Using Varying Diagnostic Criteria to Examine Mild Cognitive Impairment Prevalence and Predict Dementia Incidence in a Community-Based Sample

Article type: Research Article

Authors: Robertson, Kayela^{a; *} | Larson, Eric B.^b | Crane, Paul K.^c | Cholerton, Brenna^d | Craft, Suzanne^e | McCormick, Wayne C.^c | McCurry, Susan M.^f | Bowen, James D.^g | Baker, Laura D.^e | Trittschuh, Emily H.^{a; h}

Affiliations: [a] Geriatric Research, Education, and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, WA, USA | [b] Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA | [c] Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA | [d] Department of Pathology, Stanford University, Palo Alto, CA, USA | [e] Sticht Center on Aging, Department of Internal Medicine, Wake Forest University, Winston-Salem, NC, USA | [f] Department of Psychosocial and Community Health, University of Washington School of Nursing, Seattle, WA, USA | [g] Swedish Neuroscience Institute, Swedish Medical Center, Seattle, WA, USA | [h] Department of Psychiatry and Behavioral Science, University of Washington School of Medicine, Seattle, WA, USA

Correspondence: [*] Correspondence to: Kayela Robertson, PhD, VA Puget Sound Health Care System, GRECC-S-182, 1660 S Columbian Way, Seattle, WA 98108, USA. Tel.: +1 206 277 1825; E-mail: kayela.robertson@va.gov.

Abstract: Lack of a unitary operational definition of mild cognitive impairment (MCI) has resulted in mixed prevalence rates and unclear predictive validity regarding conversion to dementia and likelihood of reversion. We examined 1,721 nondemented participants aged 65 and older from the Adult Changes in Thought (ACT) community-based cohort. Participants were followed longitudinally through biennial visits (average years assessed = 5.38). Categorization of MCI was based on: 1) deviation of neuropsychological test scores from a benchmark based on either standard or individualized expectations of a participant’s mean premorbid cognitive ability, and 2) cutoff for impairment (1.0 versus 1.5 standard deviations [sd] below benchmark). MCI prevalence ranged from 56–92%; using individualized benchmarks and less stringent cutoffs produced higher rates. During follow-up, 17% of the cohort developed dementia. Examination of sensitivity, specificity, and predictive validity revealed that the criterion of 1.5 sd from the standardized benchmark was optimal, but still had limited predictive validity. Participants meeting this criterion at their first visit were three times more likely to develop dementia and this increased to seven times if participants had this diagnosis at the second timepoint as well. Those who did not have an MCI diagnosis at their first visit, but did at their second, had a significant increase of risk (but to a lesser extent than those diagnosed at both visits), while those who had an MCI diagnosis at their first visit, but not their second, did not have a significantly increased risk. These results highlight how assessing MCI stability greatly improves prediction of risk.

Keywords: Cognitive dysfunction, dementia, epidemiology, incidence, prevalence

DOI: 10.3233/JAD-180746

Journal: Journal of Alzheimer's Disease, vol. 68, no. 4, pp. 1439-1451, 2019