Lookup NU author(s): Dr Daniel Davis,
Dr Blossom Stephan,
Professor Fiona Matthews,
Professor Carol Brayne
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Background: In the general population, the epidemiological relationships between delirium and adverse outcomes are not well defined. The aims of this study were to: (1) construct an algorithm for the diagnosis of delirium using the Geriatric Mental State (GMS) examination; (2) test the criterion validity of this algorithm against mortality and dementia risk; (3) report the age-specific prevalence of delirium as determined by this algorithm.Methods: Participant and informant data in a randomly weighted subsample of the Cognitive Function and Ageing Study were taken from a standardized assessment battery. The algorithmic definition of delirium was based on the DSM-IV classification. Outcomes were: proportional hazard ratios for death; odds ratios of dementia at 2-year follow-up.Results: Data from 2197 persons (representative of 13,004) were used, median age 77 years, 64% women. Study-defined delirium was associated with a new dementia diagnosis at two years (OR 8.82, 95% CI 2.76 to 28.2) and death (HR 1.28, 95% CI 1.03 to 1.60), even after adjustment for acute illness severity. Similar associations were seen for study-defined subsyndromal delirium. Age-specific prevalence as determined by the algorithm increased with age from 1.8% in the 65-69 year age group to 10.1% in the >= 85 age group (p < 0.01 for trend). For study-defined subsyndromal delirium, age-specific period prevalence ranged from 8.2% (65-69 years) to 36.1% (>= 85 years).Conclusions: These results demonstrate the possibility of constructing an algorithmic diagnosis for study-defined delirium using data from the GMS schedule, with predictive criterion validity for mortality and dementia risk. These are the first population-based analyses able to account prospectively for both illness severity and an earlier study diagnosis of dementia.
Author(s): Davis DHJ, Barnes LE, Stephan BCM, MacLullich AMJ, Meagher D, Copeland J, Matthews FE, Brayne C, on behalf of the MRC Cognitive Function and Ageing Study
Publication type: Article
Publication status: Published
Journal: BMC Geriatrics
Online publication date: 28/07/2014
Acceptance date: 14/07/2014
Date deposited: 28/09/2015
ISSN (electronic): 1471-2318
Publisher: BioMed Central Ltd
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