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01-09-2018 | Original Communication

Validation of a novel Montreal Cognitive Assessment scoring algorithm in non-demented Parkinson’s disease patients

Authors: Patricia Sulzer, Sara Becker, Walter Maetzler, Elke Kalbe, Luc van Nueten, Maarten Timmers, Gerrit Machetanz, Johannes Streffer, Giacomo Salvadore, Erich Scholz, Zuzanna Tkaczynska, Kathrin Brockmann, Daniela Berg, Inga Liepelt-Scarfone

Published in: Journal of Neurology | Issue 9/2018

Abstract

Introduction

The early diagnosis of mild cognitive impairment (PD-MCI) in Parkinson’s disease (PD) is essential as it increases the future risk for PD dementia (PDD). Recently, a novel weighting algorithm for the Montreal Cognitive Assessment (MoCA) subtests has been reported, to best discriminate between those with and without cognitive impairment in PD. The aim of our study was to validate this scoring algorithm in a large sample of non-demented PD patients, hypothesizing that the weighted MoCA would have a higher diagnostic accuracy for PD-MCI than the original MoCA.

Methods

In 202 non-demented PD patients, we evaluated cognitive status, clinical and demographic data, as well as the MoCA with a weighted and unweighted score. Receiver operating characteristic (ROC) curve analysis was used to evaluate discriminative ability of the MoCA. Group comparisons and ROC analysis were performed for PD-MCI classifications with a cut-off ≤ 1, 1.5, and 2 standard deviation (SD) below appropriate norms.

Results

PD-MCI patients scored lower on the weighted than the original MoCA version (p < 0.001) compared to PD patients with normal cognitive function. Areas under the curve only differed significantly for the 2 SD cut-off, leading to an increased sensitivity of the weighted MoCA score (72.9% vs. 70.5%) and specificity compared to the original version (79.0% vs. 65.4%).

Conclusions

Our results indicate better discriminant power for the weighted MoCA compared to the original for more advanced stages of PD-MCI (2 SD cut-off). Future studies are needed to evaluate the predictive value of the weighted MoCA for PDD.

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Title: Validation of a novel Montreal Cognitive Assessment scoring algorithm in non-demented Parkinson’s disease patients
Authors: Patricia Sulzer
Sara Becker
Walter Maetzler
Elke Kalbe
Luc van Nueten
Maarten Timmers
Gerrit Machetanz
Johannes Streffer
Giacomo Salvadore
Erich Scholz
Zuzanna Tkaczynska
Kathrin Brockmann
Daniela Berg
Inga Liepelt-Scarfone
Publication date: 01-09-2018
Publisher: Springer Berlin Heidelberg
Published in: Journal of Neurology / Issue 9/2018
Print ISSN: 0340-5354
Electronic ISSN: 1432-1459
DOI: https://doi.org/10.1007/s00415-018-8942-4

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Validation of a novel Montreal Cognitive Assessment scoring algorithm in non-demented Parkinson’s disease patients

Abstract

Introduction

Methods

Results

Conclusions

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Introduction

Methods

Results

Conclusions

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