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Predicting outcomes of acute low back pain patients in emergency department: A prospective observational cohort study
Low back pain (LBP) is a common complaint among patients presenting to emergency department (ED) in Singapore. The STarT Back Screening Tool (SBT) was recently developed and validated for triage of LBP patients in primary care settings. This study aimed to investigate whether the SBT could provide p...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039631/ https://www.ncbi.nlm.nih.gov/pubmed/29952991 http://dx.doi.org/10.1097/MD.0000000000011247 |
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author | Tan, Celia Ia Choo Liaw, Jennifer Suet Ching Jiang, Bo Pothiawala, Sohil Equbal Li, Huihua Leong, Mark Kwok Fai |
author_facet | Tan, Celia Ia Choo Liaw, Jennifer Suet Ching Jiang, Bo Pothiawala, Sohil Equbal Li, Huihua Leong, Mark Kwok Fai |
author_sort | Tan, Celia Ia Choo |
collection | PubMed |
description | Low back pain (LBP) is a common complaint among patients presenting to emergency department (ED) in Singapore. The STarT Back Screening Tool (SBT) was recently developed and validated for triage of LBP patients in primary care settings. This study aimed to investigate whether the SBT could provide prognostic information for long-term outcomes of acute LBP patients visiting the ED, who might benefit from appropriate and timely management at an earlier stage. Data were collected in a prospective observational cohort study from 177 patients who consulted emergency physicians for acute LBP and completed 6-month follow-up. Patients were administered the SBT and assessed at baseline. Follow-up assessments were conducted at 6 weeks and 6 months. A multiple linear regression model incorporating SBT total score, age, employment status, LBP history, and 6-week pain score was constructed to predict 6-month pain score. In the model, SBT total score and 6-week pain score were significantly associated with 6-month pain score (P < .05) with respective coefficients of 0.125 and 0.500. The model explained 40.1% of the variance for 6-month pain score. This study demonstrated that the multiple linear regression model showed predictive performance in determining long-term outcomes for acute LBP patients presenting to the ED. |
format | Online Article Text |
id | pubmed-6039631 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-60396312018-07-16 Predicting outcomes of acute low back pain patients in emergency department: A prospective observational cohort study Tan, Celia Ia Choo Liaw, Jennifer Suet Ching Jiang, Bo Pothiawala, Sohil Equbal Li, Huihua Leong, Mark Kwok Fai Medicine (Baltimore) Research Article Low back pain (LBP) is a common complaint among patients presenting to emergency department (ED) in Singapore. The STarT Back Screening Tool (SBT) was recently developed and validated for triage of LBP patients in primary care settings. This study aimed to investigate whether the SBT could provide prognostic information for long-term outcomes of acute LBP patients visiting the ED, who might benefit from appropriate and timely management at an earlier stage. Data were collected in a prospective observational cohort study from 177 patients who consulted emergency physicians for acute LBP and completed 6-month follow-up. Patients were administered the SBT and assessed at baseline. Follow-up assessments were conducted at 6 weeks and 6 months. A multiple linear regression model incorporating SBT total score, age, employment status, LBP history, and 6-week pain score was constructed to predict 6-month pain score. In the model, SBT total score and 6-week pain score were significantly associated with 6-month pain score (P < .05) with respective coefficients of 0.125 and 0.500. The model explained 40.1% of the variance for 6-month pain score. This study demonstrated that the multiple linear regression model showed predictive performance in determining long-term outcomes for acute LBP patients presenting to the ED. Wolters Kluwer Health 2018-06-29 /pmc/articles/PMC6039631/ /pubmed/29952991 http://dx.doi.org/10.1097/MD.0000000000011247 Text en Copyright © 2018 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms. http://creativecommons.org/licenses/by-nc-sa/4.0 |
spellingShingle | Research Article Tan, Celia Ia Choo Liaw, Jennifer Suet Ching Jiang, Bo Pothiawala, Sohil Equbal Li, Huihua Leong, Mark Kwok Fai Predicting outcomes of acute low back pain patients in emergency department: A prospective observational cohort study |
title | Predicting outcomes of acute low back pain patients in emergency department: A prospective observational cohort study |
title_full | Predicting outcomes of acute low back pain patients in emergency department: A prospective observational cohort study |
title_fullStr | Predicting outcomes of acute low back pain patients in emergency department: A prospective observational cohort study |
title_full_unstemmed | Predicting outcomes of acute low back pain patients in emergency department: A prospective observational cohort study |
title_short | Predicting outcomes of acute low back pain patients in emergency department: A prospective observational cohort study |
title_sort | predicting outcomes of acute low back pain patients in emergency department: a prospective observational cohort study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039631/ https://www.ncbi.nlm.nih.gov/pubmed/29952991 http://dx.doi.org/10.1097/MD.0000000000011247 |
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