Knijff Janine M, Houdijk Euphemia C A M, van der Kaay Daniëlle C M, van Berkel Youri, Filippini Luc, Stuurman Frederik E, Cohen Adam F, Driessen Gertjan J A, Kruizinga Matthijs D
Centre for Human Drug Research, Leiden, The Netherlands.
Juliana Children's Hospital, Haga Teaching Hospital, The Hague, The Netherlands.
Digit Biomark. 2022 Mar 31;6(1):19-29. doi: 10.1159/000522185. eCollection 2022 Jan-Apr.
Clinical research and treatment of childhood obesity is challenging, and objective biomarkers obtained in a home-setting are needed. The aim of this study was to determine the potential of novel digital endpoints gathered by a home-monitoring platform in pediatric obesity.
In this prospective observational study, 28 children with obesity aged 6-16 years were included and monitored for 28 days. Patients wore a smartwatch, which measured physical activity (PA), heart rate (HR), and sleep. Furthermore, daily blood pressure (BP) measurements were performed. Data from 128 healthy children were utilized for comparison. Differences between patients and controls were assessed via linear mixed effect models.
Data from 28 patients (average age 11.6 years, 46% male, average body mass index 30.9) and 128 controls (average age 11.1 years, 46% male, average body mass index 18.0) were analyzed. Patients were recruited between November 2018 and February 2020. For patients, the median compliance for the measurements ranged from 55% to 100% and the highest median compliance was observed for the smartwatch-related measurements (81-100%). Patients had a lower daily PA level (4,597 steps vs. 6,081 steps, 95% confidence interval [CI] 862-2,108) and peak PA level (1,115 steps vs. 1,392 steps, 95% CI 136-417), a higher nighttime HR (81 bpm vs. 71 bpm, 95% CI 6.3-12.3) and daytime HR (98 bpm vs. 88 bpm, 95% CI 7.6-12.6), a higher systolic BP (115 mm Hg vs. 104 mm Hg, 95% CI 8.1-14.5) and diastolic BP (76 mm Hg vs. 65 mm Hg, 95% CI 8.7-12.7), and a shorter sleep duration (difference 0.5 h, 95% CI 0.2-0.7) compared to controls.
Remote monitoring via wearables in pediatric obesity has the potential to objectively measure the disease burden in the home-setting. The novel endpoints demonstrate significant differences in PA level, HR, BP, and sleep duration between patients and controls. Future studies are needed to determine the capacity of the novel digital endpoints to detect effect of interventions.
儿童肥胖的临床研究和治疗具有挑战性，因此需要在家庭环境中获取客观的生物标志物。本研究的目的是确定家庭监测平台收集的新型数字终点指标在儿童肥胖中的应用潜力。
在这项前瞻性观察性研究中，纳入了28名6至16岁的肥胖儿童，并对其进行了28天的监测。患者佩戴智能手表，用于测量身体活动（PA）、心率（HR）和睡眠情况。此外，还进行了每日血压（BP）测量。使用了128名健康儿童的数据进行比较。通过线性混合效应模型评估患者与对照组之间的差异。
分析了28例患者（平均年龄11.6岁，46%为男性，平均体重指数30.9）和128例对照组（平均年龄11.1岁，46%为男性，平均体重指数18.0）的数据。患者于2018年11月至2020年2月期间招募。对于患者，测量的中位依从率在55%至100%之间，与智能手表相关的测量的中位依从率最高（81%-100%）。与对照组相比，患者的每日PA水平较低（4597步对6081步，95%置信区间[CI]862-2108）和峰值PA水平较低（1115步对1392步，95%CI 136-417），夜间HR较高（81次/分钟对71次/分钟，95%CI 6.3-12.3）和白天HR较高（98次/分钟对88次/分钟，95%CI 7.6-12.6），收缩压较高（115毫米汞柱对104毫米汞柱，95%CI 8.1-14.5）和舒张压较高（76毫米汞柱对65毫米汞柱，95%CI 8.7-12.7），睡眠时间较短（差异0.5小时，95%CI 0.2-0.7）。
通过可穿戴设备对儿童肥胖进行远程监测有潜力在家庭环境中客观测量疾病负担。这些新型终点指标显示患者与对照组在PA水平、HR、BP和睡眠时间方面存在显著差异。未来需要开展研究以确定这些新型数字终点指标检测干预效果的能力。
