We also searched for relevant grey literature from the Web of Science Core Collection, including Science Citation Index and Conference Proceedings Citation Index (Thomson Reuters Web of Science), PhD theses and contacted researchers with potential relevant data. We identified further relevant studies from the PubMed ‘related articles’ feature and by tracking key studies in Science Citation Index and Scopus. We also searched ALOIS (Cochrane Dementia and Cognitive Improvement Group specialized register of diagnostic and intervention studies). In addition, we searched specialised sources containing diagnostic studies and reviews, including MEDION (Meta-analyses van Diagnostisch Onderzoek), DARE (Database of Abstracts of Reviews of Effects), HTA (Health Technology Assessment Database), ARIF (Aggressive Research Intelligence Facility) and C-EBLM (International Federation of Clinical Chemistry and Laboratory Medicine Committee for Evidence-based Laboratory Medicine) databases. We searched MEDLINE, EMBASE, BIOSIS Previews, Science Citation Index, PsycINFO and LILACS databases to August 2012. It is likely that a MoCA threshold lower than 26 would be more useful for optimal diagnostic accuracy in dementia, though this requires wider confirmation. In particular, no studies looked at how useful MoCA is for diagnosing dementia in primary care settings. During the interview, the patient produced fluent speech disrupted by mild anomia. The overall quality of the studies was not good enough to make firm recommendations on using the MoCA to detect dementia in different healthcare settings. The Montreal Cognitive Assessment (MoCA) score was 26/30 (the patient missed 1 point in delayed recall, 1 point in naming, and 2 points in the language questions of the test). In the studies we reviewed, over 40% of people without dementia would have been incorrectly diagnosed with dementia using the MoCA. On the other hand, the test also produced a high proportion of false positives, that is people who did not have dementia but tested positive at the 'less than 26' cut-off. In the studies that used this cut-off, we found the test correctly detected over 94% of people with dementia in all settings. We found that MoCA was good at detecting dementia when using a recognised cut-off score of less than 26. There was a large variation in the way the different studies were carried out: therefore we chose to present the results in a narrative summary because a statistical summary (combining all the estimates into a summary sensitivity and specificity) would not have been meaningful. The proportion of people with dementia was 5% to 10% in two population-derived studies and 22% to 54% in the five clinic-based studies. There were a total 9422 people included in all 7 studies though only one study had more than 350 people. All studies included older people, with the youngest average age of 61 years in one study. There were three from memory clinics (specialist clinics where people are referred for suspected dementia), two from general hospital clinics, none from primary care and two studies carried out in the general population. We found seven studies that matched our criteria. The evidence we reviewed is current to August 2012. MoCA uses a series of questions to test different aspects of mental functioning. Montreal Cognitive Assessment, MoCA: a brief screening tool for mild. In this review, we wanted to discover whether using a well-established cognitive test, MoCA, could accurately detect dementia when compared to a gold standard diagnostic test. Expanding the clinician's tool kit with the DCQ could reduce missed/delayed identification of atypical dementia and accelerate therapeutic intervention.We reviewed the evidence about the accuracy of the Montreal Cognitive Assessment (MoCA) test for detecting dementia.ĭementia is a common condition in older people, with at least 7% of people over 65 years old in the UK affected, and numbers are increasing worldwide. Discussion: The DCQ is a better tool to detect atypical dementia than standard cognitive screening tests. A statistical model distinguished typical from atypical dementia with a predictive power of 79%. All correlations between DCQ indexes and standard neuropsychological measures were significant. It was significantly more accurate than the MoCA to detect atypical dementia. ![]() Results: The DCQ showed excellent psychometric properties. A predictive diagnostic algorithm for atypical dementia was determined using classification tree analysis. Sensitivity and specificity were compared to the Montreal Cognitive Assessment (MoCA). Methods: We assessed the validity and reliability of the Dépistage Cognitif de Québec (DCQ a newly developed cognitive screening test, to detect atypical dementia using a multicenter cohort of 628 participants. Abstract : Introduction: Early recognition of atypical dementia remains challenging partly because of lack of cognitive screening instruments precisely tailored for this purpose.
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