Open Access Open Badges Research article

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)

Daniel HJ Davis127*, Linda E Barnes1, Blossom CM Stephan3, Alasdair MJ MacLullich2, David Meagher4, John Copeland5, Fiona E Matthews6, Carol Brayne1 and on behalf of the MRC Cognitive Function and Ageing Study

Author Affiliations

1 Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK

2 University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK

3 Institute of Health and Society, Newcastle University, Newcastle, UK

4 Graduate Entry Medical School, University of Limerick, Limerick, Ireland

5 Department of Psychiatry, University of Liverpool, Liverpool, UK

6 MRC Biostatistics Unit, Cambridge, UK

7 MRC Unit for Lifelong Health and Ageing, University College London, 33 Bedford Place, London WC1B 5JU, UK

For all author emails, please log on.

BMC Geriatrics 2014, 14:87  doi:10.1186/1471-2318-14-87

Published: 28 July 2014



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.


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.


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 ā‰„85 age group (pā€‰<ā€‰0.01 for trend). For study-defined subsyndromal delirium, age-specific period prevalence ranged from 8.2% (65-69 years) to 36.1% (ā‰„85 years).


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.

Delirium; Dementia; Population; Epidemiology; Algorithm diagnosis