Impact of factors on treatment outcomes in cervical degenerative disc disease: a logistic regression analysis of anterior decompression and interbody fusion with BAK/C technique.

Objectives: To identify predictive prognostic factors through logistic regression analysis in patients with cervical degenerative disc disease (CDDD) undergoing anterior cervical discectomy and fusion (ACDF) combined with the Bagby and Kuslich (BAK/C) interbody fusion technique. Methods: This retrospective study included 80 patients treated with ACDF and BAK/C between January and December 2020, with a 3-year follow-up. Patients were stratified into a control group (favorable recovery, n = 52) and an observation group (poor recovery, n = 28) based on pain relief and neurological improvement. Radiological fusion rates and Japanese Orthopaedic Association (JOA) scores were evaluated. Multivariate logistic regression was performed to assess independent predictors of outcomes. Results: The control group exhibited significant JOA score improvement at the final follow-up (14.49 ± 0.25 vs. preoperative 10.74 ± 1.16, P < 0.001), while the observation group showed limited recovery (12.19 ± 0.32 vs. preoperative 11.15 ± 1.45, P < 0.001). The overall fusion rate was significantly higher in the control group (92.3% vs. 64.3%, P = 0.002). Multivariate analysis identified age ≥55 years (observation group: 62.35 ± 5.41 vs. control: 51.47 ± 6.37, P < 0.001), reduced bone mineral density (T-score: -2.1 ± 0.8 vs. -1.3 ± 0.6, P < 0.001), postoperative complications (46.4% vs. 13.5%, P = 0.003), and baseline disease severity as independent risk factors for poor outcomes (P < 0.05). The observation group demonstrated significantly higher pseudoarthrosis rates (35.7% vs. 9.6%, P = 0.003). Conclusion: Advanced age, low bone density, and postoperative complications critically compromise outcomes of ACDF with BAK/C fusion. Preoperative bone density optimization, judicious use of augmented multi-level fixation, and precision patient selection are pivotal for improving prognosis. These findings provide evidence-based insights for individualized clinical decision-making.