• World Neurosurg · Jun 2018

    Comparison of Mobi-C Cervical Disc Arthroplasty Versus Fusion for the Treatment of Symptomatic Cervical Degenerative Disc Disease.

    • Guang-Zhi Ning, Shun-Li Kan, Ru-Sen Zhu, and Shi-Qing Feng.
    • Department of Orthopaedics, Tianjin Medical University General Hospital, Tianjin, China.
    • World Neurosurg. 2018 Jun 1; 114: e224-e239.

    ObjectiveMobi-C cervical disc arthroplasty (MCDA) is an alternative to anterior cervical discectomy and fusion (ACDF). This study evaluated the effectiveness and safety of MCDA and ACDF for symptomatic cervical degenerative disc disease.MethodsDatabases were systematically searched for randomized controlled trials. Studies were included based on eligibility criteria. Risk of bias assessment and quality of evidence assessment were performed.ResultsFour studies with 785 patients were included. For clinical outcomes, MCDA were superior to ACDF with fewer subsequent surgical interventions (P < 0.00001), lower neck pain scores (P = 0.01), lower incidences of adjacent segment degeneration at both superior and inferior levels (P = 0.0003 and P = 0.01, respectively), greater range of motion of the operated segment (P < 0.0001), and higher patient satisfaction (P = 0.007). No significant differences were observed between groups regarding operative time, blood loss, duration of hospitalization, and neck disability index and arm pain scores (P > 0.05). Subgroup analyses indicated that for patients with 2-level cervical degenerative disc disease, MCDA demonstrated lower neck disability index and arm pain scores and higher patient satisfaction (P < 0.05) compared with ACDF.ConclusionsMCDA had fewer subsequent surgical interventions, lower neck pain scores, lower incidences of adjacent segment degeneration at superior and inferior levels, greater range of motion, and higher patient satisfaction scores than ACDF. MCDA was similar to ACDF regarding operative time, blood loss, duration of hospitalization, and neck disability index and neck pain scores.Copyright © 2018 Elsevier Inc. All rights reserved.

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