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Multifactorial 10-Year Prior Diagnosis Prediction Model of Dementia
Dementia is a neurodegenerative disorder that affects the older adult population. To date, no cure or treatment to change its course is available. Since changes in the brains of affected individuals could be evidenced as early as 10 years before the onset of symptoms, prognosis research should consi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7557767/ https://www.ncbi.nlm.nih.gov/pubmed/32937765 http://dx.doi.org/10.3390/ijerph17186674 |
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author | Dallora, Ana Luiza Minku, Leandro Mendes, Emilia Rennemark, Mikael Anderberg, Peter Sanmartin Berglund, Johan |
author_facet | Dallora, Ana Luiza Minku, Leandro Mendes, Emilia Rennemark, Mikael Anderberg, Peter Sanmartin Berglund, Johan |
author_sort | Dallora, Ana Luiza |
collection | PubMed |
description | Dementia is a neurodegenerative disorder that affects the older adult population. To date, no cure or treatment to change its course is available. Since changes in the brains of affected individuals could be evidenced as early as 10 years before the onset of symptoms, prognosis research should consider this time frame. This study investigates a broad decision tree multifactorial approach for the prediction of dementia, considering 75 variables regarding demographic, social, lifestyle, medical history, biochemical tests, physical examination, psychological assessment and health instruments. Previous work on dementia prognoses with machine learning did not consider a broad range of factors in a large time frame. The proposed approach investigated predictive factors for dementia and possible prognostic subgroups. This study used data from the ongoing multipurpose Swedish National Study on Aging and Care, consisting of 726 subjects (91 presented dementia diagnosis in 10 years). The proposed approach achieved an AUC of 0.745 and Recall of 0.722 for the 10-year prognosis of dementia. Most of the variables selected by the tree are related to modifiable risk factors; physical strength was important across all ages. Also, there was a lack of variables related to health instruments routinely used for the dementia diagnosis. |
format | Online Article Text |
id | pubmed-7557767 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75577672020-10-20 Multifactorial 10-Year Prior Diagnosis Prediction Model of Dementia Dallora, Ana Luiza Minku, Leandro Mendes, Emilia Rennemark, Mikael Anderberg, Peter Sanmartin Berglund, Johan Int J Environ Res Public Health Article Dementia is a neurodegenerative disorder that affects the older adult population. To date, no cure or treatment to change its course is available. Since changes in the brains of affected individuals could be evidenced as early as 10 years before the onset of symptoms, prognosis research should consider this time frame. This study investigates a broad decision tree multifactorial approach for the prediction of dementia, considering 75 variables regarding demographic, social, lifestyle, medical history, biochemical tests, physical examination, psychological assessment and health instruments. Previous work on dementia prognoses with machine learning did not consider a broad range of factors in a large time frame. The proposed approach investigated predictive factors for dementia and possible prognostic subgroups. This study used data from the ongoing multipurpose Swedish National Study on Aging and Care, consisting of 726 subjects (91 presented dementia diagnosis in 10 years). The proposed approach achieved an AUC of 0.745 and Recall of 0.722 for the 10-year prognosis of dementia. Most of the variables selected by the tree are related to modifiable risk factors; physical strength was important across all ages. Also, there was a lack of variables related to health instruments routinely used for the dementia diagnosis. MDPI 2020-09-14 2020-09 /pmc/articles/PMC7557767/ /pubmed/32937765 http://dx.doi.org/10.3390/ijerph17186674 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Dallora, Ana Luiza Minku, Leandro Mendes, Emilia Rennemark, Mikael Anderberg, Peter Sanmartin Berglund, Johan Multifactorial 10-Year Prior Diagnosis Prediction Model of Dementia |
title | Multifactorial 10-Year Prior Diagnosis Prediction Model of Dementia |
title_full | Multifactorial 10-Year Prior Diagnosis Prediction Model of Dementia |
title_fullStr | Multifactorial 10-Year Prior Diagnosis Prediction Model of Dementia |
title_full_unstemmed | Multifactorial 10-Year Prior Diagnosis Prediction Model of Dementia |
title_short | Multifactorial 10-Year Prior Diagnosis Prediction Model of Dementia |
title_sort | multifactorial 10-year prior diagnosis prediction model of dementia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7557767/ https://www.ncbi.nlm.nih.gov/pubmed/32937765 http://dx.doi.org/10.3390/ijerph17186674 |
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