Optimal cutoff scores of the Montreal Cognitive Assessment to detect mild cognitive impairment and dementia in Costa Rican older adults.

Abstract

Background: The burden of Alzheimer's disease and related dementias (AD/ADRD) in Costa Rica is expected to become one of the highest in the region. Early detection will help optimize resources and improve primary care interventions. The Montreal Cognitive Assessment (MoCA) has shown good sensitivity for detecting mild cognitive impairment (MCI), but specificity varies depending on the population. This motivated the analysis of different cutoffs to minimize false-positive classifications in a Costa Rican sample for its use in clinical settings.

Methods: Data was analyzed from 516 memory clinic outpatients (148 cognitively normal, 260 MCI, 108 mild AD/ADRD; mean age 66.3 ± 10.8 years) who underwent complete neurological and neuropsychological assessment and were diagnosed by consensus. Optimal MoCA cutoff scores were identified using a multiple cutoff approach.

Results: Overall, a cutoff score of ≥ 23 showed better accuracy to distinguish between normal cognition (NC) and MCI (sensitivity 73%, specificity 83%). When analyzed by educational levels, a cutoff score of ≥ 21 showed better accuracy for ≤ 6 years (sensitivity 80%, specificity 76%), ≥23 for 7-12 years (sensitivity 86%, specificity 76%) and ≥ 24 for > 12 years (sensitivity 70%, specificity 85%). For distinguishing MCI from mild AD/ADRD, the optimal overall cutoff score was ≥ 15 (sensitivity 66%, specificity 85%). When stratified by years of education, cutoff scores of ≥ 14 showed better accuracy for ≤ 6 years (sensitivity 70%, specificity 88%), ≥15 for 7-12 years (sensitivity 46%, specificity 95%) and ≥ 17 for > 12 years (sensitivity 67%, specificity 93%).

Conclusions: A MoCA cutoff score of ≥ 23 in the Costa Rican population showed better diagnostic accuracy for detecting MCI and may reduce the false positive rate. Our findings may be helpful for primary care clinical settings and further referral criteria.