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在血压测量和使用智能手机心脏监测器时,在初级保健中进行心房颤动检测。

Atrial fibrillation detection in primary care during blood pressure measurements and using a smartphone cardiac monitor.

机构信息

School of Population Health, University of Auckland, Private Bag 92019, Auckland, New Zealand.

Green Lane Cardiovascular Service, Auckland City Hospital, Auckland, New Zealand.

出版信息

Sci Rep. 2021 Sep 6;11(1):17721. doi: 10.1038/s41598-021-97475-1.

DOI:10.1038/s41598-021-97475-1
PMID:34489508
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8421380/
Abstract

Improved atrial fibrillation (AF) screening methods are required. We detected AF with pulse rate variability (PRV) parameters using a blood pressure device (BP+; Uscom, Sydney, Australia) and with a Kardia Mobile Cardiac Monitor (KMCM; AliveCor, Mountain View, CA). In 421 primary care patients (mean (range) age: 72 (31-99) years), we diagnosed AF (n = 133) from 12-lead electrocardiogram recordings, and performed PRV and KMCM measurements. PRV parameters detected AF with area under curve (AUC) values of up to 0.92. Using the mean of two sequential readings increased AUC to up to 0.94 and improved positive predictive value at a given sensitivity (by up to 18%). The KMCM detected AF with 83% sensitivity and 68% specificity. 89 KMCM recordings were "unclassified" or blank, and PRV detected AF in these with AUC values of up to 0.88. When non-AF arrhythmias (n = 56) were excluded, the KMCM device had increased specificity (73%) and PRV had higher discrimination performance (maximum AUC = 0.96). In decision curve analysis, all PRV parameters consistently achieved a positive net benefit across the range of clinical thresholds. In primary care, AF can be detected by PRV accurately and by KMCM, especially in the absence of non-AF arrhythmias or when combinations of measurements are used.

摘要

需要改进心房颤动(AF)的筛查方法。我们使用血压设备(BP+;澳大利亚悉尼的 Uscom)和 Kardia 移动心脏监测仪(KMCM;加利福尼亚州山景城的 AliveCor)通过脉搏率变异性(PRV)参数来检测 AF。在 421 名初级保健患者(平均(范围)年龄:72(31-99)岁)中,我们从 12 导联心电图记录中诊断出 AF(n=133),并进行了 PRV 和 KMCM 测量。PRV 参数检测 AF 的曲线下面积(AUC)值高达 0.92。使用两个连续读数的平均值可将 AUC 提高到 0.94,并提高了给定敏感性的阳性预测值(最高提高了 18%)。KMCM 以 83%的敏感性和 68%的特异性检测 AF。89 个 KMCM 记录为“未分类”或空白,PRV 在这些记录中检测到的 AUC 值高达 0.88。当排除非 AF 心律失常(n=56)时,KMCM 设备的特异性(73%)提高,PRV 的鉴别性能更高(最大 AUC=0.96)。在决策曲线分析中,所有 PRV 参数在整个临床阈值范围内均能实现正净效益。在初级保健中,PRV 可以准确检测 AF,KMCM 也可以检测 AF,尤其是在没有非 AF 心律失常或使用组合测量时。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd8/8421380/2f2b0b001e11/41598_2021_97475_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd8/8421380/5a2e6894e6b6/41598_2021_97475_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd8/8421380/0bfb9292396f/41598_2021_97475_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd8/8421380/2f2b0b001e11/41598_2021_97475_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd8/8421380/5a2e6894e6b6/41598_2021_97475_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd8/8421380/0bfb9292396f/41598_2021_97475_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd8/8421380/2f2b0b001e11/41598_2021_97475_Fig3_HTML.jpg

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