Literature DB >> 34864658

Diagnosing Mild Cognitive Impairment Among Racially Diverse Older Adults: Comparison of Consensus, Actuarial, and Statistical Methods.

Kathryn N Devlin1, Laura Brennan2, Laura Saad3, Tania Giovannetti4, Roy H Hamilton5,6, David A Wolk5,6, Sharon X Xie5,7, Dawn Mechanic-Hamilton5,6.   

Abstract

BACKGROUND: Actuarial and statistical methods have been proposed as alternatives to conventional methods of diagnosing mild cognitive impairment (MCI), with the aim of enhancing diagnostic and prognostic validity, but have not been compared in racially diverse samples.
OBJECTIVE: We compared the agreement of consensus, actuarial, and statistical MCI diagnostic methods, and their relationship to race and prognostic indicators, among diverse older adults.
METHODS: Participants (N = 354; M age = 71; 68% White, 29% Black) were diagnosed with MCI or normal cognition (NC) according to clinical consensus, actuarial neuropsychological criteria (Jak/Bondi), and latent class analysis (LCA). We examined associations with race/ethnicity, longitudinal cognitive and functional change, and incident dementia.
RESULTS: MCI rates by consensus, actuarial criteria, and LCA were 44%, 53%, and 41%, respectively. LCA identified three MCI subtypes (memory; memory/language; memory/executive) and two NC classes (low normal; high normal). Diagnostic agreement was substantial, but agreement of the actuarial method with consensus and LCA was weaker than the agreement between consensus and LCA. Among cases classified as MCI by actuarial criteria only, Black participants were over-represented, and outcomes were generally similar to those of NC participants. Consensus diagnoses best predicted longitudinal outcomes overall, whereas actuarial diagnoses best predicted longitudinal functional change among Black participants.
CONCLUSION: Consensus diagnoses optimize specificity in predicting dementia, but among Black older adults, actuarial diagnoses may be more sensitive to early signs of decline. Results highlight the need for cross-cultural validity in MCI diagnosis and should be explored in community- and population-based samples.

Entities:  

Keywords:  Actuarial analysis; Alzheimer’s disease; cognitive aging; early diagnosis; latent class analysis; memory disorders; mild cognitive impairment; minority health; race factors; statistical modelszzm321990

Mesh:

Year:  2022        PMID: 34864658      PMCID: PMC8820242          DOI: 10.3233/JAD-210455

Source DB:  PubMed          Journal:  J Alzheimers Dis        ISSN: 1387-2877            Impact factor:   4.472


  81 in total

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Authors:  Emily C Edmonds; Lisa Delano-Wood; Lindsay R Clark; Amy J Jak; Daniel A Nation; Carrie R McDonald; David J Libon; Rhoda Au; Douglas Galasko; David P Salmon; Mark W Bondi
Journal:  Alzheimers Dement       Date:  2014-05-22       Impact factor: 21.566

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Journal:  Neuropsychol Rev       Date:  2008-09-25       Impact factor: 7.444

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7.  2021 Alzheimer's disease facts and figures.

Authors: 
Journal:  Alzheimers Dement       Date:  2021-03-23       Impact factor: 21.566

8.  Class-Specific Incidence of All-Cause Dementia and Alzheimer's Disease: A Latent Class Approach.

Authors:  Andrea R Zammit; Charles B Hall; Mindy J Katz; Graciela Muniz-Terrera; Ali Ezzati; David A Bennett; Richard B Lipton
Journal:  J Alzheimers Dis       Date:  2018       Impact factor: 4.472

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Journal:  J Int Neuropsychol Soc       Date:  2007-05       Impact factor: 2.892

10.  Profiles of Mild Cognitive Impairment (MCI) in the Elderly.

Authors:  Herminia Peraita; José Chacón; Carmen Díaz-Mardomingo; Rosario Martínez-Arias
Journal:  Span J Psychol       Date:  2015-11-20       Impact factor: 1.264

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