Observational studyMedicine2017
Development and validation of risk-stratification delirium prediction model for critically ill patients: A prospective, observational, single-center study.
Observational study in Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
41 citing papers in PubMed, 2 syntheses or guidelines pooled it, 63 citations in OpenAlex.
- Risk prediction models for delirium in ICU patients: a systematic review and critical appraisal.BMC anesthesiology · 2025Pooled it
- Systematic review of cognitive impairment and brain insult after mechanical ventilation.Critical care (London, England) · 2021Pooled it
- Prediction model for delirium in patients with cardiovascular surgery: development and validation.Journal of cardiothoracic surgery · 2022Trial
- Application of a flexible visitation system in critically ill patients: A randomized clinical trial.Science progressTrial
- Development of a machine learning-based prediction model for hypothyroidism-associated delirium in elderly hypothyroid patients in the intensive care unit.BMC geriatrics · 2026Article
- Development and validation of a nomogram-based risk prediction model for postoperative delirium in patients with stanford type A aortic dissection.Journal of cardiothoracic surgery · 2026Observational
- [Development and Validation of a Risk Prediction Model for Secondary Pulmonary Infarction in Elderly Patients With Acute Pulmonary Embolism].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026Article
- Construction and evaluation of a model to identify early postoperative kinesiophobia in patients with lumbar degenerative diseases: a cross-sectional study.Frontiers in rehabilitation sciences · 2026Article
- Development and validation of an explainable predictive model for the risk of moderate-to-severe obstructive sleep apnea in resistant hypertensive patients.Scientific reports · 2025Article
- Predicting ICU Delirium in Critically Ill COVID-19 Patients Using Demographic, Clinical, and Laboratory Admission Data: A Machine Learning Approach.Life (Basel, Switzerland) · 2025Article
- Validation of PREdiction of DELIRium in ICu patients (PRE-DELIRIC) model for ICU delirium in general ICU and patients with liver disease: a retrospective cohort study.Journal of intensive care · 2025Article
- Determining the ground truth for the prediction of delirium in adult patients in acute care: a scoping review.JAMIA open · 2025Review
- A nomogram for predicting delirium in the ICU among older patients with chronic obstructive pulmonary disease.BMC geriatrics · 2025Article
- Predictors of implant failure: A comprehensive analysis of risk factors in oral implant restoration for patients with partial defects of dentition.Biomolecules & biomedicine · 2025Article
- Daily Automated Prediction of Delirium Risk in Hospitalized Patients: Model Development and Validation.JMIR medical informatics · 2025Article
- Machine Learning-Based Prediction of Delirium and Risk Factor Identification in Intensive Care Unit Patients With Burns: Retrospective Observational Study.JMIR formative research · 2025Observational
- Development and Validation of Nomogram to Predict Frailty for Older Patients Undergoing Abdominal Surgery.Clinical interventions in aging · 2025Article
- Clinicopathologic significance of FUT8, STX4, and calpain2 expression in ovarian cancer.American journal of translational research · 2025Article
- Construction and validation of a prediction model for complications of femoral artery access.Frontiers in surgery · 2025Article
- Predictive modeling of ICU-AW inflammatory factors based on machine learning.BMC neurology · 2024Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The objective is to develop a model based on risk stratification to predict delirium among adult critically ill patients and whether early intervention could be provided for high-risk patients, which could reduce the incidence of delirium.We designed a prospective, observational, single-center study. We examined 11 factors, including age, APACHE-II score, coma, emergency operation, mechanical ventilation (MV), multiple trauma, metabolic acidosis, history of hypertension, delirium and dementia, and application of Dexmedetomidine Hydrochloride. Confusion assessment method for the intensive care unit (CAM-ICU) was performed to screen patients during their ICU stay. Multivariate logistic regression analysis was used to develop the model, and we assessed the predictive ability of the model by using the area under the receiver operating characteristics curve (AUROC).From May 17, 2016 to September 25, 2016, 681 consecutive patients were screened, 61 of whom were excluded. The most frequent reason for exclusion was sustained coma 30 (4.4%), followed by a length of stay in the ICU < 24 hours 18 (2.6%) and delirium before ICU admission 13 (1.9%). Among the remaining 620 patients (including 162 nervous system disease patients), 160 patients (25.8%) developed delirium, and 64 (39.5%) had nervous system disease. The mean age was 55 ± 18 years old, the mean APACHE-II score was 16 ± 4, and 49.2% of them were male. Spearman analysis of nervous system disease and incidence of delirium showed that the correlation coefficient was 0.186 (P < .01). We constructed a prediction model that included 11 risk factors. The AUROC was 0.78 (95% CI 0.72-0.83).We developed the model using 11 related factors to predict delirium in critically ill patients and further determined that prophylaxis with Dexmedetomidine Hydrochloride in delirious ICU patients was beneficial. Patients who suffer from nervous system disease are at a higher incidence of delirium, and corresponding measures should be used for prevention.
trial registrationChiCTR-OOC-16008535.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.