Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation.
Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation.
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DOI：
10.1056/nejmoa1901183
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发表时间：
2019-11-14
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影响因子：
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通讯作者：
Apple Heart Study Investigators
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作者：
Perez MV;Mahaffey KW;Hedlin H;Rumsfeld JS;Garcia A;Ferris T;Balasubramanian V;Russo AM;Rajmane A;Cheung L;Hung G;Lee J;Kowey P;Talati N;Nag D;Gummidipundi SE;Beatty A;Hills MT;Desai S;Granger CB;Desai M;Turakhia MP;Apple Heart Study Investigators
可穿戴设备上的光学传感器可以检测到不规则的脉搏。智能手表应用程序（app）在典型使用期间识别房颤的能力尚不清楚。没有房颤的参与者（由参与者自己报告）使用智能手机（Apple iPhone）应用程序同意监测。如果基于智能手表的不规则脉搏通知算法识别出可能的房颤，则启动远程医疗访视，并将心电图（ECG）贴片邮寄给参与者，佩戴长达7天。在通知不规则脉搏后90天和研究结束时进行调查。主要目的是估计ECG贴片上显示的房颤通知参与者的比例以及目标置信区间宽度为0.10的不规则脉冲间期的阳性预测值。我们在8个月内招募了419，297名参与者。在中位数为117天的监测中，2161名参与者（0.52%）收到了不规则脉搏的通知。在450名返回包含可以分析的数据的ECG补丁的参与者中-平均在通知后13天应用-总体上有34%（97.5%置信区间[CI]，29至39）存在房颤，65岁或以上的参与者有35%（97.5% CI，27至43）。在被告知脉搏不规则的参与者中，在ECG上观察到房颤并随后通知脉搏不规则的阳性预测值为0.84（95% CI，0.76至0.92），在ECG上观察到房颤并随后通知脉搏不规则的阳性预测值为0.71（97.5% CI，0.69至0.74）。在1376名返回90天调查的通知参与者中，57%的人联系了研究之外的医疗保健提供者。未报告严重应用程序相关不良事件。接收到不规则脉搏通知的概率很低。在收到不规则脉搏通知的参与者中，34%在随后的ECG贴片读数中有房颤，84%的通知与房颤一致。这种无研究中心（参与者无需现场访视）、务实的研究设计为大规模务实研究奠定了基础，在这些研究中，可以使用用户自有设备可靠地评估结局或依从性。（由Apple资助; Apple Heart Study ClinicalTrials.gov编号，NCT 03335800。
Optical sensors on wearable devices can detect irregular pulses. The ability of a smartwatch application (app) to identify atrial fibrillation during typical use is unknown. Participants without atrial fibrillation (as reported by the participants themselves) used a smartphone (Apple iPhone) app to consent to monitoring. If a smartwatch-based irregular pulse notification algorithm identified possible atrial fibrillation, a telemedicine visit was initiated and an electrocardiography (ECG) patch was mailed to the participant, to be worn for up to 7 days. Surveys were administered 90 days after notification of the irregular pulse and at the end of the study. The main objectives were to estimate the proportion of notified participants with atrial fibrillation shown on an ECG patch and the positive predictive value of irregular pulse intervals with a targeted confidence interval width of 0.10. We recruited 419,297 participants over 8 months. Over a median of 117 days of monitoring, 2161 participants (0.52%) received notifications of irregular pulse. Among the 450 participants who returned ECG patches containing data that could be analyzed — which had been applied, on average, 13 days after notification — atrial fibrillation was present in 34% (97.5% confidence interval [CI], 29 to 39) overall and in 35% (97.5% CI, 27 to 43) of participants 65 years of age or older. Among participants who were notified of an irregular pulse, the positive predictive value was 0.84 (95% CI, 0.76 to 0.92) for observing atrial fibrillation on the ECG simultaneously with a subsequent irregular pulse notification and 0.71 (97.5% CI, 0.69 to 0.74) for observing atrial fibrillation on the ECG simultaneously with a subsequent irregular tachogram. Of 1376 notified participants who returned a 90-day survey, 57% contacted health care providers outside the study. There were no reports of serious app-related adverse events. The probability of receiving an irregular pulse notification was low. Among participants who received notification of an irregular pulse, 34% had atrial fibrillation on subsequent ECG patch readings and 84% of notifications were concordant with atrial fibrillation. This siteless (no on-site visits were required for the participants), pragmatic study design provides a foundation for large-scale pragmatic studies in which outcomes or adherence can be reliably assessed with user-owned devices. (Funded by Apple; Apple Heart Study ClinicalTrials.gov number, NCT03335800.)