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Developing a Treatment Algorithm for the Management of Cervical Deformity, or Developing an Algorithm for the
Luis Felipe Colón1, Eric Zhao, Han Jo Kim
1Department of Orthopaedic Surgery, Spine Service, Hospital for Special Surgery, New York City, New York.
Study Design:
Narrative review.
Objective:
Summarize current classification systems, preoperative considerations, surgical approaches, and outcomes in patients with cervical deformity.
Summary Of Background Data:
Cervical deformity (CD) is a complex pathology with varying presentations. Surgical management of CD is debated, in part due to uncertainty in CD classifications. This review summarizes the current knowledge on CD classification, management, and postoperative outcomes.
Methods:
Review of literature on CD.
Results:
Two major classification systems for CD currently exist. The earlier Ames system is limited in clinical applicability due to complexity and extensive imaging requirements, while the Kim system is simpler, based on patient-reported outcomes, and utilizes dynamic imaging, which assists with surgical level selection. CD treatment necessitates a thorough understanding of patient medical and surgical history, physical examination, and analysis of static and dynamic preoperative imaging. Long-term treatment of CD requires surgical intervention, performed through anterior, posterior, or combined approaches, involving fusions and/or decompressions, various osteotomies, and corpectomies. Despite substantial complication rates, patients often experience significant improvements in pain and functionality after surgery.
Conclusions:
CD involves complex and varying patient presentations, pathology subtypes, and surgical treatment options. Optimizing patient outcomes requires tailored surgical management and a thorough understanding of patient pathology and presentation.
