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Original Article
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| Predicting cognitive and behavioral functions in patients with dementia: Practical prognostic models of logarithmic and linear regression | ||||||
| Aki Watanabe1, Makoto Suzuki1, Harumi Kotaki2, Hironori Sasaki2, Takayuki Kawaguchi1, Hideki Tanaka1, Michinari Fukuda1 | ||||||
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1Department of Rehabilitation, Kitasato University School of Allied Health Sciences, Kanagawa, Japan.
2Department of Rehabilitation Medicine, Hatsutomi Hoken Hospital, Chiba, Japan. | ||||||
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| How to cite this article |
| Watanabe A, Suzuki M, Kotaki H, Sasaki H, Kawaguchi T, Tanaka H, Fukuda M. Predicting cognitive and behavioral functions in patients with dementia: Practical prognostic models of logarithmic and linear regression. Edorium J Disabil Rehabil 2016;2:144–153. |
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Abstract
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Aims:
This study provides data on predicting changes in cognitive functions, behavioral independences and disturbances in dementia patients by differential modeling with logarithmic and linear regression.
Methods: This longitudinal study included two data analysis groups. Group one: 24 dementia patients for identification of cognitive and behavioral changes over time in group data; group two: 15 dementia patients to ensure correlation of the group data applied to prediction of each individual's degree of cognitive and behavioral changes. Group one mini-mental state examination, functional independence measure and dementia behavior disturbance scale scores were assessed initially and 3 and 6 months thereafter during hospitalization and were regressed on the logarithm and linear of time. In group two, calculations of the scores were made for the first two scorings after admission to tailor logarithmic and linear regression formulae to fit an individual's degree of changes at 9 and 12 months. Results: Changes in data over time resembled both logarithmic and linear functions. However, the scores sampled at two baseline points based on logarithmic regression modeling estimated prediction of cognitive and behavioral changes more accurately than did linear regression modeling. Conclusion: This simple-to-use logarithmic modeling accurately predicted changes in cognitive functions, behavioral independence and disturbances in patients with dementia. | |
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Keywords:
Behavioral independence and disturbance, Cognitive function, Dementia, Logarithmic regression modeling, Prognosis
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Author Contributions:
Aki Watanabe – Substantial contributions to conception and design, Acquisition of data, Analysis and interpretation of data, Drafting the article, Revising it critically for important intellectual content, Final approval of the version to be published Makoto Suzuki – Analysis and interpretation of data, Revising it critically for important intellectual content, Final approval of the version to be published Harumi Kotaki – Analysis and interpretation of data, Revising it critically for important intellectual content, Final approval of the version to be published Hironori Sasaki – Analysis and interpretation of data, Revising it critically for important intellectual content, Final approval of the version to be published Takayuki Kawaguchi – Analysis and interpretation of data, Revising it critically for important intellectual content, Final approval of the version to be published Hideki Tanaka – Analysis and interpretation of data, Revising it critically for important intellectual content, Final approval of the version to be published Michinari Fukuda – Analysis and interpretation of data, Revising it critically for important intellectual content, Final approval of the version to be published |
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Guarantor of submission
The corresponding author is the guarantor of submission. |
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Source of support
None |
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Conflict of interest
Authors declare no conflict of interest. |
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Copyright
© 2016 Aki Watanabe et al. This article is distributed under the terms of Creative Commons Attribution License which permits unrestricted use, distribution and reproduction in any medium provided the original author(s) and original publisher are properly credited. Please see the copyright policy on the journal website for more information. |
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