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The descriptive epidemiology of delirium symptoms in a large population-based cohort study: results from the medical research council cognitive function and ageing study (MRC CFAS)
Davis, Daniel; Barnes, Linda E.; Blossom, Stephan; MacLullich, Alasdair J.; Meagher, David; Copeland, John; Matthews, Fiona E.; Brayne, Carol
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.
Keyword(s): delirium; dementia; population; epidemiology; algorithm diagnosis
Publication Date:
Type: Journal article
Peer-Reviewed: Yes
Language(s): English
Institution: University of Limerick
Citation(s): BMC Geriatrics;14:87
Publisher(s): BioMed Central
First Indexed: 2014-11-26 05:25:29 Last Updated: 2018-07-08 06:29:44