To compare validity and reliability of three instruments for detection and assessment of delirium in intensive care unit (ICU) patients. Delirium in critically ill patients is associated with higher mortality, prolonged duration of ICU stay, and greater healthcare costs. Currently, there are several assessment tools available for detection of delirium, but only a few of these assessment systems are developed specifically to screen for delirium in ICU patients. Prospective cohort study. ICU at a university hospital. A total of 156 surgical patients aged ≥60 yrs consecutively admitted to the ICU, with a length of stay of at least 24 hrs. This study was approved by the institutional ethics committee. Trained staff members performed daily and independently the Confusion Assessment Method for the ICU (CAM-ICU), the Nursing Delirium Screening Scale (Nu-DESC), and the Delirium Detection Score (DDS). These evaluations were compared against the reference standard conducted by a delirium expert (blinded to the study), who used delirium criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). Of 156 patients, 63 (40%) were identified as delirious by the reference standard during the study. Using the CAM-ICU and the Nu-DESC, we measured comparable sensitivities (CAM-ICU, 81%; Nu-DESC, 83%). The specificity of the CAM-ICU was significantly higher than that of the Nu-DESC (96% vs. 81%, p < .01). In contrast, the DDS showed poor sensitivity (30%), whereas the specificity was significantly higher compared with the Nu-DESC (DDS, 91%; Nu-DESC, 81%, p < .05). The interrater reliability was “almost perfect” for the CAM-ICU (κ = 0.89) and “substantial” for DDS and Nu-DESC (κ = 0.79, 0.68). The CAM-ICU showed the best validity of the evaluated scales to identify delirium in ICU patients. The Nu-DESC might be an alternative tool for detection of ICU delirium. The DDS should not be used as a screening tool.

Rationale Delirium incidence in intensive care unit (ICU) patients is high and associated with poor outcome. Identification of high-risk patients may facilitate its prevention. Purpose 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. Methods 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. Results 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 6 days. Conclusion 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.

Background and objective Most therapeutic options for postoperative delirium are only symptom oriented; therefore, the best approach remains prevention. The aim of this study was to identify predisposing and precipitating factors for early postoperative delirium. Methods A total of 1002 patients were screened for delirium in an observational, cohort study. Nine hundred and ten patients were observed in the recovery room and 862 patients on the first postoperative day in the ward at the Charité – Universitaetsmedizin, Berlin. Delirium was measured with the nursing delirium screening scale. Risk factors were analysed in a multivariate analysis. Results Delirium was seen in 11.0% of the patients in the recovery room and in 4.2% of the patients on the ward. Delirium in the recovery room was associated with delirium on the ward (McNemar's test P = <0.001). Apart from age and site of surgery, we found the duration of preoperative fluid fasting to be a modifiable precipitating factor for delirium in the recovery room (odds ratio 2.69, 95% confidence interval 1.4–5.2) and on the ward (odds ratio 10.57, 95% confidence interval 1.4–78.6) and the choice of intraoperative opioid for delirium on the ward (odds ratio 2.27, 95% confidence interval 1.0–5.1). Conclusion Duration of preoperative fluid fasting and the choice of intraoperative analgesic are risk factors for postoperative delirium, and their modification provides a promising approach to reduce the incidence of postoperative delirium.

Delirium is often seen in the recovery room and is a predictor for postoperative delirium on the ward. However, monitoring to detect delirium in the recovery room as a basic prerequisite for early intervention is rarely used. The aim of this study was to identify a valid and easy-to-use test for early screening of delirium in the recovery room. One hundred and fifty-four adult patients admitted to the recovery room during regular working hours were included. A screening assessment for delirium was performed in the recovery room by a trained research team at the time when the patient was judged to be 'ready for discharge'. Delirium monitoring was performed with the Confusion Assessment Method (CAM), the Delirium Detection Score (DDS), and the Nursing Delirium Screening Scale (Nu-DESC). The Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV criteria were used as the gold standard. Delirium in the recovery room was seen in 21 patients (14%) with the DSM-IV criteria, in 11 patients (7%) with the CAM, in four patients (3%) with the DDS, and in 37 patients (24%) with the Nu-DESC. Sensitivity and specificity were 0.43 and 0.98 for the CAM, 0.14 and 0.99 for the DDS, and 0.95 and 0.87 for the Nu-DESC, respectively. All scores used were very specific, but the CAM and the DDS were less sensitive compared with the gold standard. Overall, the Nu-DESC was the most sensitive test in the recovery room to detect delirium.

Analgesia, sedation and delirium management are important parts of intensive care treatment as they are relevant for patients' clinical and functional long-term outcome. Previous surveys showed that despite this fact implementation rates are still low. The primary aim of the prospective, observational multicenter study was to investigate the implementation rate of delirium monitoring among intensivists. Secondly, current practice concerning analgesia and sedation monitoring as well as treatment strategies for patients with delirium were assesed. In addition, this study compares perceived and actual practice regarding delirium, sedation and analgesia management. Data were obtained with a two-part, anonymous survey, containing general data from intensive care units in a first part and data referring to individual patients in a second part. Questionnaires from 101 hospitals (part 1) and 868 patients (part 2) were included in data analysis. Fifty-six percent of the intensive care units reported to monitor for delirium in clinical routine. Fourty-four percent reported the use of a validated delirium score. In this respect, the survey suggests an increasing use of delirium assessment tools compared to previous surveys. Nevertheless, part two of the survey revealed that in actual practice 73% of included patients were not monitored with a validated score. Furthermore, we observed a trend towards moderate or deep sedation which is contradicting to guideline-recommendations. Every fifth patient was suffering from pain. The implementation rate of adequate pain-assessment tools for mechanically ventilated and sedated patients was low (30%). In conclusion, further efforts are necessary to implement guideline recommendations into clinical practice. The study was registered (ClinicalTrials.gov identifier: NCT01278524) and approved by the ethical committee.