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利用血压监测仪中的新型机器学习算法检测心房颤动的诊断准确性。

Diagnostic accuracy for detecting atrial fibrillation using a novel machine learning algorithm in a blood pressure monitor.

机构信息

Cardiology Division, Wilmington Health, Wilmington, North Carolina.

Internal Medicine Division, CarolinaMD, Charlotte, North Carolina.

出版信息

Heart Rhythm. 2024 Oct;21(10):2023-2027. doi: 10.1016/j.hrthm.2024.04.086. Epub 2024 Apr 30.

DOI:10.1016/j.hrthm.2024.04.086
PMID:38692340
Abstract

BACKGROUND

Early detection of atrial fibrillation (AF) is key for preventing strokes. Blood pressure monitors (BPMs) with built-in AF screening features have the potential for early detection at home. Recently, 2 BPMs (HEM-7371T1-AZ and HEM-7372T1-AZAZ, Omron Healthcare Co., Ltd.) that share a novel AF screening feature have been developed. Their AF screening feature utilizes an algorithm that incorporates machine learning, with the potential to improve diagnostic accuracy.

OBJECTIVE

The purpose of this study was to evaluate the performance of this AF screening feature in a multicenter, prospective clinical study at 5 sites in the United States.

METHODS

A total of 559 subjects were enrolled for this study: 267 in AF cohort and 292 in the non-AF cohort. AF screening was performed in all subjects by the 2 Omron BPMs and by 1 Microlife BPM (BP 3MX1-3, WatchBP Home A, Microlife Corp.), and a simultaneous 12-lead electrocardiogram (ECG) was recorded for comparison. All 12-lead ECGs were interpreted by a board-certified cardiologist who was blinded to the BPM results. Sensitivity, specificity, and accuracy for the diagnosis of AF were calculated.

RESULTS

Omron HEM-7371T1-AZ BPM had sensitivity of 95.1% (95% confidence interval [CI] 91.8%-97.4%), specificity 98.6% (95% CI 96.6%-99.7%), and accuracy of 97.0% (95% CI 95.2%-98.2%). Equivalent results were obtained with the Omron HEM-7371T1-AZAZ BPM. This compared favorably to the Microlife BPM (sensitivity 78.5%, 95% CI 73.1%-83.3%; specificity 97.6%, 95% CI 95.1%-99.0%; accuracy 88.4%, 95% CI 85.5%-91.0%).

CONCLUSION

These data support both home and professional use of these novel Omron BPMs for the detection of AF.

摘要

背景

早期发现心房颤动(AF)是预防中风的关键。具有内置 AF 筛查功能的血压监测仪(BPM)具有在家中进行早期检测的潜力。最近,开发了两款具有新型 AF 筛查功能的 BPM(欧姆龙健康护理有限公司的 HEM-7371T1-AZ 和 HEM-7372T1-AZAZ)。它们的 AF 筛查功能利用了一种结合机器学习的算法,有潜力提高诊断准确性。

目的

本研究旨在通过在美国 5 个地点的多中心前瞻性临床研究评估这种 AF 筛查功能的性能。

方法

这项研究共招募了 559 名受试者:267 名在 AF 队列中,292 名在非 AF 队列中。对所有受试者使用 2 款欧姆龙 BPM 和 1 款 Microlife BPM(BP 3MX1-3、WatchBP Home A、Microlife 公司)进行 AF 筛查,并同时记录 12 导联心电图(ECG)进行比较。所有 12 导联 ECG 均由一位对 BPM 结果不知情的、经董事会认证的心脏病专家进行解读。计算用于诊断 AF 的敏感性、特异性和准确性。

结果

欧姆龙 HEM-7371T1-AZ BPM 的敏感性为 95.1%(95%置信区间 [CI] 91.8%-97.4%),特异性为 98.6%(95% CI 96.6%-99.7%),准确性为 97.0%(95% CI 95.2%-98.2%)。欧姆龙 HEM-7371T1-AZAZ BPM 获得了等效的结果。这与 Microlife BPM 相比具有优势(敏感性 78.5%,95% CI 73.1%-83.3%;特异性 97.6%,95% CI 95.1%-99.0%;准确性 88.4%,95% CI 85.5%-91.0%)。

结论

这些数据支持在家中和专业环境中使用这些新型欧姆龙 BPM 来检测 AF。

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