BACKGROUND: delirium is frequently under diagnosed in older hospitalised patients. Predictive models have not been widely incorporated in clinical practice. OBJECTIVE: to develop and validate a predictive score for incident delirium. DESIGN AND SETTING: two consecutive observational prospective cohorts (development and validation) in a university affiliated hospital. SUBJECTS: inpatients 65 years and older. METHODS: in the development cohort patients were assessed within the first 48 h of admission, and every 48 h thereafter, using the confusion assessment method to diagnose delirium and data were collected on comorbidity, illness severity, functional status and laboratory. Delirium predictive score (DPS) was constructed in the development cohort using variables associated with incident delirium in the multivariate analysis (P < 0.05), and then tested in a validation cohort of comparable patients, admitted without delirium. Receiver operating characteristic (ROC) analysis and likelihood ratio (LR) were calculated. RESULTS: the development cohort included 374 patients, incident delirium occurred in 25. After multivariate analysis incident delirium was independently associated with lower functional status (Barthel Index) and a proxy for dehydration (elevated urea to creatinine ratio). Using these variables, DPS was constructed with a performance in the ROC curve area of 0.86 (95% CI: 0.82-0.91) and (-) LR = 0.16 and (+) LR = 3.4. The validation cohort included 104 patients and the performance of the score was ROC 0.78 (95% CI: 0.66-0.90). CONCLUSIONS: This simple predictive model highlights functional status and a proxy for dehydration as a useful tool for identifying older patients that may benefit from close monitoring and preventive care for early diagnosis of delirium.
BACKGROUND:delirium is frequently under diagnosed in older hospitalised patients. Predictive models have not been widely incorporated in clinical practice. OBJECTIVE: to develop and validate a predictive score for incident delirium. DESIGN AND SETTING: two consecutive observational prospective cohorts (development and validation) in a university affiliated hospital. SUBJECTS: inpatients 65 years and older. METHODS: in the development cohort patients were assessed within the first 48 h of admission, and every 48 h thereafter, using the confusion assessment method to diagnose delirium and data were collected on comorbidity, illness severity, functional status and laboratory. Delirium predictive score (DPS) was constructed in the development cohort using variables associated with incident delirium in the multivariate analysis (P < 0.05), and then tested in a validation cohort of comparable patients, admitted without delirium. Receiver operating characteristic (ROC) analysis and likelihood ratio (LR) were calculated. RESULTS: the development cohort included 374 patients, incident delirium occurred in 25. After multivariate analysis incident delirium was independently associated with lower functional status (Barthel Index) and a proxy for dehydration (elevated urea to creatinine ratio). Using these variables, DPS was constructed with a performance in the ROC curve area of 0.86 (95% CI: 0.82-0.91) and (-) LR = 0.16 and (+) LR = 3.4. The validation cohort included 104 patients and the performance of the score was ROC 0.78 (95% CI: 0.66-0.90). CONCLUSIONS: This simple predictive model highlights functional status and a proxy for dehydration as a useful tool for identifying older patients that may benefit from close monitoring and preventive care for early diagnosis of delirium.
Authors: Hugo A J M de Wit; Bjorn Winkens; Carlota Mestres Gonzalvo; Kim P G M Hurkens; Wubbo J Mulder; Rob Janknegt; Frans R Verhey; Paul-Hugo M van der Kuy; Jos M G A Schols Journal: Int J Clin Pharm Date: 2016-05-13
Authors: Mark A Oldham; Keith A Hawkins; David D Yuh; Michael L Dewar; Umer M Darr; Taras Lysyy; Hochang B Lee Journal: Int Psychogeriatr Date: 2015-10-02 Impact factor: 7.191
Authors: Sarah T Pendlebury; Nicola Lovett; Sarah C Smith; Emily Cornish; Ziyah Mehta; Peter M Rothwell Journal: Age Ageing Date: 2016-01 Impact factor: 10.668