Treatment of the two-level degenerative cervical disk diseases based on algorithmic anterior approach: a multicenter prospective study.

To analyze the effectiveness of an algorithmic anterior approach to the surgical treatment of patients with two-level cervical degenerative disk disease based on the preoperative clinical and imaging parameters. The study included 244 patients with two-level cervical degenerative disk disease. Three groups of patients were evaluated at 3 neurosurgical centers between 2016-2019. The prospective group (Group I, n = 126) consisted of patients who were treated using an algorithm to decide whether they should be treated with a two-level Total Disk replacement (TDR), Anterior Cervical Discectomy and Fusion (ACDF) and hybrid technique. The control group (Group II, n = 118) consisted of patients who underwent two-level anterior decompression with TDR, ACDF and hybrid stabilization between 2005-2015. Visual Analogue Scale (VAS) neck pain, VAS upper limbs pain, Neck Disability Index (NDI), SF-36, Macnab and Nurick scales were collected. Perioperative complications were identified. At 2 years of follow up Group I had significantly better clinical outcomes based on VAS neck pain score (p = 0.02), VAS upper limbs pain (p = 0.04), NDI score (p = 0.02), SF-36 score (p = 0.01), satisfaction with surgery on the Macnab scale (p < 0.001) and outcome of surgery based on Nurick scale (p < 0.001). Complication rate was lower in Group I, 6.3% compared to 24.6% in Group II, p = 0.0001. The algorithmic anterior approach to the surgical treatment of patients with two-level cervical degenerative disk disease resulted in significant improvement of functional outcomes and a decrease in complications at a minimum 2 years of follow-up.

An Algorithmic Posterior Approach to the Treatment of Multilevel Degenerative Cervical Spine Disease: A Multicenter Prospective Study.

BACKGROUND: The choice of surgical method for the treatment of multilevel degenerative cervical spine disease is based on the assessment of neurological symptoms and anatomical source of compression. However, such decision-making process remains complex and poorly defined. PURPOSE: To analyze the effectiveness of an algorithmic posterior approach to the surgical treatment of patients with multilevel degenerative disease of the cervical spine based on the preoperative clinical and imaging parameters. STUDY DESIGN: Prospective nonrandomized multicenter cohort study. METHODS: The study included 338 patients with multilevel degenerative disease of the cervical spine. Two groups of patients were evaluated at 3 neurosurgical centers between 2015 and 2019. The prospective group (Group I, n = 214) consisted of patients who were treated using an algorithm to decide whether they should be treated with an instrumented arthrodesis or a nonfusion procedure. The control group (Group II, n = 124) consisted of patients who underwent posterior decompression with or without stabilization between 2007 and 2014. A total of 192 patients in Group I and 112 in Group II had more than 2 years of follow-up. Visual analog scale (VAS) neck pain, Neck Disability Index (NDI), MacNab and Nurick Scales were collected. Perioperative complications were identified. RESULTS: At 2-year follow-up, Group I had significantly better clinical outcomes based on VAS neck pain score (P = 0.02), NDI score (P = 0.01), satisfaction with surgery on the MacNab Scale (P < 0.001), and outcome of surgery based on the Nurick Scale (P < 0.001). Complication rate was lower in Group I, 5.7% compared with 34.8% in Group II, P = 0.004. CONCLUSIONS: The algorithmic posterior approach to the surgical treatment of patients with multilevel degenerative disease of the cervical spine resulted in significant improvement of functional outcomes and a decrease in complications at a minimum 2 years of follow-up.