Publication
Title
Multinational development and validation of an early prediction model for delirium in ICU patients
Author
Abstract
Delirium incidence in intensive care unit (ICU) patients is high and associated with poor outcome. Identification of high-risk patients may facilitate its prevention. To develop and validate a model based on data available at ICU admission to predict delirium development during a patient's complete ICU stay and to determine the predictive value of this model in relation to the time of delirium development. Prospective cohort study in 13 ICUs from seven countries. Multiple logistic regression analysis was used to develop the early prediction (E-PRE-DELIRIC) model on data of the first two-thirds and validated on data of the last one-third of the patients from every participating ICU. In total, 2914 patients were included. Delirium incidence was 23.6 %. The E-PRE-DELIRIC model consists of nine predictors assessed at ICU admission: age, history of cognitive impairment, history of alcohol abuse, blood urea nitrogen, admission category, urgent admission, mean arterial blood pressure, use of corticosteroids, and respiratory failure. The area under the receiver operating characteristic curve (AUROC) was 0.76 [95 % confidence interval (CI) 0.73-0.77] in the development dataset and 0.75 (95 % CI 0.71-0.79) in the validation dataset. The model was well calibrated. AUROC increased from 0.70 (95 % CI 0.67-0.74), for delirium that developed < 2 days, to 0.81 (95 % CI 0.78-0.84), for delirium that developed > 6 days. Patients' delirium risk for the complete ICU length of stay can be predicted at admission using the E-PRE-DELIRIC model, allowing early preventive interventions aimed to reduce incidence and severity of ICU delirium.
Language
English
Source (journal)
INTENSIVE CARE MEDICINE
Publication
2015
Volume/pages
41:6(2015), p. 1048-1056
ISI
000356801200009
Full text (Publishers DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 03.09.2015
Last edited 23.05.2017
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