Delirium: Comparison of four predictive models in hospitalized critically ill elderly patients

Delirium, a cognitive and behavioral disorder affecting more than one third of all hospitalized elderly patients, is often misdiagnosed or unrecognized by caregivers, leading to higher patient morbidity and mortality rates. Prediction of the disorder, based on known predisposing and precipitating risk factors, can be used to target susceptible patients for prevention and early intervention. Predictive models need to be evaluated for clinical application and predictive value. Therefore, in this study, four predictive models were applied on a case-by-case basis to an elderly sample of 10 delirious patients and 10 nondelirious patients to determine sensitivity, specificity, and predictive values in a critical care setting. Results indicated six individual significant variables in these models: age, infection, dementia, blood urea nitrogen-to-creatinine ratio, severe illness, and comorbidity. A final multivariate model, derived from all variables, exhibited a sensitivity of 100% and specificity of 90% in predicting delirium in this study. Further studies are needed to substantiate these results. Then, identified risk factors can be incorporated into delirium prevention protocols for use by nurses at the bedside.