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)
Overview
Authors
Affiliations
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.
Gerakios F, Yarnall A, Bate G, Wright L, Davis D, Stephan B Age Ageing. 2024; 53(3).
PMID: 38497236 PMC: 10945294. DOI: 10.1093/ageing/afae046.
Russell G, Rana N, Watts R, Roshny S, Siddiqi N, Rose L Age Ageing. 2022; 51(11).
PMID: 36434799 PMC: 9701105. DOI: 10.1093/ageing/afac267.
Urinary Tract Infection in Parkinson's Disease.
Hogg E, Frank S, Oft J, Benway B, Rashid M, Lahiri S J Parkinsons Dis. 2022; 12(3):743-757.
PMID: 35147552 PMC: 9108555. DOI: 10.3233/JPD-213103.
Gao L, Gaba A, Li P, Saxena R, Scheer F, Akeju O J Sport Health Sci. 2021; 12(3):312-323.
PMID: 34915199 PMC: 10199142. DOI: 10.1016/j.jshs.2021.12.002.
Ulsa M, Xi Z, Li P, Gaba A, Wong P, Saxena R J Gerontol A Biol Sci Med Sci. 2021; 77(3):507-516.
PMID: 34558609 PMC: 8893188. DOI: 10.1093/gerona/glab272.