Dataset Information

Application of neuropsychological criteria to classify mild cognitive impairment in the active study.

ABSTRACT: Objective: Comprehensive neuropsychological criteria (NP criteria) for mild cognitive impairment (MCI) has reduced diagnostic errors and better predicted progression to dementia than conventional MCI criteria that rely on a single impaired score and/or subjective report. This study aimed to implement an actuarial approach to classifying MCI in the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study. Method: ACTIVE study participants (N = 2,755) were classified as cognitively normal (CN) or as having MCI using NP criteria. Estimated proportion of MCI participants and reversion rates were examined as well as baseline characteristics by MCI subtype. Mixed effect models examined associations of MCI subtype with 10-year trajectories of self-reported independence and difficulty performing instrumental activities of daily living (IADLs). Results: The proportion of MCI participants was estimated to be 18.8%. Of those with MCI at baseline, 19.2% reverted to CN status for all subsequent visits. At baseline, the multidomain-amnestic MCI group generally had the greatest breadth and depth of cognitive impairment and reported the most IADL difficulty. Longitudinally, MCI participants showed faster IADL decline than CN participants (multidomain-amnestic MCI > single domain-amnestic MCI > nonamnestic MCI). Conclusion: NP criteria identified a proportion of MCI and reversion rate within ACTIVE that is consistent with prior studies involving community-dwelling samples. The pattern of everyday functioning change suggests that being classified as MCI, particularly amnestic MCI, is predictive of future loss of independence. Future work will apply these classifications in ACTIVE to better understand the relationships between MCI and health, social, and cognitive intervention-related factors. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

SUBMITTER: Thomas KR

PROVIDER: S-EPMC8376229 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:We compared two methods of diagnosing mild cognitive impairment (MCI): conventional Petersen/Winblad criteria as operationalized by the Alzheimer's Disease Neuroimaging Initiative (ADNI) and an actuarial neuropsychological method put forward by Jak and Bondi designed to balance sensitivity and reliability. 1,150 ADNI participants were diagnosed at baseline as cognitively normal (CN) or MCI via ADNI criteria (MCI: n = 846; CN: n = 304) or Jak/Bondi criteria (MCI: n = 401; CN: n = 749), and the two MCI samples were submitted to cluster and discriminant function analyses. Resulting cluster groups were then compared and further examined for APOE allelic frequencies, cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarker levels, and clinical outcomes. Results revealed that both criteria produced a mildly impaired Amnestic subtype and a more severely impaired Dysexecutive/Mixed subtype. The neuropsychological Jak/Bondi criteria uniquely yielded a third Impaired Language subtype, whereas conventional Petersen/Winblad ADNI criteria produced a third subtype comprising nearly one-third of the sample that performed within normal limits across the cognitive measures, suggesting this method's susceptibility to false positive diagnoses. MCI participants diagnosed via neuropsychological criteria yielded dissociable cognitive phenotypes, significant CSF AD biomarker associations, more stable diagnoses, and identified greater percentages of participants who progressed to dementia than conventional MCI diagnostic criteria. Importantly, the actuarial neuropsychological method did not produce a subtype that performed within normal limits on the cognitive testing, unlike the conventional diagnostic method. Findings support the need for refinement of MCI diagnoses to incorporate more comprehensive neuropsychological methods, with resulting gains in empirical characterization of specific cognitive phenotypes, biomarker associations, stability of diagnoses, and prediction of progression. Refinement of MCI diagnostic methods may also yield gains in biomarker and clinical trial study findings because of improvements in sample compositions of 'true positive' cases and removal of 'false positive' cases.

Dataset Information

Application of neuropsychological criteria to classify mild cognitive impairment in the active study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets