Predicting delirium: a review of risk-stratification models

Background: Delirium is a common condition in hospitalized patients and is associated with multiple adverse outcomes. There is increasing evidence to support interventions that prevent delirium, so the identification of patients at high risk is of significant clinical value. Numerous risk factors have been identified, including both premorbid patient characteristics and acute precipitants. Despite this, predicting the occurrence of delirium remains a clinical challenge. Objective: This article reviews studies of validated risk-stratification models for delirium. We discuss possible barriers to use of these models and future directions for research. Methods: A comprehensive review of the literature was completed using PubMed and Embase. The resulting citations were filtered in a structured process. Inclusion criteria were original research, adult medical inpatient population and presence of a validation group in the study design. Results: Ten cohort studies met inclusion criteria. The quality of the studies was moderate to good. All studies proposed models using clinical data to predict the risk of patients' developing delirium. Conclusion: The most common risk factors identified were preexisting cognitive impairment, medical comorbidity, elevated Blood Urea Nitrogen, and impairment in activities of daily living. While multiple validated predictive models exist, there is substantial heterogeneity between models, and only one replication study has been performed. In addition, difficulties in implementation may be a barrier to broader use of these models. There is limited support for an accurate and reliable tool to predict inpatient delirium. Further research is needed in this clinically important area. (C) 2015 Elsevier Inc. All rights reserved.