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

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Abstract

Background and Aims

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.

Methods

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.

Results

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.

Conclusion

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.

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Funding

This research was supported by the University of Chicago Pritzker School of Medicine and an investigator-initiated grant from Takeda Pharmaceuticals.

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Authors and Affiliations

  1. University of Chicago Medicine Inflammatory Bowel Disease Center, 5841 S. Maryland Ave, MC 4076, Chicago, IL, 60637, USA

    Yangtian Yi, Philip H. Sossenheimer, Amarachi I. Erondu, Kinga B. Skowron, Victoria Rai, Jorie M. Singer, Katia El Jurdi, Neil H. Hyman & David T. Rubin

Authors
  1. Yangtian Yi
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  2. Philip H. Sossenheimer
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  3. Amarachi I. Erondu
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  4. Kinga B. Skowron
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  5. Victoria Rai
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  6. Jorie M. Singer
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  7. Katia El Jurdi
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  8. Neil H. Hyman
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  9. David T. Rubin
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Contributions

YY, PHS, NHH, and DTR conceived and designed the study. YY, PHS, AIE, KBS, VR, JS, and KEJ contributed to the acquisition of data. YY, PHS, and AIE contributed to the analysis of data. All authors contributed to interpretation of data and were involved in drafting the article or revising it critically for important intellectual content. All authors approved the final manuscript to be submitted and agreed to be accountable for all aspects of the work.

Corresponding author

Correspondence to David T. Rubin.

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Conflict of interest

YY, PHS, AIE, KBS, VR, JS, KEJ, and NHH have no relevant disclosures. DTR is a consultant and has received grant support from Abbvie, Merck & Co., Janssen, Takeda, and Pfizer.

Ethical approval

The study was approved by the University of Chicago Institutional Review Board (IRB15-1535).

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Podium presentation at Advances in Inflammatory Bowel Diseases (AIBD), Orlando, Florida; December 12–14, 2019.

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Yi, Y., Sossenheimer, P.H., Erondu, A.I. et al. Using Wearable Biosensors to Predict Length of Stay for Patients with IBD After Bowel Surgery. Dig Dis Sci 67, 844–853 (2022). https://doi.org/10.1007/s10620-021-06910-w

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  • DOI: https://doi.org/10.1007/s10620-021-06910-w

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