BACKGROUND 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. METHODS 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. RESULTS 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. CONCLUSIONS 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.).

中文翻译：

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智能手表的大规模评估以识别心房颤动。

背景技术可穿戴设备上的光学传感器可以检测不规则脉冲。智能手表应用程序 (app) 在典型使用期间识别心房颤动的能力尚不清楚。方法 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心房颤动，则会启动远程医疗访问并将心电图 (ECG) 贴片邮寄给参与者，佩戴时间最长为 7 天。在脉搏不规则通知后 90 天和研究结束时进行调查。主要目标是估计心电图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 的不规则脉搏间隔的阳性预测值。结果 我们在 8 个月内招募了 419,297 名参与者。在平均 117 天的监测中，2161 名参与者 (0.52%) 收到了脉搏不规则的通知。在返回包含可分析数据的心电图贴片的 450 名参与者中 - 平均在通知后 13 天应用 - 总体而言，34%（97.5% 置信区间 [CI]，29 至 39）存在心房颤动，并且在 65 岁或以上的参与者中，有 35%（97.5% CI，27 至 43）。在被告知脉搏不规则的参与者中，阳性预测值为 0.84（95% CI，0.76 至 0. 92) 用于在心电图上同时观察心房颤动和随后的不规则脉搏通知，0.71 (97.5% CI, 0.69 至 0.74) 用于在心电图上同时观察心房颤动和随后的不规则转速图。在返回 90 天调查的 1376 名通知参与者中，57% 的人联系了研究之外的医疗保健提供者。没有与应用程序相关的严重不良事件的报告。结论 收到不规则脉搏通知的概率很低。在收到脉搏不规则通知的参与者中，34% 的参与者在随后的心电图贴片读数中出现心房颤动，84% 的通知与心房颤动一致。这种无站点（参与者无需现场访问），务实的研究设计为大规模的务实研究奠定了基础，在这些研究中，可以使用用户拥有的设备可靠地评估结果或依从性。（由 Apple 资助；Apple Heart Study ClinicalTrials.gov 编号为 NCT03335800。）。