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Development of a clinical prediction model to inform clinical decision making for classification of patients with sciatica, based on their clinical characteristics, in the Greek health system: protocol for a prospective predictive exploratory study
INTRODUCTION: Sciatica is one of the most common reasons for seeking healthcare for musculoskeletal pain. Sciatica is primarily considered as neuropathic in nature when neural tissue in the low back is compromised, but sometimes other non-neural structures may be involved. Appropriate assessment and...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8804639/ https://www.ncbi.nlm.nih.gov/pubmed/35105622 http://dx.doi.org/10.1136/bmjopen-2021-052119 |
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author | Kontakiotis, Nikolaos Rushton, Alison B Billis, Evdokia Papathanasiou, George Gioftsos, George |
author_facet | Kontakiotis, Nikolaos Rushton, Alison B Billis, Evdokia Papathanasiou, George Gioftsos, George |
author_sort | Kontakiotis, Nikolaos |
collection | PubMed |
description | INTRODUCTION: Sciatica is one of the most common reasons for seeking healthcare for musculoskeletal pain. Sciatica is primarily considered as neuropathic in nature when neural tissue in the low back is compromised, but sometimes other non-neural structures may be involved. Appropriate assessment and management are important for patients with sciatica. Therapists use several outcome measures to assess patients to inform selection of the most suitable treatment. There is limited evidence for the best treatment of sciatica, and this is likely contributed to by having no reliable algorithm to categorise patients based on their clinical characteristics to inform physiotherapy treatment. The purpose of this study is to develop a clinical prediction model to categorise patients with sciatica, in terms of early clinical outcome, based on their initial clinical characteristics. METHODS AND ANALYSIS: A prospective observational multicentre design will recruit consecutive patients (n=467) with sciatica referred for physiotherapy. Each patient will be evaluated to determine whether or not they will be accepted into the study by answering some questions that will confirm the study’s eligibility criteria. Patients’ basic characteristics, patient-reported outcome measures and performance-based measures will be collected at baseline from multiple sites in the Greek territory using this same protocol, prior to commencement of treatment. The main researcher of this study will be responsible for data collection in all sites. On completion of the standard referred physiotherapy treatment after 3 weeks’ time, participants will be asked by telephone to evaluate their outcome using the Global Perceived Effect Scale. For the descriptive statistical analysis, the continuous variables will be expressed in the form of ‘mean’ and ‘SD’. In order to assess the prognostic value of each predictor, in terms of the level of improvement or worsening of the symptoms, multiple variable regression analysis will be used. ETHICS AND DISSEMINATION: Τhis study is approved from the Ethics and Deontology Committee of the University of West Attica, Athens, Greece, protocol number: 38313-09/06/2020, 10226-10/02/2021. The study’s findings will be published in a peer-reviewed journal and disseminated at national and international conferences and through social media. PROSPERO REGISTRATION NUMBER: CRD42020168467. |
format | Online Article Text |
id | pubmed-8804639 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-88046392022-02-07 Development of a clinical prediction model to inform clinical decision making for classification of patients with sciatica, based on their clinical characteristics, in the Greek health system: protocol for a prospective predictive exploratory study Kontakiotis, Nikolaos Rushton, Alison B Billis, Evdokia Papathanasiou, George Gioftsos, George BMJ Open Rehabilitation Medicine INTRODUCTION: Sciatica is one of the most common reasons for seeking healthcare for musculoskeletal pain. Sciatica is primarily considered as neuropathic in nature when neural tissue in the low back is compromised, but sometimes other non-neural structures may be involved. Appropriate assessment and management are important for patients with sciatica. Therapists use several outcome measures to assess patients to inform selection of the most suitable treatment. There is limited evidence for the best treatment of sciatica, and this is likely contributed to by having no reliable algorithm to categorise patients based on their clinical characteristics to inform physiotherapy treatment. The purpose of this study is to develop a clinical prediction model to categorise patients with sciatica, in terms of early clinical outcome, based on their initial clinical characteristics. METHODS AND ANALYSIS: A prospective observational multicentre design will recruit consecutive patients (n=467) with sciatica referred for physiotherapy. Each patient will be evaluated to determine whether or not they will be accepted into the study by answering some questions that will confirm the study’s eligibility criteria. Patients’ basic characteristics, patient-reported outcome measures and performance-based measures will be collected at baseline from multiple sites in the Greek territory using this same protocol, prior to commencement of treatment. The main researcher of this study will be responsible for data collection in all sites. On completion of the standard referred physiotherapy treatment after 3 weeks’ time, participants will be asked by telephone to evaluate their outcome using the Global Perceived Effect Scale. For the descriptive statistical analysis, the continuous variables will be expressed in the form of ‘mean’ and ‘SD’. In order to assess the prognostic value of each predictor, in terms of the level of improvement or worsening of the symptoms, multiple variable regression analysis will be used. ETHICS AND DISSEMINATION: Τhis study is approved from the Ethics and Deontology Committee of the University of West Attica, Athens, Greece, protocol number: 38313-09/06/2020, 10226-10/02/2021. The study’s findings will be published in a peer-reviewed journal and disseminated at national and international conferences and through social media. PROSPERO REGISTRATION NUMBER: CRD42020168467. BMJ Publishing Group 2022-01-31 /pmc/articles/PMC8804639/ /pubmed/35105622 http://dx.doi.org/10.1136/bmjopen-2021-052119 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Rehabilitation Medicine Kontakiotis, Nikolaos Rushton, Alison B Billis, Evdokia Papathanasiou, George Gioftsos, George Development of a clinical prediction model to inform clinical decision making for classification of patients with sciatica, based on their clinical characteristics, in the Greek health system: protocol for a prospective predictive exploratory study |
title | Development of a clinical prediction model to inform clinical decision making for classification of patients with sciatica, based on their clinical characteristics, in the Greek health system: protocol for a prospective predictive exploratory study |
title_full | Development of a clinical prediction model to inform clinical decision making for classification of patients with sciatica, based on their clinical characteristics, in the Greek health system: protocol for a prospective predictive exploratory study |
title_fullStr | Development of a clinical prediction model to inform clinical decision making for classification of patients with sciatica, based on their clinical characteristics, in the Greek health system: protocol for a prospective predictive exploratory study |
title_full_unstemmed | Development of a clinical prediction model to inform clinical decision making for classification of patients with sciatica, based on their clinical characteristics, in the Greek health system: protocol for a prospective predictive exploratory study |
title_short | Development of a clinical prediction model to inform clinical decision making for classification of patients with sciatica, based on their clinical characteristics, in the Greek health system: protocol for a prospective predictive exploratory study |
title_sort | development of a clinical prediction model to inform clinical decision making for classification of patients with sciatica, based on their clinical characteristics, in the greek health system: protocol for a prospective predictive exploratory study |
topic | Rehabilitation Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8804639/ https://www.ncbi.nlm.nih.gov/pubmed/35105622 http://dx.doi.org/10.1136/bmjopen-2021-052119 |
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