What is the Delirium Bibliography? The searchable Delirium Bibliography page is one of our most popular features, allowing you to quickly gain access to the literature on delirium and acute care of older persons. It is primarily intended for clinicians and researchers interested in exploring these topics. The NIDUS team keeps it updated for you on a monthly basis!
How to Search for Articles: Search by author, title, year, and/or keywords. Each article is indexed by keywords taken from MEDLINE and other relevant databases. Click on the title of the article to read the abstract, journal, etc.
Reference Information
- Title
- Identifying Patients With Delirium Based on Unstructured Clinical Notes: Observational Study
- Authors
- Ge, W. Alabsi, H. Jain, A. Ye, E. Sun, H. Fernandes, M. Magdamo, C. Tesh, R. A. Collens, S. I. Newhouse, A. Mvr Moura, L. Zafar, S. Hsu, J. Akeju, O. Robbins, G. K. Mukerji, S. S. Das, S. Westover, M. B.
- Year
- 2022
- Journal
- JMIR Form Res
- Abstract
BACKGROUND: Delirium in hospitalized patients is a syndrome of acute brain dysfunction. Diagnostic (International Classification of Diseases [ICD]) codes are often used in studies using electronic health records (EHRs), but they are inaccurate. OBJECTIVE: We sought to develop a more accurate method using natural language processing (NLP) to detect delirium episodes on the basis of unstructured clinical notes. METHODS: We collected 1.5 million notes from >10,000 patients from among 9 hospitals. Seven experts iteratively labeled 200,471 sentences. Using these, we trained three NLP classifiers: Support Vector Machine, Recurrent Neural Networks, and Transformer. Testing was performed using an external data set. We also evaluated associations with delirium billing (ICD) codes, medications, orders for restraints and sitters, direct assessments (Confusion Assessment Method [CAM] scores), and in-hospital mortality. F1 scores, confusion matrices, and areas under the receiver operating characteristic curve (AUCs) were used to compare NLP models. We used the φ coefficient to measure associations with other delirium indicators. RESULTS: The transformer NLP performed best on the following parameters: micro F1=0.978, macro F1=0.918, positive AUC=0.984, and negative AUC=0.992. NLP detections exhibited higher correlations (φ) than ICD codes with deliriogenic medications (0.194 vs 0.073 for ICD codes), restraints and sitter orders (0.358 vs 0.177), mortality (0.216 vs 0.000), and CAM scores (0.256 vs -0.028). CONCLUSIONS: Clinical notes are an attractive alternative to ICD codes for EHR delirium studies but require automated methods. Our NLP model detects delirium with high accuracy, similar to manual chart review. Our NLP approach can provide more accurate determination of delirium for large-scale EHR-based studies regarding delirium, quality improvement, and clinical trails.
- PMID
- Keywords
clinical notes
delirium
electronic health records
machine learning
natural language processing
- Page(s)
- Volume
- Issue
Title | Authors | Journal | Year | Keywords |
---|---|---|---|---|
Have you SCAND MMe Please? A framework to prevent harm during acute hospitalisation of older persons: A retrospective audit. | Redley, B. Baker, T. | Journal of Clinical Nursing | 2019 |
acute disease |
Low-Dose Ketamine Infusion to Decrease Postoperative Delirium for Spinal Fusion Patients. | Plyler, S. S. Muckler, V. C. Titch, J. F. Gupta, D. K. Rice, A. N. | J Perianesth Nurs | 2019 |
3d-cam |
Nurses' experiences of caring for older patients afflicted by delirium in a neurological department. | Kristiansen, S. Konradsen, H. Beck, M. | Journal of Clinical Nursing | 2019 |
adult |
Association of Delirium Response and Safety of Pharmacological Interventions for the Management and Prevention of Delirium: A Network Meta-analysis. | Wu, Y. C. Tseng, P. T. Tu, Y. K. Hsu, C. Y. Liang, C. S. Yeh, T. C. Chen, T. Y. Chu, C. S. Matsuoka, Y. J. Stubbs, B. Carvalho, A. F. Wada, S. Lin, P. Y. Chen, Y. W. Su, K. P. | JAMA Psychiatry | 2019 | |
Effect of electroencephalography-guided anesthetic administration on postoperative delirium among older adults undergoing major surgery the engages randomized clinical trial. | Wildes, T. S. Mickle, A. M. Abdallah, A. B. Maybrier, H. R. Oberhaus, J. Budelier, T. P. Kronzer, A. McKinnon, S. L. Park, D. Torres, B. A. Graetz, T. J. Emmert, D. A. Palanca, B. J. Goswami, S. Jordan, K. Lin, N. Fritz, B. A. Stevens, T. W. Jacobsohn, E. | JAMA | 2019 |
NCT02241655 |
Perioperative Epidural Use and Risk of Delirium in Surgical Patients: A Secondary Analysis of the PODCAST Trial. | Vlisides, P. E. Thompson, A. Kunkler, B. S. Maybrier, H. R. Avidan, M. S. Mashour, G. A. | Anesth Analg | 2019 | |
Effect of Intravenous Acetaminophen vs Placebo Combined with Propofol or Dexmedetomidine on Postoperative Delirium among Older Patients Following Cardiac Surgery: The DEXACET Randomized Clinical Trial. | Subramaniam, B. Shankar, P. Shaefi, S. Mueller, A. O'Gara, B. Banner-Goodspeed, V. Gallagher, J. Gasangwa, D. Patxot, M. Packiasabapathy, S. Mathur, P. Eikermann, M. Talmor, D. Marcantonio, E. R. | JAMA | 2019 |
NCT02546765 |
The use of a screening scale improves the recognition of delirium in older patients after cardiac surgery - a retrospective observational study. | Smulter, N. Claesson Lingehall, H. Gustafson, Y. Olofsson, B. Engstrom, K. G. | J Clin Nurs | 2019 |
Assessments scales |
Incidence and predictors of postoperative delirium in the older acute care surgery population: a prospective study. | Saravana-Bawan, B. Warkentin, L. M. Rucker, D. Carr, F. Churchill, T. A. Khadaroo, R. G. | Canadian Journal of Surgery | 2019 |
aged |
Association of Duration of Surgery With Postoperative Delirium Among Patients Receiving Hip Fracture Repair. | Ravi, B. Pincus, D. Choi, S. Jenkinson, R. Wasserstein, D. N. Redelmeier, D. A. | JAMA Netw Open | 2019 | |
Depression Predicts Delirium After Coronary Artery Bypass Graft Surgery Independent of Cognitive Impairment and Cerebrovascular Disease: An Analysis of the Neuropsychiatric Outcomes After Heart Surgery Study. | Oldham, M. A. Hawkins, K. A. Lin, I. H. Deng, Y. Hao, Q. Scoutt, L. M. Yuh, D. D. Lee, H. B. | American Journal of Geriatric Psychiatry | 2019 |
aged |
Accuracy of the Delirium Observational Screening Scale (DOS) as a screening tool for delirium in patients with advanced cancer. | Neefjes, E. C. W. van der Vorst, Mjdl Boddaert, M. S. A. Verdegaal, Batt Beeker, A. Teunissen, S. C. C. Beekman, A. T. F. Zuurmond, W. W. A. Berkhof, J. Verheul, H. M. W. | BMC Cancer | 2019 |
Delirium |
The impact of intravenous isotonic and hypotonic maintenance fluid on the risk of delirium in adult postoperative patients: retrospective before-after observational study. | Nagae, M. Egi, M. Furushima, N. Okada, M. Makino, S. Mizobuchi, S. | J Anesth | 2019 |
Delirium |
Association between delirium, adverse clinical events and functional outcomes in older patients admitted to rehabilitation settings after a hip fracture: A multicenter retrospective cohort study. | Morandi, A. Mazzone, A. Bernardini, B. Suardi, T. Prina, R. Pozzi, C. Gentile, S. Trabucchi, M. Bellelli, G. | Geriatrics & Gerontology International | 2019 |
aged |
Handover of anesthesia care is associated with an increased risk of delirium in elderly after major noncardiac surgery: results of a secondary analysis. | Liu, G. Y. Su, X. Meng, Z. T. Cui, F. Li, H. L. Zhu, S. N. Wang, D. X. | J Anesth | 2019 |
Delirium |
Undiagnosed delirium is frequent and difficult to predict: Results from a prevalence survey of a tertiary hospital. | Lange, P. W. Lamanna, M. Watson, R. Maier, A. B. | J Clin Nurs | 2019 |
Undiagnosed delirium |