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.