Risk factors analysis and risk prediction model for failed back surgery syndrome: a prospective cohort study

Introduction: With the growing number of posterior open surgery, the incidence of failed back surgery syndrome (FBSS) increases gradually. Currently, there is a lack of predictive systems and scientific evaluation in clinical practice. This study aimed to risk factors analysis of FBSS and develop a risk prediction model. Materials and Methods Baseline data were collected from 512 patients. Patients were followed up for one year. Ultimately, 146 patients were classified in the FBSS group, with an incidence rate of 32.5%. Logistic regression was used to screen for independent risk factors influencing the occurrence of FBSS. The diagnostic power of model was evaluated using the ROC curve. Findings: Age, smoking, type of pain, revision surgery, surgical technique, quality of life, and psychological status were significantly associated with the incidence of FBSS. The strongest factor in this model was the selected surgical technique, with an odds ratio of 0.095. The area under the ROC curve for the model's diagnostic and classification power was 0.852. Conclusion The causes of FBSS can stem from underlying factors, lifestyle, surgical causes, and patients' psychological factors. Therefore, prevention and treatment for each individual should be based on their specific cause to achieve optimal results.