• A Wassenaar, M van den Boogaard, T van Achterberg, A J C Slooter, M A Kuiper, M E Hoogendoorn, K S Simons, E Maseda, N Pinto, C Jones, A Luetz, A Schandl, W Verbrugghe, L M Aitken, F M P van Haren, A R T D... more onders, L Schoonhoven, and P Pickkers. less
• Scientific Institute for Quality of Healthcare, Radboud Institute for Health Sciences, Radboud university medical center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands, annelies.wassenaar@radboudumc.nl... more . less
• Intensive Care Med. 2015 Jun 1; 41 (6): 1048-56.

RationaleDelirium incidence in intensive care unit (ICU) patients is high and associated with poor outcome. Identification of high-risk patients may facilitate its prevention.PurposeTo 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.MethodsProspective 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.ResultsIn 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.ConclusionPatients' 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.

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