A prediction rule for shoulder pain related sick leave: a prospective cohort study
1 Institute for Research in Extramural Medicine, VU University Medical Center, Amsterdam, The Netherlands
2 Department of Allied Health Care Research, Amsterdam School of Allied Health Care Education, The Netherlands
3 Care and Public Health Research Institute, Maastricht University, The Netherlands
4 Primary Care Musculoskeletal Research Centre, Keele University, Keele Staffordshire, UK
5 Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands
6 Department of Clinical Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
BMC Musculoskeletal Disorders 2006, 7:97 doi:10.1186/1471-2474-7-97Published: 6 December 2006
Shoulder pain is common in primary care, and has an unfavourable outcome in many patients. Information about predictors of shoulder pain related sick leave in workers is scarce and inconsistent. The objective was to develop a clinical prediction rule for calculating the risk of shoulder pain related sick leave for individual workers, during the 6 months following first consultation in general practice.
A prospective cohort study with 6 months follow-up was conducted among 350 workers with a new episode of shoulder pain. Potential predictors included the results of a physical examination, sociodemographic variables, disease characteristics (duration of symptoms, sick leave in the 2 months prior to consultation, pain intensity, disability, comorbidity), physical activity, physical work load, psychological factors, and the psychosocial work environment. The main outcome measure was sick leave during 6 months following first consultation in general practice.
Response rate to the follow-up questionnaire at 6 months was 85%. During the 6 months after first consultation 30% (89/298) of the workers reported sick leave. 16% (47) reported 10 days sick leave or more. Sick leave during this period was predicted in a multivariable model by a longer duration of sick leave prior to consultation, more shoulder pain, a perceived cause of strain or overuse during regular activities, and co-existing psychological complaints. The discriminative ability of the prediction model was satisfactory with an area under the curve of 0.70 (95% CI 0.64–0.76).
Although 30% of all workers with shoulder pain reported sick leave during follow-up, the duration of sick leave was limited to a few days in most workers. We developed a prediction rule and a score chart that can be used by general practitioners and occupational health care providers to calculate the absolute risk of sick leave in individual workers with shoulder pain, which may help to identify workers who need additional attention. The performance and applicability of our model needs to be tested in other working populations with shoulder pain to enable valid and reliable use of the score chart in everyday practice.