Mild cognitive impairment: a cross-national comparison. Issue 9 (16th August 2004)

• Record Type: Journal Article
• Authors: Arnáiz, E; Almkvist, O; Ivnik, R J; Tangalos, E G; Wahlund, L O; Winblad, B; Petersen, R C
• Is Part Of: Journal of neurology, neurosurgery and psychiatry. Volume 75:Issue 9(2004)
• Page Start: 1275
• Page End: 1280
• Publication Date: 2004-08-16
• Subjects: AD, Alzheimer's disease -- AVLT, Auditory Verbal Learning Test -- CDR, Clinical Dementia Rating (scale) -- KI, Karolinska Institute -- MC, Mayo Clinic -- MCFS, Mayo Cognitive Factor Scores -- MCI, mild cognitive impairment -- WAIS-R, Wechsler Adult Intelligence Scale-Revised -- WMS-R, Wechsler Memory Scale-Revised; Keywords: Alzheimer's disease -- mild cognitive impairment -- neuropsychology -- cross-national comparison; Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Psychiatry -- Periodicals; 616.8
• DOI: 10.1136/jnnp.2003.015032
• Languages: English
• ISSNs: 0022-3050

Abstract

Abstract : Objective: The main aim of this collaborative study was to assess the comparability of the most commonly used criteria for mild cognitive impairment (MCI) by comparing the cognitive performance of patients with MCI from the Mayo Clinic (USA) and the Karolinska Institutet (Sweden). Methods: Standardised neuropsychological test scores were used to compare the two samples from the two institutions with regard to the number of cognitive domains in which performance was below 1.5 SD. Possible predictors for the conversion from MCI to Alzheimer's disease (AD) were assessed. Results: When the two institutions were considered together in the Cox proportional hazard model, the number of affected cognitive domains below 1.5 SD was a significant predictor of time to AD diagnosis with age, education, and APOE ε4 genotype entered into the same model as covariates. The number of affected cognitive areas remained as a significant predictor when the institutions were considered separately. The logistic regression model of conversion to AD showed that only tests assessing learning and retention were predictors of developing AD. Conclusions: Differences in population as well as in methodology of case ascertainment as well as other aspects may account for the observed variability between samples of patients with MCI. The number of impaired cognitive factors at baseline can predict the progression from MCI to AD. Furthermore, tests assessing learning and retention are the best predictors for progression to AD.