University of Chicago Medicine Inflammatory Bowel Disease Center, 5841 S. Maryland Ave, MC 4076, Chicago, IL, 60637, USA.
Dig Dis Sci. 2022 Mar;67(3):844-853. doi: 10.1007/s10620-021-06910-w. Epub 2021 Mar 24.
It remains unknown whether ambulation or sleep predicts postoperative length of stay for patients with IBD. We aim to identify the utility of wearable biosensors in predicting postoperative length of stay for patients with IBD.
Associations of postoperative length of stay with step count/sleep duration/sleep efficiency measured by wearable biosensors were examined. The best-fitting multivariable linear regression model predicting length of stay was constructed using stepwise model selection.
Final sample included 37 patients. Shorter sleep duration on postoperative day 4 (r = 0.51, p = 0.043) or 5 (r = 0.81, p = 0.0045) or higher sleep efficiency on postoperative day 5 (r = - 0.77, p = 0.0098) was associated with a shorter length of stay. Additionally, a more positive change in sleep efficiency from postoperative day 4-5 was associated with a shorter length of stay (r = - 0.77, p = 0.024). The best-fitting multivariable linear regression model revealed Clavien-Dindo grade 1 (p = 0.045) and interaction between Clavien-Dindo grade 2/3a and mean daily steps (p = 0.00038) are significant predictors of length of stay. The following variables were not significantly associated with length of stay: mean daily steps/sleep duration/sleep efficiency, average rate of change in these three variables, and changes in step count between successive postoperative days 1-5, sleep duration between successive postoperative days 2-5, and sleep efficiency between successive postoperative days 2-4.
We demonstrated the utility of activity and sleep data from wearable biosensors in predicting length of stay. Patients with more severe complications may benefit more (i.e., reduced postoperative length of stay) from increased ambulation. However, overall, sleep duration/efficiency did not predict length of stay.
目前尚不清楚活动或睡眠是否可以预测 IBD 患者的术后住院时间。本研究旨在探讨可穿戴生物传感器在预测 IBD 患者术后住院时间中的应用价值。
分析可穿戴生物传感器测量的术后住院时间与步数/睡眠时间/睡眠效率之间的相关性。采用逐步模型选择法构建预测住院时间的最佳拟合多变量线性回归模型。
最终纳入 37 例患者。术后第 4 天（r=0.51，p=0.043）或第 5 天（r=0.81，p=0.0045）睡眠时间较短，或术后第 5 天（r=-0.77，p=0.0098）睡眠效率较高与较短的住院时间相关。此外，术后第 4 天至第 5 天睡眠效率的变化与较短的住院时间相关（r=-0.77，p=0.024）。最佳拟合的多变量线性回归模型显示，Clavien-Dindo 分级 1（p=0.045）和 Clavien-Dindo 分级 2/3a 与平均每日步数之间的相互作用（p=0.00038）是住院时间的显著预测因子。以下变量与住院时间无显著相关性：平均每日步数/睡眠时间/睡眠效率、这三个变量的平均变化率以及术后第 1 至 5 天之间的步数变化、术后第 2 至 5 天之间的睡眠时间变化和术后第 2 至 4 天之间的睡眠效率变化。
本研究证明了可穿戴生物传感器的活动和睡眠数据在预测住院时间方面的有效性。并发症更严重的患者可能会从增加活动中获益更多（即缩短术后住院时间）。但是，总体而言，睡眠时间/效率并未预测住院时间。
