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Detecting disabilities in everyday life: evidence from a geriatric assessment

BACKGROUND: The activities of daily living (ADL) score is a widely used index to establish the degree of independence from any help in everyday life situations. Measuring ADL accurately is time-consuming and costly. This paper presents a framework to approximate ADL via variables usually collected i...

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Autores principales: Dzien, Cornelius, Unterberger, Petra, Hofmarcher, Paul, Winner, Hannes, Lechleitner, Monika
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9429328/
https://www.ncbi.nlm.nih.gov/pubmed/36042419
http://dx.doi.org/10.1186/s12877-022-03368-x
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author Dzien, Cornelius
Unterberger, Petra
Hofmarcher, Paul
Winner, Hannes
Lechleitner, Monika
author_facet Dzien, Cornelius
Unterberger, Petra
Hofmarcher, Paul
Winner, Hannes
Lechleitner, Monika
author_sort Dzien, Cornelius
collection PubMed
description BACKGROUND: The activities of daily living (ADL) score is a widely used index to establish the degree of independence from any help in everyday life situations. Measuring ADL accurately is time-consuming and costly. This paper presents a framework to approximate ADL via variables usually collected in comprehensive geriatric assessments. We show that the selected variables serve as good indicators in explaining the physical disabilities of older patients. METHODS: Our sample included information from a geriatric assessment of 326 patients aged between 64 and 99 years in a hospital in Tyrol, Austria. In addition to ADL, 23 variables reflecting the physical and mental status of these patients were recorded during the assessment. We performed least absolute shrinkage and selection operator (LASSO) to determine which of these variables had the highest impact on explaining ADL. Then, we used receiver operating characteristic (ROC) analysis and logistic regression techniques to validate our model performance. Finally, we calculated cut-off points for each of the selected variables to show the values at which ADL fall below a certain threshold. RESULTS: Mobility, urinary incontinence, nutritional status and cognitive function were most closely related to ADL and, therefore, to geriatric patients’ functional limitations. Jointly, the selected variables were able to detect neediness with high accuracy (area under the ROC curve (AUC) = 0.89 and 0.91, respectively). If a patient had a limitation in one of these variables, the probability of everyday life disability increased with a statistically significant factor between 2.4 (nutritional status, 95%-CI 1.5–3.9) and 15.1 (urinary incontinence, 95%-CI 3.6–63.4). CONCLUSIONS: Our study highlights the most important impairments of everyday life to facilitate more efficient use of clinical resources, which in turn allows for more targeted treatment of geriatric patients. At the patient level, our approach enables early detection of functional limitations and timely indications of a possible need for assistance in everyday life. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12877-022-03368-x).
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spelling pubmed-94293282022-09-01 Detecting disabilities in everyday life: evidence from a geriatric assessment Dzien, Cornelius Unterberger, Petra Hofmarcher, Paul Winner, Hannes Lechleitner, Monika BMC Geriatr Research BACKGROUND: The activities of daily living (ADL) score is a widely used index to establish the degree of independence from any help in everyday life situations. Measuring ADL accurately is time-consuming and costly. This paper presents a framework to approximate ADL via variables usually collected in comprehensive geriatric assessments. We show that the selected variables serve as good indicators in explaining the physical disabilities of older patients. METHODS: Our sample included information from a geriatric assessment of 326 patients aged between 64 and 99 years in a hospital in Tyrol, Austria. In addition to ADL, 23 variables reflecting the physical and mental status of these patients were recorded during the assessment. We performed least absolute shrinkage and selection operator (LASSO) to determine which of these variables had the highest impact on explaining ADL. Then, we used receiver operating characteristic (ROC) analysis and logistic regression techniques to validate our model performance. Finally, we calculated cut-off points for each of the selected variables to show the values at which ADL fall below a certain threshold. RESULTS: Mobility, urinary incontinence, nutritional status and cognitive function were most closely related to ADL and, therefore, to geriatric patients’ functional limitations. Jointly, the selected variables were able to detect neediness with high accuracy (area under the ROC curve (AUC) = 0.89 and 0.91, respectively). If a patient had a limitation in one of these variables, the probability of everyday life disability increased with a statistically significant factor between 2.4 (nutritional status, 95%-CI 1.5–3.9) and 15.1 (urinary incontinence, 95%-CI 3.6–63.4). CONCLUSIONS: Our study highlights the most important impairments of everyday life to facilitate more efficient use of clinical resources, which in turn allows for more targeted treatment of geriatric patients. At the patient level, our approach enables early detection of functional limitations and timely indications of a possible need for assistance in everyday life. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12877-022-03368-x). BioMed Central 2022-08-31 /pmc/articles/PMC9429328/ /pubmed/36042419 http://dx.doi.org/10.1186/s12877-022-03368-x 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
Dzien, Cornelius
Unterberger, Petra
Hofmarcher, Paul
Winner, Hannes
Lechleitner, Monika
Detecting disabilities in everyday life: evidence from a geriatric assessment
title Detecting disabilities in everyday life: evidence from a geriatric assessment
title_full Detecting disabilities in everyday life: evidence from a geriatric assessment
title_fullStr Detecting disabilities in everyday life: evidence from a geriatric assessment
title_full_unstemmed Detecting disabilities in everyday life: evidence from a geriatric assessment
title_short Detecting disabilities in everyday life: evidence from a geriatric assessment
title_sort detecting disabilities in everyday life: evidence from a geriatric assessment
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9429328/
https://www.ncbi.nlm.nih.gov/pubmed/36042419
http://dx.doi.org/10.1186/s12877-022-03368-x
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