title: 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).
abstract: 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.
authors: Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. daniel.davis@ucl.ac.uk.
authors: Daniel H J
authors: DH
authors: Davis
authors: Linda E
authors: LE
authors: Barnes
authors: Blossom C M
authors: BC
authors: Stephan
authors: Alasdair M J
authors: AM
authors: MacLullich
authors: David
authors: D
authors: Meagher
authors: John
authors: J
authors: Copeland
authors: Fiona E
authors: FE
authors: Matthews
authors: Carol
authors: C
authors: Brayne
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology / Q000523:psychology*; D035843:Biomedical Research / Q000379:methods*; D003071:Cognition / Q000502:physiology*; D015331:Cohort Studies; D003693:Delirium / Q000175:diagnosis / Q000453:epidemiology* / Q000523:psychology*; D005260:Female; D006801:Humans; D008297:Male; D011159:Population Surveillance / Q000379:methods*; D006113:United Kingdom / Q000453:epidemiology