Using Wearable Biosensors to Predict Length of Stay for Patients with IBD After Bowel Surgery

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.