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

The prevalence of mild cognitive impairment in Gulf War veterans: a follow-up study

Introduction

Gulf War Illness (GWI), also called Chronic Multisymptom Illness (CMI), is a multi-faceted condition that plagues an estimated 250,000 Gulf War (GW) veterans. Symptoms of GWI/CMI include fatigue, pain, and cognitive dysfunction. We previously reported that 12% of a convenience sample of middle aged (median age 52 years) GW veterans met criteria for mild cognitive impairment (MCI), a clinical syndrome most prevalent in older adults (e.g., ≥70 years). The current study sought to replicate and extend this finding.

Methods

We used the actuarial neuropsychological criteria and the Montreal Cognitive Assessment (MoCA) to assess the cognitive status of 952 GW veterans. We also examined regional brain volumes in a subset of GW veterans (n = 368) who had three Tesla magnetic resonance images (MRIs).

Results

We replicated our previous finding of a greater than 10% rate of MCI in four additional cohorts of GW veterans. In the combined sample of 952 GW veterans (median age 51 years at time of cognitive testing), 17% met criteria for MCI. Veterans classified as MCI were more likely to have CMI, history of depression, and prolonged (≥31 days) deployment-related exposures to smoke from oil well fires and chemical nerve agents compared to veterans with unimpaired and intermediate cognitive status. We also replicated our previous finding of hippocampal atrophy in veterans with MCI, and found significant group differences in lateral ventricle volumes.

Discussion

Because MCI increases the risk for late-life dementia and impacts quality of life, it may be prudent to counsel GW veterans with cognitive dysfunction, CMI, history of depression, and high levels of exposures to deployment-related toxicants to adopt lifestyle habits that have been associated with lowering dementia risk. With the Food and Drug Administration's recent approval of and the VA's decision to cover the cost for anti-amyloid β (Aβ) therapies, a logical next step for this research is to determine if GW veterans with MCI have elevated Aβ in their brains.

A Critical Review of Neuropsychological Actuarial Criteria for Mild Cognitive Impairment

BACKGROUND

The concept of mild cognitive impairment (MCI) has evolved since its original conception. So, too, have MCI diagnostic methods, all of which have varying degrees of success in identifying individuals at risk of conversion to dementia. The neuropsychological actuarial method is a straightforward diagnostic approach that has shown promise in large datasets in identifying individuals with MCI who are likely to have progressive courses. This method has been increasingly applied in various iterations and samples, raising questions of how best to apply this method and when caution should be used.

OBJECTIVE

Our objective was to review the literature investigating use of the neuropsychological actuarial method to diagnose MCI to identify strengths and weaknesses of this approach, as well as highlight areas for further research.

METHODS

Databases PubMed and PsychInfo were systematically searched for studies that compared the neuropsychological actuarial method to some other diagnostic method.

RESULTS

We identified 13 articles and extracted relevant study characteristics and findings. Existing literature was reviewed and integrated, with focus on the neuropsychological actuarial method's performance relative to existing diagnostic methods/criteria as well as associations with longitudinal outcomes and biomarkers. Tables with pertinent methodological information and general findings are also provided.

CONCLUSION

The neuropsychological actuarial method to diagnose MCI has shown utility some in large-scale homogenous databases compared to research criteria. However, its standing relative to consensus diagnostic methods is unclear, and emerging evidence suggests the neuropsychological actuarial method may be more prone to diagnostic errors in more demographically diverse populations.

Cognitive Heterogeneity and Risk of Progression in Data-Driven Subtle Cognitive Decline Phenotypes

BACKGROUND

There is increasing recognition of cognitive and pathological heterogeneity in early-stage Alzheimer's disease and other dementias. Data-driven approaches have demonstrated cognitive heterogeneity in those with mild cognitive impairment (MCI), but few studies have examined this heterogeneity and its association with progression to MCI/dementia in cognitively unimpaired (CU) older adults.

OBJECTIVE

We identified cluster-derived subgroups of CU participants based on comprehensive neuropsychological data and compared baseline characteristics and rates of progression to MCI/dementia or a Dementia Rating Scale (DRS) of ≤129 across subgroups.

METHODS

Hierarchical cluster analysis was conducted on individual baseline neuropsychological test scores from 365 CU participants in the UCSD Shiley-Marcos Alzheimer's Disease Research Center longitudinal cohort. Cox regressions examined the risk of progression to consensus diagnosis of MCI or dementia, or to DRS score ≤129, by cluster group.

RESULTS

Cluster analysis identified 5 groups: All-Average (n = 139), Low-Visuospatial (n = 46), Low-Executive (n = 51), Low-Memory/Language (n = 83), and Low-All Domains (n = 46). Subgroups had unique demographic and clinical characteristics. Rates of progression to MCI/dementia or to DRS ≤129 were faster for all subgroups (Low-All Domains progressed the fastest > Low Memory/Language≥Low-Visuospatial and Low-Executive) relative to the All-Average subgroup.

CONCLUSION

Faster progression in the Low-Visuospatial, Low-Executive, and Low-Memory/Language groups compared to the All-Average group suggests that there are multiple pathways and/or unique subtle cognitive decline profiles that ultimately lead to a diagnosis of MCI/dementia. Use of comprehensive neuropsychological test batteries that assess several domains may be a key first step toward an individualized approach to early detection and fewer missed opportunities for early intervention.