Thomann, Alessandra E. and Berres, Manfred and Goettel, Nicolai and Steiner, Luzius A. and Monsch, Andreas U.. (2020) Enhanced diagnostic accuracy for neurocognitive disorders: a revised cut-off approach for the Montreal Cognitive Assessment. Alzheimer's Research & Therapy, 12 (1). p. 39.
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Official URL: https://edoc.unibas.ch/79889/
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Abstract
The Montreal Cognitive Assessment (MoCA) has good sensitivity for mild cognitive impairment, but specificity is low when the original cut-off (25/26) is used. We aim to revise the cut-off on the German MoCA for its use in clinical routine.; Data were analyzed from 496 Memory Clinic outpatients (447 individuals with a neurocognitive disorder; 49 with cognitive normal findings) and from 283 normal controls. Cut-offs were identified based on (a) Youden's index and (b) the 10th percentile of the control group.; A cut-off of 23/24 on the MoCA had better correct classification rates than the MMSE and the original MoCA cut-off. Compared to the original MoCA cut-off, the cut-off of 23/24 points had higher specificity (92% vs 63%), but lower sensitivity (65% vs 86%). Introducing two separate cut-offs increased diagnostic accuracies with 92% specificity (23/24 points) and 91% sensitivity (26/27 points). Scores between these two cut-offs require further examinations.; Using two separate cut-offs for the MoCA combined with scores in an indecisive area enhances the accuracy of cognitive screening. What do you want to do ? New mail Copy
Faculties and Departments: | 03 Faculty of Medicine > Bereich Medizinische Fächer (Klinik) > Geriatrie > Geriatrie (Kressig) 03 Faculty of Medicine > Departement Klinische Forschung > Bereich Medizinische Fächer (Klinik) > Geriatrie > Geriatrie (Kressig) 07 Faculty of Psychology > Departement Psychologie 07 Faculty of Psychology > Departement Psychologie > Ehemalige Einheiten Psychologie > Molecular Neuroscience (Papassotiropoulos) |
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UniBasel Contributors: | Monsch, Andreas U. U |
Item Type: | Article, refereed |
Article Subtype: | Research Article |
Publisher: | BioMed Central |
e-ISSN: | 1758-9193 |
Note: | Publication type according to Uni Basel Research Database: Journal article |
Related URLs: | |
Identification Number: |
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Last Modified: | 29 Dec 2020 09:58 |
Deposited On: | 29 Dec 2020 09:58 |
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