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Predicting Falls in People with Multiple Sclerosis: Fall History Is as Accurate as More Complex Measures
Background. Many people with MS fall, but the best method for identifying those at increased fall risk is not known. Objective. To compare how accurately fall history, questionnaires, and physical tests predict future falls and injurious falls in people with MS. Methods. 52 people with MS were asked...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3804404/ https://www.ncbi.nlm.nih.gov/pubmed/24191198 http://dx.doi.org/10.1155/2013/496325 |
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author | Cameron, Michelle H. Thielman, Emily Mazumder, Rajarshi Bourdette, Dennis |
author_facet | Cameron, Michelle H. Thielman, Emily Mazumder, Rajarshi Bourdette, Dennis |
author_sort | Cameron, Michelle H. |
collection | PubMed |
description | Background. Many people with MS fall, but the best method for identifying those at increased fall risk is not known. Objective. To compare how accurately fall history, questionnaires, and physical tests predict future falls and injurious falls in people with MS. Methods. 52 people with MS were asked if they had fallen in the past 2 months and the past year. Subjects were also assessed with the Activities-specific Balance Confidence, Falls Efficacy Scale-International, and Multiple Sclerosis Walking Scale-12 questionnaires, the Expanded Disability Status Scale, Timed 25-Foot Walk, and computerized dynamic posturography and recorded their falls daily for the following 6 months with calendars. The ability of baseline assessments to predict future falls was compared using receiver operator curves and logistic regression. Results. All tests individually provided similar fall prediction (area under the curve (AUC) 0.60–0.75). A fall in the past year was the best predictor of falls (AUC 0.75, sensitivity 0.89, specificity 0.56) or injurious falls (AUC 0.69, sensitivity 0.96, specificity 0.41) in the following 6 months. Conclusion. Simply asking people with MS if they have fallen in the past year predicts future falls and injurious falls as well as more complex, expensive, or time-consuming approaches. |
format | Online Article Text |
id | pubmed-3804404 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-38044042013-11-04 Predicting Falls in People with Multiple Sclerosis: Fall History Is as Accurate as More Complex Measures Cameron, Michelle H. Thielman, Emily Mazumder, Rajarshi Bourdette, Dennis Mult Scler Int Research Article Background. Many people with MS fall, but the best method for identifying those at increased fall risk is not known. Objective. To compare how accurately fall history, questionnaires, and physical tests predict future falls and injurious falls in people with MS. Methods. 52 people with MS were asked if they had fallen in the past 2 months and the past year. Subjects were also assessed with the Activities-specific Balance Confidence, Falls Efficacy Scale-International, and Multiple Sclerosis Walking Scale-12 questionnaires, the Expanded Disability Status Scale, Timed 25-Foot Walk, and computerized dynamic posturography and recorded their falls daily for the following 6 months with calendars. The ability of baseline assessments to predict future falls was compared using receiver operator curves and logistic regression. Results. All tests individually provided similar fall prediction (area under the curve (AUC) 0.60–0.75). A fall in the past year was the best predictor of falls (AUC 0.75, sensitivity 0.89, specificity 0.56) or injurious falls (AUC 0.69, sensitivity 0.96, specificity 0.41) in the following 6 months. Conclusion. Simply asking people with MS if they have fallen in the past year predicts future falls and injurious falls as well as more complex, expensive, or time-consuming approaches. Hindawi Publishing Corporation 2013 2013-09-26 /pmc/articles/PMC3804404/ /pubmed/24191198 http://dx.doi.org/10.1155/2013/496325 Text en Copyright © 2013 Michelle H. Cameron et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Cameron, Michelle H. Thielman, Emily Mazumder, Rajarshi Bourdette, Dennis Predicting Falls in People with Multiple Sclerosis: Fall History Is as Accurate as More Complex Measures |
title | Predicting Falls in People with Multiple Sclerosis: Fall History Is as Accurate as More Complex Measures |
title_full | Predicting Falls in People with Multiple Sclerosis: Fall History Is as Accurate as More Complex Measures |
title_fullStr | Predicting Falls in People with Multiple Sclerosis: Fall History Is as Accurate as More Complex Measures |
title_full_unstemmed | Predicting Falls in People with Multiple Sclerosis: Fall History Is as Accurate as More Complex Measures |
title_short | Predicting Falls in People with Multiple Sclerosis: Fall History Is as Accurate as More Complex Measures |
title_sort | predicting falls in people with multiple sclerosis: fall history is as accurate as more complex measures |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3804404/ https://www.ncbi.nlm.nih.gov/pubmed/24191198 http://dx.doi.org/10.1155/2013/496325 |
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