title: Potential Value of Impaired Cognition in Stroke Prediction: A U.K. Population-Based Study.
abstract: OBJECTIVE
  To determine whether the association between impaired cognition and greater risk of incident stroke is also observed when cognitive impairment is defined using different criteria for mild cognitive impairment (MCI).
  
  
  METHODS
  Prospective cohort study with 10 years of follow-up.
  
  
  METHODS
  Large multicentre study in the United Kingdom.
  
  
  METHODS
  Individuals (aged 64-105) from the Medical Research Council Cognitive Function and Ageing Study (N = 13,004). From this, a subsample of 2,640 individuals was selected based on age, center, and cognitive ability to undergo a detailed cognitive assessment.
  
  
  METHODS
  Information on sociodemographic characteristics, health, cognition, and functional ability was collected in an interview. The Geriatric Mental State Automated Geriatric Examination for Computer Assisted Taxonomy and the Cambridge Cognitive Examination were used to determine cognitive status. Stroke incidence was derived from self-report, informant report, and death certificates. Participants were divided into no, mild, moderate, and severe cognitive impairment according to their baseline Mini-Mental State Examination (MMSE) score. MCI criteria were used to classify persons into four groups: no cognitive impairment, MCI, severe impairment (i.e. other cognitive impairment no dementia: OCIND) and dementia.
  
  
  RESULTS
  Over 10 years, 703 incident strokes occurred. Lower MMSE score at baseline was associated with greater risk of incident stroke. When cognitive status was determined according to MCI criteria, those with severe impairment (odds ratio (OR) = 1.5, 95% confidence interval (CI) = 1.0-2.2) and dementia (OR = 2.6, 95% CI = 1.6-3.4) had a significantly greater risk of stroke than those with no cognitive impairment.
  
  
  CONCLUSIONS
  Criteria for MCI, defined using MMSE scores or clinical criteria, can capture individuals at greater stroke risk. The results highlight the need to focus on stroke risk in individuals even with MCI.
authors.affiliation: Newcastle University Institute of Ageing, Newcastle University, Newcastle upon Tyne, UK.|Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK.
authors.forename: Blossom C M
authors.initials: BCM
authors.lastname: Stephan
authors.affiliation: School of Health Sciences, University of East Anglia, Norwich, UK.
authors.forename: Kathryn
authors.initials: K
authors.lastname: Richardson
authors.affiliation: School of Health Sciences, University of East Anglia, Norwich, UK.
authors.forename: George M
authors.initials: GM
authors.lastname: Savva
authors.affiliation: Newcastle University Institute of Ageing, Newcastle University, Newcastle upon Tyne, UK.
authors.forename: Fiona E
authors.initials: FE
authors.lastname: Matthews
authors.affiliation: Department of Public Health and Primary Care, Cambridge University, Cambridge, UK.
authors.forename: Carol
authors.initials: C
authors.lastname: Brayne
authors.affiliation: University of Western Ontario, London, Canada.
authors.forename: Vladimir
authors.initials: V
authors.lastname: Hachinski
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003071:Cognition; D060825:Cognitive Dysfunction / Q000175:diagnosis / Q000453:epidemiology*; D003704:Dementia / Q000453:epidemiology; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008609:Mental Status Schedule / Q000706:statistics & numerical data*; D011446:Prospective Studies; D020521:Stroke / Q000175:diagnosis / Q000453:epidemiology*; D006113:United Kingdom / Q000453:epidemiology
keywords: cognitive aging; cohort studies; mild cognitive impairment (MCI); risk factors in epidemiology; stroke