 3.9 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS European heart journal. Digital health Pub Date : 2023-03-23 eCollection Date: 2023-05-01 DOI:10.1093/ehjdh/ztad022
Fabian Theurl, Michael Schreinlechner, Nikolay Sappler, Michael Toifl, Theresa Dolejsi, Florian Hofer, Celine Massmann, Christian Steinbring, Silvia Komarek, Kurt Mölgg, Benjamin Dejakum, Christian Böhme, Rudolf Kirchmair, Sebastian Reinstadler, Axel Bauer
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引用次数: 0

摘要

目的:我们的目的是研究心血管疾病患者心率变异性(HRV)与黄金标准高分辨率心电图(ECG)得出的心率变异性之间的一致性:我们前瞻性地招募了104名急性ST段抬高型心肌梗死幸存者、129名缺血性脑卒中患者和30名对照组患者。所有受试者都在标准化条件下接受了 30 分钟的智能手表(Garmin vivoactive 4;Garmin Ltd,Olathe,KS,USA)PPG 信号和高分辨率(1000 Hz)心电图同步记录。时域和频域的心率变异测量值、非线性测量值以及减速能力(DC)都是根据以前公布的技术从这两种信号中计算出来的。智能手表和心电图心率变异标记之间的林氏一致性相关系数(ρc)被用来衡量诊断的准确性。在整个研究队列中,平均心率(ρc = 0.9998)、所有 5 分钟片段中正常到正常(NN)间隔平均值的标准偏差(SDANN;ρc = 0.9617)和极低频功率(VLF 功率;ρc = 0.9613)的一致性非常高。相比之下,去趋势波动分析(DF-α1;ρc = 0.5919)和相邻 NN 间隔差平方和的均方根(rMSSD;ρc = 0.6617)仅显示出中等程度的一致性:结论:与基于心电图的心率变异相比,智能手表得出的心率变异提供了一种实用的替代方法,在全局标记和表征低频成分的心率变异方面具有极佳的准确性。然而,对于主要评估短期变异性的心率变异标记,需要谨慎对待。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Smartwatch-derived heart rate variability: a head-to-head comparison with the gold standard in cardiovascular disease.

Aims: We aimed to investigate the concordance between heart rate variability (HRV) derived from the photoplethysmographic (PPG) signal of a commercially available smartwatch compared with the gold-standard high-resolution electrocardiogram (ECG)-derived HRV in patients with cardiovascular disease.

Methods and results: We prospectively enrolled 104 survivors of acute ST-elevation myocardial infarction, 129 patients after an ischaemic stroke, and 30 controls. All subjects underwent simultaneous recording of a smartwatch (Garmin vivoactive 4; Garmin Ltd, Olathe, KS, USA)-derived PPG signal and a high-resolution (1000 Hz) ECG for 30 min under standardized conditions. HRV measures in time and frequency domain, non-linear measures, as well as deceleration capacity (DC) were calculated according to previously published technologies from both signals. Lin's concordance correlation coefficient (ρc) between smartwatch-derived and ECG-based HRV markers was used as a measure of diagnostic accuracy. A very high concordance within the whole study cohort was observed for the mean heart rate (ρc = 0.9998), standard deviation of the averages of normal-to-normal (NN) intervals in all 5min segments (SDANN; ρc = 0.9617), and very low frequency power (VLF power; ρc = 0.9613). In contrast, detrended fluctuation analysis (DF-α1; ρc = 0.5919) and the square mean root of the sum of squares of adjacent NN-interval differences (rMSSD; ρc = 0.6617) showed only moderate concordance.

Conclusion: Smartwatch-derived HRV provides a practical alternative with excellent accuracy compared with ECG-based HRV for global markers and those characterizing lower frequency components. However, caution is warranted with HRV markers that predominantly assess short-term variability.

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