OBJECTIVES: To explore the application of existing classifications of mild cognitive impairment (MCI) and associated states in a large population sample. DESIGN: Prospective cohort study, baseline phase (cross-sectional analysis). SETTING: Large-scale multicenter study in the United Kingdom. PARTICIPANTS: Thirteen thousand four individuals aged 65 and older from the Medical Research Council Cognitive Function and Aging Study. From this, a subsample of 2,640 individuals was selected and completed a more-detailed cognitive assessment. MEASUREMENTS: Information on sociodemographic status, general health, cognitive impairment (measured using the Mini-Mental State Examination), and functional ability was collected in a structured interview at baseline. The Geriatric Mental State Automated Geriatric Examination for Computer-Assisted Taxonomy and the Cambridge Cognitive Examination were used in assessment to determine cognitive status. Using a systematic literature review to collect all symptom classifications for nonnormal dementia states, these were then operationalized retrospectively. Each participant was classified according to each. RESULTS: Population prevalence estimates were variable (range 0.1-42%), reflecting differences in the focus and content of each state. Limited overlap existed between states such that many individuals were concurrently classified as normal and impaired. This highlights the heterogeneity in classification as captured using different definitions. CONCLUSION: Classification of cognitively impaired and cognitively normal individuals is dependent on the way criteria are defined and operationalized. Each classification captures a unique group of individuals, with little concordance. Given the importance of early detection of dementia and the calls for screening, and recruitment into pharmacological trials of cognitively impaired individuals, there is an urgent need for an agreed-upon standard MCI case definition to use as a criterion standard.
OBJECTIVES: To explore the application of existing classifications of mild cognitive impairment (MCI) and associated states in a large population sample. DESIGN: Prospective cohort study, baseline phase (cross-sectional analysis). SETTING: Large-scale multicenter study in the United Kingdom. PARTICIPANTS: Thirteen thousand four individuals aged 65 and older from the Medical Research Council Cognitive Function and Aging Study. From this, a subsample of 2,640 individuals was selected and completed a more-detailed cognitive assessment. MEASUREMENTS: Information on sociodemographic status, general health, cognitive impairment (measured using the Mini-Mental State Examination), and functional ability was collected in a structured interview at baseline. The Geriatric Mental State Automated Geriatric Examination for Computer-Assisted Taxonomy and the Cambridge Cognitive Examination were used in assessment to determine cognitive status. Using a systematic literature review to collect all symptom classifications for nonnormal dementia states, these were then operationalized retrospectively. Each participant was classified according to each. RESULTS: Population prevalence estimates were variable (range 0.1-42%), reflecting differences in the focus and content of each state. Limited overlap existed between states such that many individuals were concurrently classified as normal and impaired. This highlights the heterogeneity in classification as captured using different definitions. CONCLUSION: Classification of cognitively impaired and cognitively normal individuals is dependent on the way criteria are defined and operationalized. Each classification captures a unique group of individuals, with little concordance. Given the importance of early detection of dementia and the calls for screening, and recruitment into pharmacological trials of cognitively impaired individuals, there is an urgent need for an agreed-upon standard MCI case definition to use as a criterion standard.
Authors: Emily H Trittschuh; Paul K Crane; Eric B Larson; Brenna Cholerton; Wayne C McCormick; Susan M McCurry; James D Bowen; Laura D Baker; Suzanne Craft Journal: J Alzheimers Dis Date: 2011 Impact factor: 4.472
Authors: Ingrid Arevalo-Rodriguez; Nadja Smailagic; Marta Roqué I Figuls; Agustín Ciapponi; Erick Sanchez-Perez; Antri Giannakou; Olga L Pedraza; Xavier Bonfill Cosp; Sarah Cullum Journal: Cochrane Database Syst Rev Date: 2015-03-05
Authors: Fred Andersen; Torgeir A Engstad; Bjørn Straume; Matti Viitanen; Dag S Halvorsen; Samuel Hykkerud; Kjell Sjøbrend Journal: BMC Med Res Methodol Date: 2010-04-29 Impact factor: 4.615