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Consistency analysis and conversion model establishment of mini-mental state examination and montreal cognitive assessment in Chinese patients with Alzheimer’s disease
BACKGROUND: The Chinese version of the Mini-Mental State Examination (MMSE-C) and the Beijing version of the Montreal Cognitive Assessment (MoCA-BJ) are the most commonly used scales to screen for Alzheimer’s disease (AD) among Chinese patients; however, their consistency varies according to populat...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9537111/ https://www.ncbi.nlm.nih.gov/pubmed/36211834 http://dx.doi.org/10.3389/fpsyg.2022.990666 |
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author | Zhou, Lu Lin, Zhichuan Jiao, Bin Liao, Xinxin Zhou, Yafang Li, Hui Shen, Lu Weng, Ling |
author_facet | Zhou, Lu Lin, Zhichuan Jiao, Bin Liao, Xinxin Zhou, Yafang Li, Hui Shen, Lu Weng, Ling |
author_sort | Zhou, Lu |
collection | PubMed |
description | BACKGROUND: The Chinese version of the Mini-Mental State Examination (MMSE-C) and the Beijing version of the Montreal Cognitive Assessment (MoCA-BJ) are the most commonly used scales to screen for Alzheimer’s disease (AD) among Chinese patients; however, their consistency varies according to populations and languages. Equivalent conversion of MMSE-C and MoCA-BJ scores is important for meta-analysis. MATERIALS AND METHODS: MMSE-C and MoCA-BJ scoring were performed on the enrolled patients with AD (n = 332). Consistency analysis of MMSE-C and MoCA-BJ scores of patients in the conversion groups was performed. The circle-arc method was used to convert the MMSE-C scores of the conversion groups into MoCA-BJ scores, and the conversion formula was generated. The MMSE-C data of the verification group was converted to MoCA-BJ according to the formula, and the consistency analysis of the original MoCA-BJ of the verification group and the converted MoCA-BJ was performed to verify the conversion model. RESULTS: The results of the consistency analysis of MMSE-C and MoCA-BJ in group A showed that the correlation coefficients of the total group, high education years subgroup, medium education years subgroup, and low education years subgroup were 0.905 (P < 0.001), 0.874 (P < 0.001), 0.949 (P < 0.001), and 0.874 (P < 0.001), respectively, with high consistency and statistical significance. After applying the circle-arc method for equivalent conversion, the consistency analysis results of the original and the converted MoCA-BJ of the patients in group B of the total group, high education years subgroup, medium education years subgroup, and low education years subgroup were 0.891 (P < 0.001), 0.894 (P < 0.001), 0.781 (P < 0.001), 0.909 (P < 0.001), respectively, with high consistency and statistical significance. CONCLUSION: We established and validated a model of MMSE-C and MoCA-BJ score conversion for Chinese patients with AD using the circle-arc method. This model could be useful for multi-centers clinical trials and meta-analysis. |
format | Online Article Text |
id | pubmed-9537111 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95371112022-10-08 Consistency analysis and conversion model establishment of mini-mental state examination and montreal cognitive assessment in Chinese patients with Alzheimer’s disease Zhou, Lu Lin, Zhichuan Jiao, Bin Liao, Xinxin Zhou, Yafang Li, Hui Shen, Lu Weng, Ling Front Psychol Psychology BACKGROUND: The Chinese version of the Mini-Mental State Examination (MMSE-C) and the Beijing version of the Montreal Cognitive Assessment (MoCA-BJ) are the most commonly used scales to screen for Alzheimer’s disease (AD) among Chinese patients; however, their consistency varies according to populations and languages. Equivalent conversion of MMSE-C and MoCA-BJ scores is important for meta-analysis. MATERIALS AND METHODS: MMSE-C and MoCA-BJ scoring were performed on the enrolled patients with AD (n = 332). Consistency analysis of MMSE-C and MoCA-BJ scores of patients in the conversion groups was performed. The circle-arc method was used to convert the MMSE-C scores of the conversion groups into MoCA-BJ scores, and the conversion formula was generated. The MMSE-C data of the verification group was converted to MoCA-BJ according to the formula, and the consistency analysis of the original MoCA-BJ of the verification group and the converted MoCA-BJ was performed to verify the conversion model. RESULTS: The results of the consistency analysis of MMSE-C and MoCA-BJ in group A showed that the correlation coefficients of the total group, high education years subgroup, medium education years subgroup, and low education years subgroup were 0.905 (P < 0.001), 0.874 (P < 0.001), 0.949 (P < 0.001), and 0.874 (P < 0.001), respectively, with high consistency and statistical significance. After applying the circle-arc method for equivalent conversion, the consistency analysis results of the original and the converted MoCA-BJ of the patients in group B of the total group, high education years subgroup, medium education years subgroup, and low education years subgroup were 0.891 (P < 0.001), 0.894 (P < 0.001), 0.781 (P < 0.001), 0.909 (P < 0.001), respectively, with high consistency and statistical significance. CONCLUSION: We established and validated a model of MMSE-C and MoCA-BJ score conversion for Chinese patients with AD using the circle-arc method. This model could be useful for multi-centers clinical trials and meta-analysis. Frontiers Media S.A. 2022-09-23 /pmc/articles/PMC9537111/ /pubmed/36211834 http://dx.doi.org/10.3389/fpsyg.2022.990666 Text en Copyright © 2022 Zhou, Lin, Jiao, Liao, Zhou, Li, Shen and Weng. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Zhou, Lu Lin, Zhichuan Jiao, Bin Liao, Xinxin Zhou, Yafang Li, Hui Shen, Lu Weng, Ling Consistency analysis and conversion model establishment of mini-mental state examination and montreal cognitive assessment in Chinese patients with Alzheimer’s disease |
title | Consistency analysis and conversion model establishment of mini-mental state examination and montreal cognitive assessment in Chinese patients with Alzheimer’s disease |
title_full | Consistency analysis and conversion model establishment of mini-mental state examination and montreal cognitive assessment in Chinese patients with Alzheimer’s disease |
title_fullStr | Consistency analysis and conversion model establishment of mini-mental state examination and montreal cognitive assessment in Chinese patients with Alzheimer’s disease |
title_full_unstemmed | Consistency analysis and conversion model establishment of mini-mental state examination and montreal cognitive assessment in Chinese patients with Alzheimer’s disease |
title_short | Consistency analysis and conversion model establishment of mini-mental state examination and montreal cognitive assessment in Chinese patients with Alzheimer’s disease |
title_sort | consistency analysis and conversion model establishment of mini-mental state examination and montreal cognitive assessment in chinese patients with alzheimer’s disease |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9537111/ https://www.ncbi.nlm.nih.gov/pubmed/36211834 http://dx.doi.org/10.3389/fpsyg.2022.990666 |
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