Dataset Information

Diagnostic Precision in the Detection of Mild Cognitive Impairment: A Comparison of Two Approaches.

ABSTRACT:

Objective

This study compared diagnostic rates and clinical predictors of discrepancies between diagnoses conferred via: 1) a comprehensive neuropsychological evaluation and National Institute on Aging-Alzheimer's Association (NIA-AA) criteria versus 2) a cognitive screener and Diagnostic Statistical Manual of Mental Disorders (DSM-5) criteria.

Design

Cross-sectional examination of baseline data from the Prevention of Alzheimer's dementia (AD) using Cognitive remediation and transcranial direct current stimulation in Mild Cognitive Impairment (MCI) and Depression (PACt-MD; ClinicalTrials.gov Identifier: NCT02386670) trial.

Setting

Five geriatric psychiatry and memory clinics located at academic hospitals affiliated with the Department of Psychiatry, University of Toronto.

Participants

Older adults (N = 431) with a history of major depressive disorder (MDD) in remission, MCI, or both.

Measurements

Main outcome was a comparison of NIA-AA diagnostic rates of MCI or dementia versus DSM-5 rates of mild or major neurocognitive disorder. Secondary analyses examined demographic, race, gender, premorbid intellectual ability, psychosocial, health-related, and genetic predictors of discrepancy between DSM-5 and NIA-AA diagnoses.

Results

There were 103 (23.8%) discrepant cases, with most (91; 88.3%) of these discrepant cases reflecting more impairment with the detailed neuropsychological testing and NIA-AA criteria. Discrepancies were more likely in individuals with a history of MDD or who had at least one ApoE4 allele.

Conclusion

The NIA-AA criteria, in conjunction with comprehensive neuropsychological testing, identified a greater prevalence of cognitive impairment than DSM-5 criteria, in conjunction with the Montreal Cognitive Assessment. Detailed neuropsychological evaluations are recommended for older adults who have a history of MDD or a genetic vulnerability to dementia.

SUBMITTER: Weinstein AM

PROVIDER: S-EPMC8720569 | biostudies-literature |

REPOSITORIES: biostudies-literature

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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.