用于心房颤动中心率和心律监测的智能手机光电血压计的真实世界验证

Henri Gruwez, Daniel Ezzat, Tim Van Puyvelde, Sebastiaan Dhont, Evelyne Meekers, Liesbeth Bruckers, Femke Wouters, Michiel Kellens, Hugo Van Herendael, Maximo Rivero-Ayerza, Dieter Nuyens, Peter Haemers, Laurent Pison
{"title":"用于心房颤动中心率和心律监测的智能手机光电血压计的真实世界验证","authors":"Henri Gruwez, Daniel Ezzat, Tim Van Puyvelde, Sebastiaan Dhont, Evelyne Meekers, Liesbeth Bruckers, Femke Wouters, Michiel Kellens, Hugo Van Herendael, Maximo Rivero-Ayerza, Dieter Nuyens, Peter Haemers, Laurent Pison","doi":"10.1093/europace/euae065","DOIUrl":null,"url":null,"abstract":"Aims Photoplethysmography- (PPG) based smartphone applications facilitate heart rate and rhythm monitoring in patients with paroxysmal and persistent atrial fibrillation (AF). Despite an endorsement from the European Heart Rhythm Association, validation studies in this setting are lacking. Therefore, we evaluated the accuracy of PPG-derived heart rate and rhythm classification in subjects with an established diagnosis of AF in unsupervised real-world conditions. Methods and results Fifty consecutive patients were enrolled, 4 weeks before undergoing AF ablation. Patients used a handheld single-lead electrocardiography (ECG) device and a fingertip PPG smartphone application to record 3907 heart rhythm measurements twice daily during 8 weeks. The ECG was performed immediately before and after each PPG recording and was given a diagnosis by the majority of three blinded cardiologists. A consistent ECG diagnosis was exhibited along with PPG data of sufficient quality in 3407 measurements. A single measurement exhibited good quality more often with ECG (93.2%) compared to PPG (89.5%; P < 0.001). However, PPG signal quality improved to 96.6% with repeated measurements. Photoplethysmography-based detection of AF demonstrated excellent sensitivity [98.3%; confidence interval (CI): 96.7–99.9%], specificity (99.9%; CI: 99.8–100.0%), positive predictive value (99.6%; CI: 99.1–100.0%), and negative predictive value (99.6%; CI: 99.0–100.0%). Photoplethysmography underestimated the heart rate in AF with 6.6 b.p.m. (95% CI: 5.8 b.p.m. to 7.4 b.p.m.). Bland–Altman analysis revealed increased underestimation in high heart rates. The root mean square error was 11.8 b.p.m. Conclusion Smartphone applications using PPG can be used to monitor patients with AF in unsupervised real-world conditions. The accuracy of AF detection algorithms in this setting is excellent, but PPG-derived heart rate may tend to underestimate higher heart rates.","PeriodicalId":11720,"journal":{"name":"EP Europace","volume":"34 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real-world validation of smartphone-based photoplethysmography for rate and rhythm monitoring in atrial fibrillation\",\"authors\":\"Henri Gruwez, Daniel Ezzat, Tim Van Puyvelde, Sebastiaan Dhont, Evelyne Meekers, Liesbeth Bruckers, Femke Wouters, Michiel Kellens, Hugo Van Herendael, Maximo Rivero-Ayerza, Dieter Nuyens, Peter Haemers, Laurent Pison\",\"doi\":\"10.1093/europace/euae065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aims Photoplethysmography- (PPG) based smartphone applications facilitate heart rate and rhythm monitoring in patients with paroxysmal and persistent atrial fibrillation (AF). Despite an endorsement from the European Heart Rhythm Association, validation studies in this setting are lacking. Therefore, we evaluated the accuracy of PPG-derived heart rate and rhythm classification in subjects with an established diagnosis of AF in unsupervised real-world conditions. Methods and results Fifty consecutive patients were enrolled, 4 weeks before undergoing AF ablation. Patients used a handheld single-lead electrocardiography (ECG) device and a fingertip PPG smartphone application to record 3907 heart rhythm measurements twice daily during 8 weeks. The ECG was performed immediately before and after each PPG recording and was given a diagnosis by the majority of three blinded cardiologists. A consistent ECG diagnosis was exhibited along with PPG data of sufficient quality in 3407 measurements. A single measurement exhibited good quality more often with ECG (93.2%) compared to PPG (89.5%; P < 0.001). However, PPG signal quality improved to 96.6% with repeated measurements. Photoplethysmography-based detection of AF demonstrated excellent sensitivity [98.3%; confidence interval (CI): 96.7–99.9%], specificity (99.9%; CI: 99.8–100.0%), positive predictive value (99.6%; CI: 99.1–100.0%), and negative predictive value (99.6%; CI: 99.0–100.0%). Photoplethysmography underestimated the heart rate in AF with 6.6 b.p.m. (95% CI: 5.8 b.p.m. to 7.4 b.p.m.). Bland–Altman analysis revealed increased underestimation in high heart rates. The root mean square error was 11.8 b.p.m. Conclusion Smartphone applications using PPG can be used to monitor patients with AF in unsupervised real-world conditions. The accuracy of AF detection algorithms in this setting is excellent, but PPG-derived heart rate may tend to underestimate higher heart rates.\",\"PeriodicalId\":11720,\"journal\":{\"name\":\"EP Europace\",\"volume\":\"34 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EP Europace\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/europace/euae065\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EP Europace","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/europace/euae065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

目的 基于照相血压计(PPG)的智能手机应用有助于阵发性和持续性心房颤动(房颤)患者的心率和心律监测。尽管得到了欧洲心脏节律协会的认可,但在这种情况下仍缺乏验证研究。因此,我们评估了在无监督的真实世界条件下,对已确诊为房颤的受试者进行 PPG 导出心率和心律分类的准确性。方法和结果 在房颤消融术前 4 周,我们连续招募了 50 名患者。患者使用手持式单导联心电图(ECG)设备和指尖 PPG 智能手机应用程序,在 8 周内每天两次记录 3907 次心律测量。心电图在每次 PPG 记录前后立即进行,并由三位盲人心脏病专家中的大多数做出诊断。在 3407 次测量中,心电图诊断与 PPG 数据质量一致。与 PPG(89.5%;P <0.001)相比,ECG(93.2%)的单次测量更经常表现出良好的质量。然而,PPG 信号质量在重复测量后提高到 96.6%。基于光电生理盐水成像技术的房颤检测具有极佳的灵敏度[98.3%;置信区间(CI):96.7-99.9%]、特异性(99.9%;CI:99.8-100.0%)、阳性预测值(99.6%;CI:99.1-100.0%)和阴性预测值(99.6%;CI:99.0-100.0%)。光电血压计低估了房颤患者的心率,为 6.6 b.p.m.(95% CI:5.8 b.p.m.至 7.4 b.p.m.)。Bland-Altman 分析显示,高心率时的低估率增加。均方根误差为 11.8 b.p.m。 结论 使用 PPG 的智能手机应用程序可用于在无监督的真实世界条件下监测房颤患者。在这种情况下,房颤检测算法的准确性非常高,但 PPG 导出的心率可能会低估较高的心率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-world validation of smartphone-based photoplethysmography for rate and rhythm monitoring in atrial fibrillation
Aims Photoplethysmography- (PPG) based smartphone applications facilitate heart rate and rhythm monitoring in patients with paroxysmal and persistent atrial fibrillation (AF). Despite an endorsement from the European Heart Rhythm Association, validation studies in this setting are lacking. Therefore, we evaluated the accuracy of PPG-derived heart rate and rhythm classification in subjects with an established diagnosis of AF in unsupervised real-world conditions. Methods and results Fifty consecutive patients were enrolled, 4 weeks before undergoing AF ablation. Patients used a handheld single-lead electrocardiography (ECG) device and a fingertip PPG smartphone application to record 3907 heart rhythm measurements twice daily during 8 weeks. The ECG was performed immediately before and after each PPG recording and was given a diagnosis by the majority of three blinded cardiologists. A consistent ECG diagnosis was exhibited along with PPG data of sufficient quality in 3407 measurements. A single measurement exhibited good quality more often with ECG (93.2%) compared to PPG (89.5%; P < 0.001). However, PPG signal quality improved to 96.6% with repeated measurements. Photoplethysmography-based detection of AF demonstrated excellent sensitivity [98.3%; confidence interval (CI): 96.7–99.9%], specificity (99.9%; CI: 99.8–100.0%), positive predictive value (99.6%; CI: 99.1–100.0%), and negative predictive value (99.6%; CI: 99.0–100.0%). Photoplethysmography underestimated the heart rate in AF with 6.6 b.p.m. (95% CI: 5.8 b.p.m. to 7.4 b.p.m.). Bland–Altman analysis revealed increased underestimation in high heart rates. The root mean square error was 11.8 b.p.m. Conclusion Smartphone applications using PPG can be used to monitor patients with AF in unsupervised real-world conditions. The accuracy of AF detection algorithms in this setting is excellent, but PPG-derived heart rate may tend to underestimate higher heart rates.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信