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A comparison of theoretical and statistically derived indices for predicting cognitive decline
INTRODUCTION: Both theoretical and statistically derived approaches have been used in research settings for predicting cognitive decline. METHODS: Fifty-eight cognitively normal (NC) and 71 mild cognitive impairment (MCI) subjects completed a comprehensive cognitive battery for up to 5 years of foll...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5328960/ https://www.ncbi.nlm.nih.gov/pubmed/28275699 http://dx.doi.org/10.1016/j.dadm.2016.10.002 |
_version_ | 1782510963723862016 |
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author | Wilhalme, Holly Goukasian, Naira De Leon, Fransia He, Angie Hwang, Kristy S. Woo, Ellen Elashoff, David Zhou, Yan Ringman, John M. Apostolova, Liana G. |
author_facet | Wilhalme, Holly Goukasian, Naira De Leon, Fransia He, Angie Hwang, Kristy S. Woo, Ellen Elashoff, David Zhou, Yan Ringman, John M. Apostolova, Liana G. |
author_sort | Wilhalme, Holly |
collection | PubMed |
description | INTRODUCTION: Both theoretical and statistically derived approaches have been used in research settings for predicting cognitive decline. METHODS: Fifty-eight cognitively normal (NC) and 71 mild cognitive impairment (MCI) subjects completed a comprehensive cognitive battery for up to 5 years of follow-up. Composite indices of cognitive function were derived using a classic theoretical approach and exploratory factor analysis (EFA). Cognitive variables comprising each factor were averaged to form the EFA composite indices. Logistic regression was used to investigate whether these cognitive composites can reliably predict cognitive outcomes. RESULTS: Neither method predicted decline in NC. The theoretical memory, executive, attention, and language composites and the EFA-derived “attention/executive” and “verbal memory” composites were significant predictors of decline in MCI. The best models achieved an area under the curve of 0.94 in MCI. CONCLUSIONS: The theoretical and the statistically derived cognitive composite approaches are useful in predicting decline in MCI but not in NC. |
format | Online Article Text |
id | pubmed-5328960 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-53289602017-03-08 A comparison of theoretical and statistically derived indices for predicting cognitive decline Wilhalme, Holly Goukasian, Naira De Leon, Fransia He, Angie Hwang, Kristy S. Woo, Ellen Elashoff, David Zhou, Yan Ringman, John M. Apostolova, Liana G. Alzheimers Dement (Amst) Cognitive & Behavioral Assessment INTRODUCTION: Both theoretical and statistically derived approaches have been used in research settings for predicting cognitive decline. METHODS: Fifty-eight cognitively normal (NC) and 71 mild cognitive impairment (MCI) subjects completed a comprehensive cognitive battery for up to 5 years of follow-up. Composite indices of cognitive function were derived using a classic theoretical approach and exploratory factor analysis (EFA). Cognitive variables comprising each factor were averaged to form the EFA composite indices. Logistic regression was used to investigate whether these cognitive composites can reliably predict cognitive outcomes. RESULTS: Neither method predicted decline in NC. The theoretical memory, executive, attention, and language composites and the EFA-derived “attention/executive” and “verbal memory” composites were significant predictors of decline in MCI. The best models achieved an area under the curve of 0.94 in MCI. CONCLUSIONS: The theoretical and the statistically derived cognitive composite approaches are useful in predicting decline in MCI but not in NC. Elsevier 2016-11-05 /pmc/articles/PMC5328960/ /pubmed/28275699 http://dx.doi.org/10.1016/j.dadm.2016.10.002 Text en © 2016 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Cognitive & Behavioral Assessment Wilhalme, Holly Goukasian, Naira De Leon, Fransia He, Angie Hwang, Kristy S. Woo, Ellen Elashoff, David Zhou, Yan Ringman, John M. Apostolova, Liana G. A comparison of theoretical and statistically derived indices for predicting cognitive decline |
title | A comparison of theoretical and statistically derived indices for predicting cognitive decline |
title_full | A comparison of theoretical and statistically derived indices for predicting cognitive decline |
title_fullStr | A comparison of theoretical and statistically derived indices for predicting cognitive decline |
title_full_unstemmed | A comparison of theoretical and statistically derived indices for predicting cognitive decline |
title_short | A comparison of theoretical and statistically derived indices for predicting cognitive decline |
title_sort | comparison of theoretical and statistically derived indices for predicting cognitive decline |
topic | Cognitive & Behavioral Assessment |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5328960/ https://www.ncbi.nlm.nih.gov/pubmed/28275699 http://dx.doi.org/10.1016/j.dadm.2016.10.002 |
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