Predicting chronic low-back pain based on pain trajectories in patients in an occupational setting: an exploratory analysis.
- Publisher:
- SCANDINAVIAN JOURNAL WORK ENVIRONMENT & HEALTH
- Publication Type:
- Journal Article
- Citation:
- Scand J Work Environ Health, 2016, 42, (6), pp. 520-527
- Issue Date:
- 2016-06-01
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Field | Value | Language |
---|---|---|
dc.contributor.author | Panken, G | |
dc.contributor.author | Hoekstra, T | |
dc.contributor.author |
Verhagen, A https://orcid.org/0000-0002-6195-0128 |
|
dc.contributor.author | van Tulder, M | |
dc.contributor.author | Twisk, J | |
dc.contributor.author | Heymans, MW | |
dc.date.accessioned | 2022-07-18T06:46:54Z | |
dc.date.available | 2022-07-18T06:46:54Z | |
dc.date.issued | 2016-06-01 | |
dc.identifier.citation | Scand J Work Environ Health, 2016, 42, (6), pp. 520-527 | |
dc.identifier.issn | 0355-3140 | |
dc.identifier.issn | 1795-990X | |
dc.identifier.uri | http://hdl.handle.net/10453/159007 | |
dc.description.abstract | OBJECTIVE: This study aimed to (i) identify subpopulations of patients in an occupational setting who will still have or develop chronic low-back pain (LBP) and (ii) evaluate a previously developed prediction model based on the determined subpopulations. METHOD: In this prospective cohort, study data were analyzed from three merged randomized controlled trials, conducted in an occupational setting (N=622). Latent class growth analysis (LCGA) was used to distinguish patients with a different course of pain intensity measured over 12 months. The determined subpopulations were used to derive a definition for chronic LBP and evaluate an existing model to predict chronic LBP. RESULTS: The LCGA model identified three subpopulations of LBP patients. These were used to define recovering (353) and chronic (269) patients. None of the interventions showed a relevant treatment effect over another but the rate of decline in symptoms during the first months of the intervention seems to predict recovery. The prediction model, based on this dichotomous outcome, with the variables pain intensity, kinesiophobia and a clinically relevant change in pain intensity and functional status in the first three months, showed a bootstrap-corrected performance with an area under the operating characteristic curve (AUC) of 0.75 and explained variance of 0.26. CONCLUSION: In an occupational setting, different subpopulations of chronic LBP patients could be identified using LCGA. The prediction model based on these subpopulations showed a promising predictive performance. | |
dc.format | Print-Electronic | |
dc.language | eng | |
dc.publisher | SCANDINAVIAN JOURNAL WORK ENVIRONMENT & HEALTH | |
dc.relation.ispartof | Scand J Work Environ Health | |
dc.relation.isbasedon | 10.5271/sjweh.3584 | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | 1117 Public Health and Health Services, 1701 Psychology | |
dc.subject.classification | Environmental & Occupational Health | |
dc.subject.mesh | Adult | |
dc.subject.mesh | Chronic Pain | |
dc.subject.mesh | Disability Evaluation | |
dc.subject.mesh | Female | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Low Back Pain | |
dc.subject.mesh | Male | |
dc.subject.mesh | Models, Statistical | |
dc.subject.mesh | Occupational Health | |
dc.subject.mesh | Pain Measurement | |
dc.subject.mesh | Predictive Value of Tests | |
dc.subject.mesh | Prospective Studies | |
dc.subject.mesh | Recovery of Function | |
dc.subject.mesh | Sick Leave | |
dc.subject.mesh | Surveys and Questionnaires | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Low Back Pain | |
dc.subject.mesh | Pain Measurement | |
dc.subject.mesh | Disability Evaluation | |
dc.subject.mesh | Models, Statistical | |
dc.subject.mesh | Prospective Studies | |
dc.subject.mesh | Predictive Value of Tests | |
dc.subject.mesh | Recovery of Function | |
dc.subject.mesh | Adult | |
dc.subject.mesh | Occupational Health | |
dc.subject.mesh | Sick Leave | |
dc.subject.mesh | Female | |
dc.subject.mesh | Male | |
dc.subject.mesh | Chronic Pain | |
dc.subject.mesh | Surveys and Questionnaires | |
dc.title | Predicting chronic low-back pain based on pain trajectories in patients in an occupational setting: an exploratory analysis. | |
dc.type | Journal Article | |
utslib.citation.volume | 42 | |
utslib.location.activity | Finland | |
utslib.for | 1117 Public Health and Health Services | |
utslib.for | 1701 Psychology | |
pubs.organisational-group | /University of Technology Sydney | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Health | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Health/Graduate School of Health | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Health/Graduate School of Health/GSH.Physiotherapy | |
utslib.copyright.status | open_access | * |
dc.date.updated | 2022-07-18T06:46:53Z | |
pubs.issue | 6 | |
pubs.publication-status | Published | |
pubs.volume | 42 | |
utslib.citation.issue | 6 |
Abstract:
OBJECTIVE: This study aimed to (i) identify subpopulations of patients in an occupational setting who will still have or develop chronic low-back pain (LBP) and (ii) evaluate a previously developed prediction model based on the determined subpopulations. METHOD: In this prospective cohort, study data were analyzed from three merged randomized controlled trials, conducted in an occupational setting (N=622). Latent class growth analysis (LCGA) was used to distinguish patients with a different course of pain intensity measured over 12 months. The determined subpopulations were used to derive a definition for chronic LBP and evaluate an existing model to predict chronic LBP. RESULTS: The LCGA model identified three subpopulations of LBP patients. These were used to define recovering (353) and chronic (269) patients. None of the interventions showed a relevant treatment effect over another but the rate of decline in symptoms during the first months of the intervention seems to predict recovery. The prediction model, based on this dichotomous outcome, with the variables pain intensity, kinesiophobia and a clinically relevant change in pain intensity and functional status in the first three months, showed a bootstrap-corrected performance with an area under the operating characteristic curve (AUC) of 0.75 and explained variance of 0.26. CONCLUSION: In an occupational setting, different subpopulations of chronic LBP patients could be identified using LCGA. The prediction model based on these subpopulations showed a promising predictive performance.
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