![]() ![]() Our results suggest that the MoCA test is a useful screening instrument for assessing cognitive impairment in psychotic patients and has some advantages over other available instruments, such as its ease-of-use and short administration time.Ĭognitive impairment Cognitive screening MoCA Schizophrenia. Receiver operating characteristic (ROC) analysis suggested a <25 cut-off for cognitive impairment instead of the original <26. We also found significant associations between 5 out of 7 MoCA subtests (visuospatial-executive, attention, language, abstraction and delayed recall) and MCCB subtests but not for the naming and orientation MoCA subtests. Concurrent validation was found between the total scores of the MoCA and MCCB. Two cut-off scores for cognitive impairment using the MCCB were applied (T score <40 and < 30). Patients were psychopathologically assessed, and the MoCA test and MATRICS Consensus Cognitive Battery (MCCB) were administered. One hundred-forty stabilized patients were re-evaluated more than 15 years after a First Episode of Psychosis (FEP). This study explores the usefulness of this instrument to detect cognitive impairment in long-term psychotic disorders. The Montreal Cognitive Assessment (MoCA) is a brief tool that has been shown to be effective in identifying mild cognitive impairment and early dementia. Let us know how this access is important for you.Cognitive impairment is a key feature in patients with psychotic disorders. Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. MoCA scores are translatable to the MMSE to facilitate comparison. Functional assessment can help exclude dementia cases. Another methodological problem when selecting the optimal cut-off score for MoCA normality is the choice of the thresholds to define cognitive impairment in the gold standard. 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. ![]() ConclusionsMoCA and MMSE were more similar for dementia cases, but MoCA distributes MCI cases across a broader score range with less ceiling effect. Mean FAQ scores were significantly higher and a greater proportion had abnormal FAQ scores in dementia than MCI and HC. 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%). ResultsMost dementia cases scored abnormally, while MCI and HC score distributions overlapped on each test. However, age and education adjusted cutoff. In identifying cognitive impairment, the sensitivity and specificity were 0.932 and 0.723, respectively. ![]() To detect dementia, its sensitivity was 0.922, and specificity was 0.923. Receiver Operating Characteristic (ROC) analyses evaluated lower cutoff scores for capturing the most MCI cases. Results: Single cutoff score of HK-MoCA differentiated MCI from normal with sensitivity of 0.861 and specificity of 0.723. 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. MethodsFor 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. BackgroundThe 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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