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Consistency and applicability of different brief screen instrument of cognitive function in elderly population

BACKGROUND: Screening for cognitive impairment (CI) is often hampered by lack of consensus as to which screening instrument to use. The aim is to assess the consistence and applicability of different CI screening tools. METHOD: In a cross-sectional study from October 2017 to September 2018 in 7 comm...

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Autores principales: Lu, Lixia, Chen, Lin, Wu, Weiwen, Wang, Yang, Liu, Zhenbao, Xu, Jun, Yang, Qianhong, Zhao, Jun, Liu, Liangxian, Yu, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7919302/
https://www.ncbi.nlm.nih.gov/pubmed/33648444
http://dx.doi.org/10.1186/s12883-021-02048-4
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author Lu, Lixia
Chen, Lin
Wu, Weiwen
Wang, Yang
Liu, Zhenbao
Xu, Jun
Yang, Qianhong
Zhao, Jun
Liu, Liangxian
Yu, Hui
author_facet Lu, Lixia
Chen, Lin
Wu, Weiwen
Wang, Yang
Liu, Zhenbao
Xu, Jun
Yang, Qianhong
Zhao, Jun
Liu, Liangxian
Yu, Hui
author_sort Lu, Lixia
collection PubMed
description BACKGROUND: Screening for cognitive impairment (CI) is often hampered by lack of consensus as to which screening instrument to use. The aim is to assess the consistence and applicability of different CI screening tools. METHOD: In a cross-sectional study from October 2017 to September 2018 in 7 communities in Shanghai, China, elder (≧60) residential volunteers with no history of major cardiovascular diseases, cancers and other comorbidities known to affect cognitive functions were recruited. The participants underwent tests with 7 cognitive function screening instruments. Multivariate linear regressions were performed to test correlations between demographic characteristics, including gender, age, education, and marital status, with cognitive test scores. Mini-Mental State Examination (MMSE) score adjusted according to the correlation coefficients was used to detect CI with a cutoff of 24. Other cognitive function scores were compared between participants with and without CI. In addition, Pearson’s correlation test was used to detect association between different test scores. RESULTS: 172 participants with relatively low education levels were included. Age and education showed significant association with cognitive test scores. Using adjusted MMSE, 39.6% of participants were identified with CI, while the percentage was 87.2% when adjusted Montreal Cognitive Assessment (MoCA) with cutoff of 26 was used. Analysis of “abnormal” test scores showed that MMSE had the highest percentage of valid data (98.8%). MoCA and Isaacs test of Verbal Fluency (VF) score had correlation with most the other scores, while MMSE only significantly associated with VF and MoCA. CONCLUSIONS: MMSE may still present the most applicable tools for quick screen of cognitive functions, especially when environmental conditions may interfere with participants’ attention.
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spelling pubmed-79193022021-03-02 Consistency and applicability of different brief screen instrument of cognitive function in elderly population Lu, Lixia Chen, Lin Wu, Weiwen Wang, Yang Liu, Zhenbao Xu, Jun Yang, Qianhong Zhao, Jun Liu, Liangxian Yu, Hui BMC Neurol Research Article BACKGROUND: Screening for cognitive impairment (CI) is often hampered by lack of consensus as to which screening instrument to use. The aim is to assess the consistence and applicability of different CI screening tools. METHOD: In a cross-sectional study from October 2017 to September 2018 in 7 communities in Shanghai, China, elder (≧60) residential volunteers with no history of major cardiovascular diseases, cancers and other comorbidities known to affect cognitive functions were recruited. The participants underwent tests with 7 cognitive function screening instruments. Multivariate linear regressions were performed to test correlations between demographic characteristics, including gender, age, education, and marital status, with cognitive test scores. Mini-Mental State Examination (MMSE) score adjusted according to the correlation coefficients was used to detect CI with a cutoff of 24. Other cognitive function scores were compared between participants with and without CI. In addition, Pearson’s correlation test was used to detect association between different test scores. RESULTS: 172 participants with relatively low education levels were included. Age and education showed significant association with cognitive test scores. Using adjusted MMSE, 39.6% of participants were identified with CI, while the percentage was 87.2% when adjusted Montreal Cognitive Assessment (MoCA) with cutoff of 26 was used. Analysis of “abnormal” test scores showed that MMSE had the highest percentage of valid data (98.8%). MoCA and Isaacs test of Verbal Fluency (VF) score had correlation with most the other scores, while MMSE only significantly associated with VF and MoCA. CONCLUSIONS: MMSE may still present the most applicable tools for quick screen of cognitive functions, especially when environmental conditions may interfere with participants’ attention. BioMed Central 2021-03-01 /pmc/articles/PMC7919302/ /pubmed/33648444 http://dx.doi.org/10.1186/s12883-021-02048-4 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Lu, Lixia
Chen, Lin
Wu, Weiwen
Wang, Yang
Liu, Zhenbao
Xu, Jun
Yang, Qianhong
Zhao, Jun
Liu, Liangxian
Yu, Hui
Consistency and applicability of different brief screen instrument of cognitive function in elderly population
title Consistency and applicability of different brief screen instrument of cognitive function in elderly population
title_full Consistency and applicability of different brief screen instrument of cognitive function in elderly population
title_fullStr Consistency and applicability of different brief screen instrument of cognitive function in elderly population
title_full_unstemmed Consistency and applicability of different brief screen instrument of cognitive function in elderly population
title_short Consistency and applicability of different brief screen instrument of cognitive function in elderly population
title_sort consistency and applicability of different brief screen instrument of cognitive function in elderly population
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7919302/
https://www.ncbi.nlm.nih.gov/pubmed/33648444
http://dx.doi.org/10.1186/s12883-021-02048-4
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