Development of a Machine Learning–Based Predictive Model for Postoperative Delirium in Older Adult Intensive Care Unit Patients: Retrospective Study
The high-performance XGB model for predicting postoperative delirium state in older adult ICU patients has been successfully developed and validated. The model predicts the delirium state at 12 h, 24 h, 48 h, and whole stay time after the first day of hospitalization within the ICU. This enables physicians to identify high-risk patients early, thus facilitating the optimization of personalized management strategies and care plans.
Authors
- Miao Zhou (ORCID: https://orcid.org/0000-0002-9440-6284)
- Qinglai Zang
- Yanchen Lin (ORCID: https://orcid.org/0009-0006-7184-3234)
- Huixiu Hu (ORCID: https://orcid.org/0000-0002-2570-0551)
- Dengyun Xia
- Qi Li (ORCID: https://orcid.org/0000-0001-8788-0992)
- Jing Huang (ORCID: https://orcid.org/0000-0001-9234-3702)
- Houfeng Li
- Jintao Duan
- Ying Zhang (ORCID: https://orcid.org/0000-0002-4499-6394)
Institutions
- Wannan Medical College (CN)
- University of Shanghai for Science and Technology (CN)
- Hebei North University (CN)
- Second Military Medical University (CN)
- Shanghai Jiao Tong University (CN)
- Shanghai Ninth People's Hospital (CN)
- Shanghai Changzheng Hospital (CN)
- Jiangsu Cancer Hospital (CN)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-04-18
- DOI
- https://doi.org/10.2196/67258
- Citations
- 5
- Primary Topic
- Intensive Care Unit Cognitive Disorders
- Type
- article
- Field-Weighted Citation Impact
- 7.73