Early Functional Limitations in Cognitively Normal Older Adults Predict Diagnostic Conversion to Mild Cognitive Impairment

Abstract

Background and Objectives There is increasing evidence that changes in everyday functional abilities are among the first signs of incipient neurodegenerative disease. The present study sought to examine whether specific types of early functional limitations in cognitively normal older adults are associated with the subsequent development of mild cognitive impairment (MCI), as well as the relative predictive value of self- versus informant-report in predicting diagnostic conversion to MCI. Design Participants received baseline and annual multidisciplinary clinical evaluations including a physical and neurological exam, imaging, lab work, and neuropsychological testing. Setting Data used in this study was collected as part of a longitudinal research cohort at the University of California, Davis Alzheimer’s Disease Center (ADC). Participants Participants (n = 324) were diagnosed as having normal cognition at study baseline, had an informant who could complete informant-based ratings, and had at least one follow-up visit. Measurements Participants and informants each completed The Everyday Cognition (ECog) scale, an instrument designed to measure everyday function across six cognitive domains. Results Both self- and informant-reported functional limitations on the ECog were associated with a significant increase in risk of diagnostic conversion to MCI (informant: HR = 2.0, 95% CI = 1.3–3.2, p = .002), with self-report having a slightly higher hazard ratio (HR = 2.3, 95% CI = 1.4–3.6, p < .001). When controlling for baseline cognitive abilities, the effect remained significant for both self- and informant-reported functional limitations. Conclusion Deficits in everyday memory and executive function domains were the strongest predictors of diagnostic conversion to MCI. These results indicate detection of early functional limitations may be clinically useful in assessing the future risk of developing cognitive impairment in cognitively normal older adults.

The Brain Health Assessment for Detecting and Diagnosing Neurocognitive Disorders

“…Adding the ECog‐12 increased sensitivity from 72% to 82% to detect MCI that was likely to be due to AD, with specificity fixed at 85%. This finding is consistent with previous work showing that the full‐length version of this measure, independent of neuropsychological test performance, aids in predicting who will develop MCI, dementia, and disability . The additional 9 questions, designed to elicit symptoms of less typical presentations of AD and non‐AD disorders, increased the sensitivity minimally beyond the ECog‐12 in this group that was likely to have AD (83%).…”

Function Begets Function and Resilience in Old Age: Is Precision Gerontology Possible?

“…The report in this issue, by Farias and colleagues 22 , presents another distinct, yet related issue. Self-and informant-based changes involving the Everyday Cognition scale, an instrument designed to measure everyday function in six cognitive domains, were associated with a significantly greater risk of diagnostic conversion to mild cognitive impairment (MCI) after controlling for objective cognitive test performance in 324 members of a…”

“…Older adults vary greatly in their capacities to respond effectively to defined stressors as diverse as infection, changes in ambient temperature, dehydration, bedrest, surgery, and anesthesia 17 Aging is a major shared risk factor for geriatric syndromes and chronic diseases of aging As stated in the Geroscience Hypothesis, efforts to target shared biological pathways may help delay the onset and progression of such conditions 18,19 Personal preferences Not only do treatment goals and preferences tend to change with aging, but increasingly they also vary based on differences in individual health considerations and cultural, social, and economic factors 3,20 longitudinal research cohort defined as being cognitively normal at baseline. 22 At first it may not seem that evidence of disability would be observable on self-and informantbased reports long before an expert clinician could diagnose an accepted functional limitation or disease in the form of MCI. Nevertheless, in the case of clinical trials targeting cognition, observers sometimes report functional improvements while objective improvements in formal cognitive testing may not be evident.…”

“…Moreover, in the context of caring for older adults with complex and highly variable multimorbidities, precision medicine must ultimately be transformed into precision care, carefully considering the applicability of each healthcare decision to an individual's unique profile of chronic and subacute conditions, health and functional status, goals, and stated preferences. 3,20 As noted above, the roles of mobility performance measures as strong predictors of future frailty, disability, and mortality have been well established, 13 but two reports published in the Journal 21,22 highlight the importance of considering functional measures involving distinct cognitive domains when seeking to identify subsets of older adults with definable risk profiles for future disabilities and diseases. In evaluating relationships between these various functional constructs and how these may be applied to precision gerontology, it is helpful to consider the findings of such studies within the framework of the Nagi Model of Disablement, first described more than half a century ago 23 (Table 2).…”

Physical Activity and Positive Psychological Well-Being Attributes Among U.S. Latino Older Adults

“…Many studies on physical activity of older adults did not include an older Latino population, but reported key moderating variables (Farias et al, 2017;Kelly, Edney, Moran, Srikanth, & Callisaya, 2016;Murphy, Niemiec, Lyden, & Kratz, 2016;Stephan, Sutin, & Terracciano, 2014). A moderating variable, either quantitative (e.g., satisfaction level) or qualitative (e.g., gender, race), "aff ects the direction and/or strength of the relation between an independent or predictor variable and a dependent or criterion variable" (Baron & Kenny, 1986, p. 1174.…”