Related Experiment Video
Updated: Sep 12, 2025
A Rat Graft Rejection Model of Intestinal Transplantation with Exteriorized Ileostomy for Longitudinal Prognosis Assessment
Published on: June 10, 2025
Gated recurrent unit with decay has real-time capability for postoperative ileus surveillance and offers
Xiaoyang Ruan1,2, Sunyang Fu1,2, Heling Jia2
1McWilliams School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA.
Background:
Ileus, a postoperative complication after colorectal surgery, increases morbidity, costs, and hospital stays. Assessing risk of ileus is crucial, especially with the trend towards early discharge. Prior studies assessed risk of ileus with regression models, the role of deep learning remains unexplored.
Methods:
We evaluated the Gated Recurrent Unit with Decay (GRU-D) for real-time ileus risk assessment in 7349 colorectal surgeries across three Mayo Clinic sites with two Electronic Health Record (EHR) systems. The results were compared with atemporal models on a panel of benchmark metrics.
Results:
Here we show that despite extreme data sparsity (e.g., 72.2% of labs, 26.9% of vitals lack measurements within 24 h post-surgery), GRU-D demonstrates improved performance by integrating new measurements and exhibits robust transferability. In brute-force transfer, AUROC decreases by no more than 5%, while multi-source instance transfer yields up to a 2.6% improvement in AUROC and an 86% narrower confidence interval. Although atemporal models perform better at certain pre-surgical time points, their performance fluctuates considerably and generally falls short of GRU-D in post-surgical hours.
Conclusions:
GRU-D's dynamic risk assessment capability is crucial in scenarios where clinical follow-up is essential, warranting further research on built-in explainability for clinical integration.
