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How accurate are geriatricians’ fall predictions?
BACKGROUND: Older patients are at increased risk of falling and of serious morbidity and mortality resulting from falls. The ability to accurately identify older patients at increased fall risk affords the opportunity to implement interventions to reduce morbidity and mortality. Geriatricians are tr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118876/ https://www.ncbi.nlm.nih.gov/pubmed/35585524 http://dx.doi.org/10.1186/s12877-022-03129-w |
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author | Wilbur, Jason Jogerst, Gerald Butler, Nicholas Xu, Yinghui |
author_facet | Wilbur, Jason Jogerst, Gerald Butler, Nicholas Xu, Yinghui |
author_sort | Wilbur, Jason |
collection | PubMed |
description | BACKGROUND: Older patients are at increased risk of falling and of serious morbidity and mortality resulting from falls. The ability to accurately identify older patients at increased fall risk affords the opportunity to implement interventions to reduce morbidity and mortality. Geriatricians are trained to assess older patients for fall risk. If geriatricians can accurately predict fallers (as opposed to evaluating for individual risk factors for falling), more aggressive and earlier interventions could be employed to reduce falls in older adult fallers. However, there is paucity of knowledge regarding the accuracy of geriatrician fall risk predictions. This study aims to determine the accuracy of geriatricians in predicting falls. METHODS: Between October 2018 and November 2019, a convenience sample of 100 subjects was recruited from an academic geriatric clinic population seeking routine medical care. Subjects performed a series of gait and balance assessments, answered the Stay Independent Brochure and were surveyed about fall incidence 6–12 months after study entry. Five geriatricians, blinded to subjects and fall outcomes, were provided the subjects’ data and asked to categorize each as a faller or non-faller. No requirements were imposed on the geriatricians’ use of the available data. These predictions were compared to predictions of an examining geriatrician who performed the assessments and to fall outcomes reported by subjects. RESULTS: Kappa values for the 5 geriatricians who used all the available data to classify participants as fallers or non-fallers compared with the examining geriatrician were 0.42 to 0.59, indicating moderate agreement. Compared to screening tools’ mean accuracy of 66.6% (59.6–73.0%), the 5 geriatricians had a mean accuracy for fall prediction of 67.4% (57.3–71.9%). CONCLUSIONS: This study adds to the scant knowledge available in the medical literature regarding the abilities of geriatricians to accurately predict falls in older patients. Studies are needed to characterize how geriatrician assessments of fall risk compare to standardized assessment tools. |
format | Online Article Text |
id | pubmed-9118876 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-91188762022-05-20 How accurate are geriatricians’ fall predictions? Wilbur, Jason Jogerst, Gerald Butler, Nicholas Xu, Yinghui BMC Geriatr Research BACKGROUND: Older patients are at increased risk of falling and of serious morbidity and mortality resulting from falls. The ability to accurately identify older patients at increased fall risk affords the opportunity to implement interventions to reduce morbidity and mortality. Geriatricians are trained to assess older patients for fall risk. If geriatricians can accurately predict fallers (as opposed to evaluating for individual risk factors for falling), more aggressive and earlier interventions could be employed to reduce falls in older adult fallers. However, there is paucity of knowledge regarding the accuracy of geriatrician fall risk predictions. This study aims to determine the accuracy of geriatricians in predicting falls. METHODS: Between October 2018 and November 2019, a convenience sample of 100 subjects was recruited from an academic geriatric clinic population seeking routine medical care. Subjects performed a series of gait and balance assessments, answered the Stay Independent Brochure and were surveyed about fall incidence 6–12 months after study entry. Five geriatricians, blinded to subjects and fall outcomes, were provided the subjects’ data and asked to categorize each as a faller or non-faller. No requirements were imposed on the geriatricians’ use of the available data. These predictions were compared to predictions of an examining geriatrician who performed the assessments and to fall outcomes reported by subjects. RESULTS: Kappa values for the 5 geriatricians who used all the available data to classify participants as fallers or non-fallers compared with the examining geriatrician were 0.42 to 0.59, indicating moderate agreement. Compared to screening tools’ mean accuracy of 66.6% (59.6–73.0%), the 5 geriatricians had a mean accuracy for fall prediction of 67.4% (57.3–71.9%). CONCLUSIONS: This study adds to the scant knowledge available in the medical literature regarding the abilities of geriatricians to accurately predict falls in older patients. Studies are needed to characterize how geriatrician assessments of fall risk compare to standardized assessment tools. BioMed Central 2022-05-18 /pmc/articles/PMC9118876/ /pubmed/35585524 http://dx.doi.org/10.1186/s12877-022-03129-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Wilbur, Jason Jogerst, Gerald Butler, Nicholas Xu, Yinghui How accurate are geriatricians’ fall predictions? |
title | How accurate are geriatricians’ fall predictions? |
title_full | How accurate are geriatricians’ fall predictions? |
title_fullStr | How accurate are geriatricians’ fall predictions? |
title_full_unstemmed | How accurate are geriatricians’ fall predictions? |
title_short | How accurate are geriatricians’ fall predictions? |
title_sort | how accurate are geriatricians’ fall predictions? |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118876/ https://www.ncbi.nlm.nih.gov/pubmed/35585524 http://dx.doi.org/10.1186/s12877-022-03129-w |
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