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Risk Prediction Models for Post-Stroke Dementia
A strong association exists between stroke and dementia with both diseases linked to ageing. Survival rates from stroke are improving which would equate to an ever-expanding population of patients at risk of future dementia. Early or timelier identification of dementia has become a priority in many...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371182/ https://www.ncbi.nlm.nih.gov/pubmed/31011029 http://dx.doi.org/10.3390/geriatrics2030019 |
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author | Tang, Eugene Yee Hing Robinson, Louise Stephan, Blossom Christa Maree |
author_facet | Tang, Eugene Yee Hing Robinson, Louise Stephan, Blossom Christa Maree |
author_sort | Tang, Eugene Yee Hing |
collection | PubMed |
description | A strong association exists between stroke and dementia with both diseases linked to ageing. Survival rates from stroke are improving which would equate to an ever-expanding population of patients at risk of future dementia. Early or timelier identification of dementia has become a priority in many countries, including the UK. Although screening for dementia is not advocated, targeting at risk populations could be used to reduce an individual’s risk via intervention (i.e., personalised medicine), where available. One approach to improving identification of high-risk dementia individuals is using risk prediction models. Such models could be applied to stroke survivors. Dementia risk prediction models specific to stroke survivors have recently been developed and will be discussed here. |
format | Online Article Text |
id | pubmed-6371182 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63711822019-03-07 Risk Prediction Models for Post-Stroke Dementia Tang, Eugene Yee Hing Robinson, Louise Stephan, Blossom Christa Maree Geriatrics (Basel) Communication A strong association exists between stroke and dementia with both diseases linked to ageing. Survival rates from stroke are improving which would equate to an ever-expanding population of patients at risk of future dementia. Early or timelier identification of dementia has become a priority in many countries, including the UK. Although screening for dementia is not advocated, targeting at risk populations could be used to reduce an individual’s risk via intervention (i.e., personalised medicine), where available. One approach to improving identification of high-risk dementia individuals is using risk prediction models. Such models could be applied to stroke survivors. Dementia risk prediction models specific to stroke survivors have recently been developed and will be discussed here. MDPI 2017-06-22 /pmc/articles/PMC6371182/ /pubmed/31011029 http://dx.doi.org/10.3390/geriatrics2030019 Text en © 2017 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 | Communication Tang, Eugene Yee Hing Robinson, Louise Stephan, Blossom Christa Maree Risk Prediction Models for Post-Stroke Dementia |
title | Risk Prediction Models for Post-Stroke Dementia |
title_full | Risk Prediction Models for Post-Stroke Dementia |
title_fullStr | Risk Prediction Models for Post-Stroke Dementia |
title_full_unstemmed | Risk Prediction Models for Post-Stroke Dementia |
title_short | Risk Prediction Models for Post-Stroke Dementia |
title_sort | risk prediction models for post-stroke dementia |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371182/ https://www.ncbi.nlm.nih.gov/pubmed/31011029 http://dx.doi.org/10.3390/geriatrics2030019 |
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