LAUSR

To evaluate the predictive precision of the Dialogue Support, a tool for additional help in shared decision-making before surgery of the degenerative spine. Data in Swespine (Swedish national quality registry) of patients operated between 2007 and 2019 found the development of prediction algorithms based on logistic regression analyses, where socio-demographic and baseline variables were included. The algorithms were tested in four diagnostic groups: lumbar disc herniation, lumbar spinal stenosis, degenerative disc disease and cervical radiculopathy. By random selection, 80% of the study population was used for the prediction of outcome and then tested against the actual outcome of the remaining 20%. Outcome measures were global assessment of pain (GA), and satisfaction with outcome. Calibration plots demonstrated a high degree of concordance on a group level. On an individual level, ROC curves showed moderate predictive capacity with AUC (area under the curve) values 0.67–0.68 for global assessment and 0.6–0.67 for satisfaction. The Dialogue Support can serve as an aid to both patient and surgeon when discussing and deciding on surgical treatment of degenerative conditions in the lumbar and cervical spine. I.