Which patient-reported factors predict referral to spinal surgery? A cohort study among 4987 chronic low back pain patients
SourceEuropean Spine Journal, 26, 11, (2017), pp. 2782-2788
Article / Letter to editor
Display more detailsDisplay less details
European Spine Journal
SubjectRadboudumc 10: Reconstructive and regenerative medicine RIHS: Radboud Institute for Health Sciences
PURPOSE: It is unknown which chronic low back pain (CLBP) patients are typically referred to spinal surgery. The present study, therefore, aimed to explore which patient-reported factors are predictive of spinal surgery referral among CLBP patients. METHODS: CLBP patients were consecutively recruited from a Dutch orthopedic hospital specialized in spine care (n = 4987). The outcome of this study was referral to spinal surgery (yes/no), and was assessed using hospital records. Possible predictive factors were assessed using a screening questionnaire. A prediction model was constructed using logistic regression, with backwards selection and p < 0.10 for keeping variables in the model. The model was internally validated and evaluated using discrimination and calibration measures. RESULTS: Female gender, previous back surgery, high intensity leg pain, somatization, and positive treatment expectations increased the odds of being referred to spinal surgery, while being obese, having comorbidities, pain in the thoracic spine, increased walking distance, and consultation location decreased the odds. The model's fit was good (X (2) = 10.5; p = 0.23), its discriminative ability was poor (AUC = 0.671), and its explained variance was low (5.5%). A post hoc analysis indicated that consultation location was significantly associated with spinal surgery referral, even after correcting for case-mix variables. CONCLUSION: Some patient-reported factors could be identified that are predictive of spinal surgery referral. Although the identified factors are known as common predictive factors of surgery outcome, they could only partly predict spinal surgery referral.
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.