Predictors of sickness absence in patients with a new episode of low back pain in primary care
This study examines predictors of sickness absence in patients presenting to a health practitioner with acute/ subacute low back pain (LBP). Aims of this study were to identify baseline-variables that detect patients with a new LBP episode at risk of sickness absence and to identify prognostic model...
| Main Authors: | , , , , , , |
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| Format: | Journal Article |
| Published: |
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/15674 |
| _version_ | 1848748957888413696 |
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| author | Melloh, Markus Elfering, A. Salathé, C. Käser, A. Barz, T. Röder, C. Theis, J. |
| author_facet | Melloh, Markus Elfering, A. Salathé, C. Käser, A. Barz, T. Röder, C. Theis, J. |
| author_sort | Melloh, Markus |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This study examines predictors of sickness absence in patients presenting to a health practitioner with acute/ subacute low back pain (LBP). Aims of this study were to identify baseline-variables that detect patients with a new LBP episode at risk of sickness absence and to identify prognostic models for sickness absence at different time points after initial presentation. Prospective cohort study investigating 310 patients presenting to a health practitioner with a new episode of LBP at baseline, three-, six-, twelve-week and six-month follow-up, addressing work-related, psychological and biomedical factors. Multivariate logistic regression analysis was performed to identify baseline-predictors of sickness absence at different time points. Prognostic models comprised 'job control', 'depression' and 'functional limitation' as predictive baseline-factors of sickness absence at three and six-week follow-up with 'job control' being the best single predictor (OR 0.47; 95%CI 0.26-0.87). The six-week model explained 47% of variance of sickness absence at six-week follow-up (p<0.001). The prediction of sickness absence beyond six-weeks is limited, and health practitioners should re-assess patients at six weeks, especially if they have previously been identified as at risk of sickness absence. This would allow timely intervention with measures designed to reduce the likelihood of prolonged sickness absence. © 2012 National Institute of Occupational Safety and Health. |
| first_indexed | 2025-11-14T07:13:18Z |
| format | Journal Article |
| id | curtin-20.500.11937-15674 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:13:18Z |
| publishDate | 2012 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-156742017-09-13T13:41:02Z Predictors of sickness absence in patients with a new episode of low back pain in primary care Melloh, Markus Elfering, A. Salathé, C. Käser, A. Barz, T. Röder, C. Theis, J. This study examines predictors of sickness absence in patients presenting to a health practitioner with acute/ subacute low back pain (LBP). Aims of this study were to identify baseline-variables that detect patients with a new LBP episode at risk of sickness absence and to identify prognostic models for sickness absence at different time points after initial presentation. Prospective cohort study investigating 310 patients presenting to a health practitioner with a new episode of LBP at baseline, three-, six-, twelve-week and six-month follow-up, addressing work-related, psychological and biomedical factors. Multivariate logistic regression analysis was performed to identify baseline-predictors of sickness absence at different time points. Prognostic models comprised 'job control', 'depression' and 'functional limitation' as predictive baseline-factors of sickness absence at three and six-week follow-up with 'job control' being the best single predictor (OR 0.47; 95%CI 0.26-0.87). The six-week model explained 47% of variance of sickness absence at six-week follow-up (p<0.001). The prediction of sickness absence beyond six-weeks is limited, and health practitioners should re-assess patients at six weeks, especially if they have previously been identified as at risk of sickness absence. This would allow timely intervention with measures designed to reduce the likelihood of prolonged sickness absence. © 2012 National Institute of Occupational Safety and Health. 2012 Journal Article http://hdl.handle.net/20.500.11937/15674 10.2486/indhealth.MS1335 unknown |
| spellingShingle | Melloh, Markus Elfering, A. Salathé, C. Käser, A. Barz, T. Röder, C. Theis, J. Predictors of sickness absence in patients with a new episode of low back pain in primary care |
| title | Predictors of sickness absence in patients with a new episode of low back pain in primary care |
| title_full | Predictors of sickness absence in patients with a new episode of low back pain in primary care |
| title_fullStr | Predictors of sickness absence in patients with a new episode of low back pain in primary care |
| title_full_unstemmed | Predictors of sickness absence in patients with a new episode of low back pain in primary care |
| title_short | Predictors of sickness absence in patients with a new episode of low back pain in primary care |
| title_sort | predictors of sickness absence in patients with a new episode of low back pain in primary care |
| url | http://hdl.handle.net/20.500.11937/15674 |