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.Electronic supplementary materialThe online version of this article (doi:10.1007/s00134-015-3777-2) contains supplementary material, which is available to authorized users.

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BackgroundAccurate prediction of delirium in the intensive care unit (ICU) may facilitate efficient use of early preventive strategies and stratification of ICU patients by delirium risk in clinical research, but the optimal delirium prediction model to use is unclear. We compared the predictive performance and user convenience of the prediction  model for delirium (PRE-DELIRIC) and early prediction model for delirium (E-PRE-DELIRIC) in ICU patients and determined the value of a two-stage calculation.MethodsThis 7-country, 11-hospital, prospective cohort study evaluated consecutive adults admitted to the ICU who could be reliably assessed for delirium using the Confusion Assessment Method-ICU or the Intensive Care Delirium Screening Checklist. The predictive performance of the models was measured using the area under the receiver operating characteristic curve. Calibration was assessed graphically. A physician questionnaire evaluated user convenience. For the two-stage calculation we used E-PRE-DELIRIC immediately after ICU admission and updated the prediction using PRE-DELIRIC after 24 h.ResultsIn total 2178 patients were included. The area under the receiver operating characteristic curve was significantly greater for PRE-DELIRIC (0.74 (95% confidence interval 0.71–0.76)) compared to E-PRE-DELIRIC (0.68 (95% confidence interval 0.66–0.71)) (z score of − 2.73 (p < 0.01)). Both models were well-calibrated. The sensitivity improved when using the two-stage calculation in low-risk patients. Compared to PRE-DELIRIC, ICU physicians (n = 68) rated the E-PRE-DELIRIC model more feasible.ConclusionsWhile both ICU delirium prediction models have moderate-to-good performance, the PRE-DELIRIC model predicts delirium better. However, ICU physicians rated the user convenience of E-PRE-DELIRIC superior to PRE-DELIRIC. In low-risk patients the delirium prediction further improves after an update with the PRE-DELIRIC model after 24 h.Trial registrationClinicalTrials.gov, NCT02518646. Registered on 21 July 2015.Electronic supplementary materialThe online version of this article (10.1186/s13054-018-2037-6) contains supplementary material, which is available to authorized users.

Background: Delirium is frequently unrecognised. EEG shows slower frequencies (i.e. below 4 Hz) during delirium, which might be useful in improving delirium recognition. We studied the discriminative performance of a brief single-channel EEG recording for delirium detection in an independent cohort of patients. Methods: In this prospective, multicentre study, postoperative patients aged !60 yr were included (n¼159). Before operation and during the first 3 postoperative days, patients underwent a 5-min EEG recording, followed by a videorecorded standardised cognitive assessment. Two or, in case of disagreement, three delirium experts classified each postoperative day based on the video and chart review. Relative delta power (1e4 Hz) was based on 1-min artifact-free EEG. The diagnostic value of the relative delta power was evaluated by the area under the receiver operating characteristic curve (AUROC), using the expert classification as the gold standard. Results: Experts classified 84 (23.3%) postoperative days as either delirium or possible delirium, and 276 (76.7%) nondelirium days. The AUROC of the relative EEG delta power was 0.75 [95% confidence interval (CI) 0.69e0.82]. Exploratory analysis showed that relative power from 1 to 6 Hz had significantly higher AUROC (0.78, 95% CI 0.72e0.84, P¼0.014). Conclusions: Delirium/possible delirium can be detected in older postoperative patients based on a single-channel EEG recording that can be automatically analysed. This objective detection method with a continuous scale instead of a dichotomised outcome is a promising approach for routine detection of delirium. Clinical trial registration: NCT02404181.

The importance of feeling safe in ICU patients should be addressed within the education and clinical practice of ICU nurses, to ensure that they become aware of ICU patients' perception of safety.

Cognitive training exercises used in this study were feasible for intensive care unit patients (including cooperative patients with delirium) and their nurses. More research is needed to determine the clinical effect of the exercises on delirium outcome.

Rationale: Delirium is common in critically ill patients and is associated with deleterious outcomes. Nonpharmacological interventions are recommended in current delirium guidelines, but their effects have not been unequivocally established.Objectives: To determine the effects of a multicomponent nursing intervention program on delirium in the ICU.Methods: A stepped-wedge cluster-randomized controlled trial was conducted in ICUs of 10 centers. Adult critically ill surgical, medical, or trauma patients at high risk of developing delirium were included. A multicomponent nursing intervention program focusing on modifiable risk factors was implemented as standard of care. The primary outcome was the number of delirium-free and coma-free days alive in 28 days after ICU admission.Measurements and Main Results: A total of 1,749 patients were included. Time spent on interventions per 8-hour shift was median (interquartile range) 38 (14-116) minutes in the intervention period and median 32 (13-73) minutes in the control period (P = 0.44). Patients in the intervention period had a median of 23 (4-27) delirium-free and coma-free days alive compared with a median of 23 (5-27) days for patients in the control group (mean difference, 21.21 days; 95% confidence interval, 22.84 to 0.42 d; P = 0.15). In addition, the number of delirium days was similar: median 2 (1-4) days (ratio of medians, 0.90; 95% confidence interval, 0.75 to 1.09; P = 0.27).Conclusions: In this large randomized controlled trial in adult ICU patients, a limited increase in the use of nursing interventions was achieved, and no change in the number of delirium-free and coma-free days alive in 28 days could be determined.Clinical trial registered with www.clinicaltrials.gov (NCT03002701).

It is feasible to use the abbreviated CFQ-14 to measure self-reported cognitive failure in ICU survivors as this questionnaire has a similar performance as the full CFQ-25.