Journal article
Machine learning-based prediction of delirium in older patients with chronic kidney disease requiring intensive care: A hospital-based retrospective cohort study
Journal of Psychosomatic Research, Vol.200, pp.1-9
2026
PMID: 41265364
Abstract
Objectives
Delirium is a common complication in intensive care units (ICUs), especially among older adults with chronic kidney disease (CKD). It is associated with increased mortality and prolonged hospitalization. Machine learning (ML)-based models can help predict delirium. In this study, we developed an ML-based delirium prediction model for critically ill older patients with CKD.
Methods
This retrospective cohort study included patients aged ≥65 years admitted to the ICU between January 2021 and November 2023. Delirium was assessed every 8 h throughout the ICU stay using the Intensive Care Delirium Screening Checklist (ICDSC) and defined as a score of ≥4. Eight ML models were compared in terms of the area under the receiver operating characteristic curve (AUROC), accuracy, F1-score, specificity, and recall.
Results
This study included 895 patients, of whom 55.3 % developed delirium. The random forest model outperformed others (F1-score: 0.891; specificity: 0.911; recall: 0.864; accuracy: 0.885; precision: 0.923; AUROC: 0.950). Backward feature selection achieved an F1-score of 0.892 and an AUROC of 0.953, identifying 14 key predictors of delirium: physical restraint use, low Glasgow Coma Scale score, high white blood cell count, hypernatremia, fever, advanced age, hypoalbuminemia, hypercalcemia, low hemoglobin, high Acute Physiology and Chronic Health Evaluation II (APACHE II) score, hyperkalemia, mechanical ventilation, sedation, and elevated C-reactive protein.
Conclusion
Our ML model demonstrated good performance in predicting delirium in critically ill older adults with CKD, suggesting potential value for early identification. Future studies may explore integration into hospital systems to support delirium prevention strategies.
Details
- Title
- Machine learning-based prediction of delirium in older patients with chronic kidney disease requiring intensive care: A hospital-based retrospective cohort study
- Authors
- Chia-Rung Wu - Taipei Medical UniversityYung-Chun Chang - Taipei Medical UniversityVictoria Tranyor - University of the Sunshine Coast, Queensland, School of Health - NursingShu-Tai Shen Hsiao - Taipei Medical UniversityShu-Liu Guo - Taipei Medical UniversityShu-Chuan Lin - Taipei Medical University HospitalSen-Kuang Hou - Taipei Medical University HospitalHsiao-Yean Chiu (Corresponding Author) - Taipei Medical University
- Publication details
- Journal of Psychosomatic Research, Vol.200, pp.1-9
- Publisher
- Elsevier Inc.
- Date published
- 2026
- DOI
- 10.1016/j.jpsychores.2025.112454
- ISSN
- 1879-1360
- PMID
- 41265364
- Grant note
- This work was financially supported by the Higher Education Support Project of the Ministry of Education (MOE) in Taiwan. This work was funded by the National Science and Technology Council, Taiwan (113-2628-B-038-003-MY3 and 114-2314-B-038-094-MY3).
- Organisation Unit
- Healthy Ageing Research Cluster; School of Health - Nursing
- Language
- English
- Record Identifier
- 991192244902621
- Output Type
- Journal article
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web Of Science research areas
- Psychiatry