Wiebe Madeleine, Mackay Marnie, Krishnan Ragur, Tian Julie, Larsson Jakob, Modanloo Setayesh, Job McIntosh Christiane, Sztym Melissa, Elton-Smith Gail, Rose Alyssa, Ho Chester, Greenshaw Andrew, Cao Bo, Chan Andrew, Hayward Jake
Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.
Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.
PLOS Digit Health. 2024 Aug 22;3(8):e0000571. doi: 10.1371/journal.pdig.0000571. eCollection 2024 Aug.
Common, consumer-grade biosensors mounted on fitness trackers and smartwatches can measure an array of biometrics that have potential utility in post-discharge medical monitoring, especially in remote/rural communities. The feasibility characteristics for wrist-worn biosensors are poorly described for post-COVID conditions and rural populations.
We prospectively recruited patients in rural communities who were enrolled in an at-home rehabilitation program for post-COVID conditions. They were asked to wear a FitBit Charge 2 device and biosensor parameters were analyzed [e.g. heart rate, sleep, and activity]. Electronic patient reported outcome measures [E-PROMS] for mental [bi-weekly] and physical [daily] symptoms were collected using SMS text or email [per patient preference]. Exit surveys and interviews evaluated the patient experience.
Ten patients were observed for an average of 58 days and half [N = 5] were monitored for 8 weeks or more. Five patients [50%] had been hospitalized with COVID [mean stay = 41 days] and 4 [36%] had required mechanical ventilation. As baseline, patients had moderate to severe levels of anxiety, depression, and stress; fatigue and shortness of breath were the most prevalent physical symptoms. Four patients [40%] already owned a smartwatch. In total, 575 patient days of patient monitoring occurred across 10 patients. Biosensor data was usable for 91.3% of study hours and surveys were completed 82.1% and 78.7% of the time for physical and mental symptoms, respectively. Positive correlations were observed between stress and resting heart rate [r = 0.360, p<0.01], stress and daily steps [r = 0.335, p<0.01], and anxiety and daily steps [r = 0.289, p<0.01]. There was a trend toward negative correlation between sleep time and physical symptom burden [r = -0.211, p = 0.05]. Patients reported an overall positive experience and identified the potential for wearable devices to improve medical safety and access to care. Concerns around data privacy/security were infrequent.
We report excellent feasibility characteristics for wrist-worn biosensors and e-PROMS as a possible substrate for multi-modal disease tracking in post-COVID conditions. Adapting consumer-grade wearables for medical use and scalable remote patient monitoring holds great potential.
安装在健身追踪器和智能手表上的普通消费级生物传感器可以测量一系列生物特征，这些生物特征在出院后医疗监测中具有潜在用途，特别是在偏远/农村社区。对于新冠疫情后情况和农村人口，腕戴式生物传感器的可行性特征描述较少。
我们前瞻性招募了农村社区中参加新冠疫情后居家康复计划的患者。要求他们佩戴FitBit Charge 2设备，并分析生物传感器参数（如心率、睡眠和活动）。使用短信或电子邮件（根据患者偏好）收集患者报告的电子结局指标（E-PROMS），用于评估精神（每两周一次）和身体（每天）症状。出院调查和访谈评估了患者体验。
观察了10名患者，平均观察时间为58天，其中一半（N = 5）被监测了8周或更长时间。5名患者（50%）曾因新冠住院（平均住院时间 = 41天），4名患者（36%）需要机械通气。基线时，患者有中度至重度焦虑、抑郁和压力；疲劳和呼吸急促是最常见的身体症状。4名患者（40%）已经拥有智能手表。10名患者总共进行了575个患者监测日。生物传感器数据在91.3%的研究时间内可用，身体和精神症状调查的完成率分别为82.1%和78.7%。观察到压力与静息心率之间呈正相关（r = 0.360，p<0.01），压力与每日步数之间呈正相关（r = 0.335，p<0.01），焦虑与每日步数之间呈正相关（r = 0.289，p<0.01）。睡眠时间与身体症状负担之间有负相关趋势（r = -0.211，p = 0.05）。患者报告总体体验良好，并确定了可穿戴设备在改善医疗安全和获得医疗服务方面的潜力。对数据隐私/安全的担忧较少。
我们报告了腕戴式生物传感器和电子PROMS作为新冠疫情后多模式疾病追踪可能基质的极佳可行性特征。将消费级可穿戴设备用于医疗用途以及可扩展的远程患者监测具有巨大潜力。
