![]() MethodsĪ total of 1289 participants aged over 65 were included from the baseline visits of Alzheimer’s disease Neuroimaging Initiative. We aimed to accurately evaluate the discriminative ability of the three tests administrated at the same visit simultaneously in detecting AD and MCI due to AD in the absence of a gold standard. Neuropsychological testing, such as the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-cog), is commonly used tests in identifying AD and MCI, offering convenience, affordability, non-invasiveness, and accessibility in clinical settings. In addition, the gold standard for diagnosing Mild Cognitive Impairment (MCI) remains unclear yet. MoCA scores are translatable to the MMSE to facilitate comparison.The neuropathological confirmation serves as the gold standard for diagnosing Alzheimer's disease (AD), but it is usually not available to the living individuals. Functional assessment can help exclude dementia cases. A cutoff of ≥ 17 on the MoCA may help capture early and late MCI cases depending on the level of sensitivity desired, ≥ 18 or 19 could be used. Mean FAQ scores were significantly higher and a greater proportion had abnormal FAQ scores in dementia than MCI and HC.ĬONCLUSIONS: MoCA and MMSE were more similar for dementia cases, but MoCA distributes MCI cases across a broader score range with less ceiling effect. The core and orientation domains in both tests best distinguished HC from MCI groups, whereas comprehension/executive function and attention/calculation were not helpful. ROC analysis found MoCA ≥ 17 as the cutoff between MCI and dementia that emphasized high sensitivity (92.3%) to capture MCI cases. Equi-percentile equating showed a MoCA score of 18 was equivalent to MMSE of 24. MoCA and MMSE scores correlated most for dementia (r = 0.86 versus MCI r = 0.60 HC r = 0.43). The ceiling effect (28-30 points) for MCI and HC was less using MoCA (18.1%) versus MMSE (71.4%). Most MCI cases scored ≥ 17 on MoCA (96.3%) and ≥ 24 on MMSE (98.3%). RESULTS: Most dementia cases scored abnormally, while MCI and HC score distributions overlapped on each test. Receiver Operating Characteristic (ROC) analyses evaluated lower cutoff scores for capturing the most MCI cases. Equi-percentile equating produced a translation grid for MoCA against MMSE scores. Functional Activities Questionnaire (FAQ) was evaluated as a strategy to separate dementia from MCI. Stepwise variable selection in logistic regression evaluated relative value of four test domains for separating MCI from HC. METHODS: For this cross-sectional study, we analyzed 219 healthy control (HC), 299 MCI, and 100 Alzheimer's disease (AD) dementia cases from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 database to evaluate MMSE and MoCA score distributions and select MoCA values to capture early and late MCI cases. ![]() Clinicians need to better understand the relationship between MoCA and MMSE scores. BACKGROUND: The Montreal Cognitive Assessment (MoCA) was developed to enable earlier detection of mild cognitive impairment (MCI) relative to familiar multi-domain tests like the Mini-Mental State Exam (MMSE). ![]()
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