Recognition of cognitive dysfunction in hospitalised older patients: a flash mob study.

BACKGROUND: It is important that healthcare professionals recognise cognitive dysfunction in hospitalised older patients in order to address associated care needs, such as enhanced involvement of relatives and extra cognitive and functional support. However, studies analysing medical records suggest that healthcare professionals have low awareness of cognitive dysfunction in hospitalised older patients. In this study, we investigated the prevalence of cognitive dysfunction in hospitalised older patients, the percentage of patients in which cognitive dysfunction was recognised by healthcare professionals, and which variables were associated with recognition. METHODS: A multicentre, nationwide, cross-sectional observational study was conducted on a single day using a flash mob study design in thirteen university and general hospitals in the Netherlands. Cognitive function was assessed in hospitalised patients aged ≥ 65 years old, who were admitted to medical and surgical wards. A Mini-Cog score of < 3 out of 5 indicated cognitive dysfunction. The attending nurses and physicians were asked whether they suspected cognitive dysfunction in their patient. Variables associated with recognition of cognitive dysfunction were assessed using multilevel and multivariable logistic regression analyses. RESULTS: 347 of 757 enrolled patients (46%) showed cognitive dysfunction. Cognitive dysfunction was recognised by attending nurses in 137 of 323 patients (42%) and by physicians in 156 patients (48%). In 135 patients (42%), cognitive dysfunction was not recognised by either the attending nurse or physician. Recognition of cognitive dysfunction was better at a lower Mini-Cog score, with the best recognition in patients with the lowest scores. Patients with a Mini-Cog score < 3 were best recognised in the geriatric department (69% by nurses and 72% by physicians). CONCLUSION: Cognitive dysfunction is common in hospitalised older patients and is poorly recognised by healthcare professionals. This study highlights the need to improve recognition of cognitive dysfunction in hospitalised older patients, particularly in individuals with less apparent cognitive dysfunction. The high proportion of older patients with cognitive dysfunction suggests that it may be beneficial to provide care tailored to cognitive dysfunction for all hospitalised older patients.

DeltaScan for the Assessment of Acute Encephalopathy and Delirium in ICU and non-ICU Patients, a Prospective Cross-Sectional Multicenter Validation Study.

OBJECTIVES: To measure the diagnostic accuracy of DeltaScan: a portable real-time brain state monitor for identifying delirium, a manifestation of acute encephalopathy (AE) detectable by polymorphic delta activity (PDA) in single-channel electroencephalograms (EEGs). DESIGN: Prospective cross-sectional study. SETTING: Six Intensive Care Units (ICU's) and 17 non-ICU departments, including a psychiatric department across 10 Dutch hospitals. PARTICIPANTS: 494 patients, median age 75 (IQR:64-87), 53% male, 46% in ICUs, 29% delirious. MEASUREMENTS: DeltaScan recorded 4-minute EEGs, using an algorithm to select the first 96 seconds of artifact-free data for PDA detection. This algorithm was trained and calibrated on two independent datasets. METHODS: Initial validation of the algorithm for AE involved comparing its output with an expert EEG panel's visual inspection. The primary objective was to assess DeltaScan's accuracy in identifying delirium against a delirium expert panel's consensus. RESULTS: DeltaScan had a 99% success rate, rejecting 6 of the 494 EEG's due to artifacts. Performance showed and an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.86 (95% CI: 0.83-0.90) for AE (sensitivity: 0.75, 95%CI=0.68-0.81, specificity: 0.87 95%CI=0.83-0.91. The AUC was 0.71 for delirium (95%CI=0.66-0.75, sensitivity: 0.61 95%CI=0.52-0.69, specificity: 72, 95%CI=0.67-0.77). Our validation aim was an NPV for delirium above 0.80 which proved to be 0.82 (95%CI: 0.77-0.86). Among 84 non-delirious psychiatric patients, DeltaScan differentiated delirium from other disorders with a 94% (95%CI: 87-98%) specificity. CONCLUSIONS: DeltaScan can diagnose AE at bedside and shows a clear relationship with clinical delirium. Further research is required to explore its role in predicting delirium-related outcomes.