Cargando…

Predicting Falls in Musculoskeletal Rehabilitation: A Retrospective Multisite Study

Background. Fall represents one of the highest concerns in the healthcare system, especially in medical rehabilitation settings. However, there is a lack of instruments for the assessment of risk falls in the context of musculoskeletal rehabilitation. Methods. This retrospective multisite study aime...

Descripción completa

Detalles Bibliográficos
Autores principales: Scarabel, Luca, Scarpina, Federica, Ruggieri, Graziano, Schiavone, Nicola, Limoni, Costanzo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606819/
https://www.ncbi.nlm.nih.gov/pubmed/37893879
http://dx.doi.org/10.3390/healthcare11202805
_version_ 1785127406816722944
author Scarabel, Luca
Scarpina, Federica
Ruggieri, Graziano
Schiavone, Nicola
Limoni, Costanzo
author_facet Scarabel, Luca
Scarpina, Federica
Ruggieri, Graziano
Schiavone, Nicola
Limoni, Costanzo
author_sort Scarabel, Luca
collection PubMed
description Background. Fall represents one of the highest concerns in the healthcare system, especially in medical rehabilitation settings. However, there is a lack of instruments for the assessment of risk falls in the context of musculoskeletal rehabilitation. Methods. This retrospective multisite study aimed to assess the sensitivity and specificity of four fall risk assessment tools (the Functional Independence Measure, the Fall Risk Assessment, the Schmid Fall Risk Assessment Tool, and the ePA-AC) in predicting falls in patients admitted to musculoskeletal rehabilitation in Swiss inpatient facilities. Results. The data relative to 6970 individuals (61.5% females) were analyzed and 685 (9.83% of patients) fall events were registered. The area under the curve (AUC) relative to the Functional Independence Measure was 0.689, 0.66 for the Fall Risk Assessment, 0.641 for the Schmid Fall Risk Assessment Tool, and 0.675 for the ePA-AC. Among the four tools, the Functional Independence Measure had an acceptable discriminatory power in distinguishing between significant events (i.e., patients’ falls) and non-events (no falls). Conclusion. None of the assessed tools showed highly satisfying levels of statistical sensitivity or sensibility. However, the Functional Independence Measure could be used to assess the fall risk assessment in musculoskeletal rehabilitation settings, although with some caution, since this questionnaire was not designed for this diagnostic purpose. We strongly suggest urgently designing a tool for risk assessment that is specific to this population and the rehabilitative setting.
format Online
Article
Text
id pubmed-10606819
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-106068192023-10-28 Predicting Falls in Musculoskeletal Rehabilitation: A Retrospective Multisite Study Scarabel, Luca Scarpina, Federica Ruggieri, Graziano Schiavone, Nicola Limoni, Costanzo Healthcare (Basel) Article Background. Fall represents one of the highest concerns in the healthcare system, especially in medical rehabilitation settings. However, there is a lack of instruments for the assessment of risk falls in the context of musculoskeletal rehabilitation. Methods. This retrospective multisite study aimed to assess the sensitivity and specificity of four fall risk assessment tools (the Functional Independence Measure, the Fall Risk Assessment, the Schmid Fall Risk Assessment Tool, and the ePA-AC) in predicting falls in patients admitted to musculoskeletal rehabilitation in Swiss inpatient facilities. Results. The data relative to 6970 individuals (61.5% females) were analyzed and 685 (9.83% of patients) fall events were registered. The area under the curve (AUC) relative to the Functional Independence Measure was 0.689, 0.66 for the Fall Risk Assessment, 0.641 for the Schmid Fall Risk Assessment Tool, and 0.675 for the ePA-AC. Among the four tools, the Functional Independence Measure had an acceptable discriminatory power in distinguishing between significant events (i.e., patients’ falls) and non-events (no falls). Conclusion. None of the assessed tools showed highly satisfying levels of statistical sensitivity or sensibility. However, the Functional Independence Measure could be used to assess the fall risk assessment in musculoskeletal rehabilitation settings, although with some caution, since this questionnaire was not designed for this diagnostic purpose. We strongly suggest urgently designing a tool for risk assessment that is specific to this population and the rehabilitative setting. MDPI 2023-10-23 /pmc/articles/PMC10606819/ /pubmed/37893879 http://dx.doi.org/10.3390/healthcare11202805 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Scarabel, Luca
Scarpina, Federica
Ruggieri, Graziano
Schiavone, Nicola
Limoni, Costanzo
Predicting Falls in Musculoskeletal Rehabilitation: A Retrospective Multisite Study
title Predicting Falls in Musculoskeletal Rehabilitation: A Retrospective Multisite Study
title_full Predicting Falls in Musculoskeletal Rehabilitation: A Retrospective Multisite Study
title_fullStr Predicting Falls in Musculoskeletal Rehabilitation: A Retrospective Multisite Study
title_full_unstemmed Predicting Falls in Musculoskeletal Rehabilitation: A Retrospective Multisite Study
title_short Predicting Falls in Musculoskeletal Rehabilitation: A Retrospective Multisite Study
title_sort predicting falls in musculoskeletal rehabilitation: a retrospective multisite study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606819/
https://www.ncbi.nlm.nih.gov/pubmed/37893879
http://dx.doi.org/10.3390/healthcare11202805
work_keys_str_mv AT scarabelluca predictingfallsinmusculoskeletalrehabilitationaretrospectivemultisitestudy
AT scarpinafederica predictingfallsinmusculoskeletalrehabilitationaretrospectivemultisitestudy
AT ruggierigraziano predictingfallsinmusculoskeletalrehabilitationaretrospectivemultisitestudy
AT schiavonenicola predictingfallsinmusculoskeletalrehabilitationaretrospectivemultisitestudy
AT limonicostanzo predictingfallsinmusculoskeletalrehabilitationaretrospectivemultisitestudy