Making advances in delirium research: coupling delirium outcomes research and data sharing

Abstract

Understanding and improving the current management of delirium in critically ill patients has become a major challenge for clinicians at the bedside and researchers. In the past decade significant advances have been made increasing our knowledge on the epidemiology, clinical phenotype, diagnosis, prevention, treatment, and risk assessment of delirium [1]. As clinicians in the intensive care unit (ICU), being able to predict the occurrence of delirium early in the course of critical illness may be extremely useful for the implementation of preventive measures or to design interventions for preemptive treatment of high-risk individuals. In a recent study Wassenaar et al. [2] demonstrated the ability to predict delirium with a relatively straightforward model for implementation at ICU admission.Before publishing the E-PRE-DELIRIC, the authors planned and realized a series of rigorous studies. In their first study, the authors developed the PREdiction of DELIRium for Intensive Care patients (PRE-DELIRIC) model for prediction of delirium based on variables readily available in the first 24 h after ICU admission. The authors then temporally validated it in a second prospective cohort in the same hospital and finally validated it externally in four other Dutch hospitals. Prevalence of delirium varied between 25.5 and 36.8 %. Risk factors were selected on the basis of a systematic review [3]. Of the 25 potential risk factors, ten were retained (Table 1). The area under receiver operating characteristics curve (AUROC) of pooled data varied for development (AUROC = 0.86), temporal validation (AUROC = 0.89), and external validation (AUROC = 0.84), resulting in an AUROC of 0.85.In a second study [4], the PRE-DELIRIC was recalibrated in eight ICUs from six countries; the median delirium incidence was 22.5 % (IQR 12.8-36.6 %). The incidence of the ten predictors differed significantly between centers, but the AUROC of the eight participating centers remained good at 0.77 [95 % confidence interval (CI) 0.74-0.79].In this third prospective cohort study in 13 ICUs from seven countries [2], the authors enrolled 2914 patients to develop and validate a predictive model for ICU delirium based on data available at ICU admission. Multiple logistic regression analysis was used to develop the model on data of the first two-thirds and validated on data of the last one-third of the patients from every participating ICU. The incidence of delirium was 24.5 % in the development cohort (1962 patients), 21.8 % in the validation cohort (952 patients), and 23.6 % in the entire study population. The AUROC was 0.76 (95 % CI

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