General Session: Innovative Technologies II - Hall F

Presented by: P. Passias


P. Passias(1), C. Oh(1), S. Horn(1), H.J. Kim(2), D.K. Hamilton(3), D. Sciubba(4), B. Neuman(5), A. Buckland(1), G. Poorman(1), C. Bortz(1), F. Segreto(1), N. Frangella(1), C. Varlotta(1), T. Protopsaltis(1), E. Klineberg(6), C. Ames(7), J. Smith(8), V. Lafage(2), International Spine Study Group

(1) New York University Langone Orthopedic Hospital, Division of Spinal Surgery, New York, NY, United States
(2) Hospital for Special Surgery, Department of Orthopaedic Surgery, New York, NY, United States
(3) University of Pittsburgh, Department of Neurologic Surgery, Pittsburgh, PA, United States
(4) Johns Hopkins University, Department of Neurosurgery, Baltimore, MD, United States
(5) Johns Hopkins University, Department of Orthopaedics, Baltimore, MD, United States
(6) University of California Davis, Department of Orthopaedic Surgery, Sacramento, CA, United States
(7) University of California San Francisco, Department of Neurological Surgery, San Francisco, CA, United States
(8) University of Virginia, Department of Neurosurgery, Charlottesville, VA, United States


Introduction: Multivariate regression models may be useful in determining the relative impact of patient and clinical predictors for adverse outcomes. Cervical deformity (CD) surgical patients are growing in number, but remain under-studied in the literature. The purpose of this study was to develop a predictive model that could describe factors that may predict surgical and medical complications in cervical deformity surgeries.

Methods: Retrospective review of prospective, multicenter CD database. CD was defined as at least one of the following: C2-C7 Cobb>10°, CL>10°, cSVA>4cm, CBVA>25°. Medical complications included: cardiopulmonary, dysphagia, GI/GU, neurologic, respiratory, peripheral vascular, post-op shock; surgical complications included: surgical site infection, vessel nerve injury, dural tear, hemorrhagic anemia, wound dehiscence, hematoma/seroma, radiographic and implant failure. Univariable and multiple logistic regression analyses were performed to assess each independent variable with the development of any complication, a medical complication, and a surgical complication.

Results: 123 patients underwent CD corrective surgery (mean age 60.6 years, 60.8% female). Surgical approaches included anterior-only (16.3%), posterior-only (50.4%), and combined approach (33.3%). The mean levels fused were 8.11 levels, average operation time was 297.40 minutes, and estimated blood loss was 776.59cc. A total of 93 (75.6%) complications were reported up to 1-year. The most common complications were neurologic (24.4%), dysphagia (13.0%), cardiopulmonary (11.4%), infection (9.7%). 51 (41.5%) patients experienced a medical complication (cardiac, dysphagia, neurologic most common) and 73 (59.3%) had a surgical complication (infection, dural tear, DJK most common). According to univariate logistic regression analysis, patients with worse baseline cSVA had an increased complication risk (OR: 2.15, CI: 1.03, 4.49). Corpectomy (OR: 0.54, CI: 0.30, 0.98), higher baseline cSVA (OR: 1.02, CI: 1.00, 1.04), and larger McGregor's slope (OR:1.03, CI: 1.00, 1.03) increased chances of a medical complication. Higher blood loss (per 500cc) (OR:1.434, CI: 1.086, 1.894) and baseline global SVA (OR: 1.93, CI:1.04, 3.59) increased the chances of a surgical complication. An overall complication can be predicted with high accuracy (AUC=0.80) by the following combinations of factors: male gender, higher baseline EQ5D pain and lower baseline EQ5D anxiety/depression scores, and higher cervical and global SVA. A medical complication can be predicted by male gender, baseline mJOA score, hand numbness, and cervical SVA (AUC=0.770). A surgical complication can be predicted by higher estimated blood loss, lower anxiety scores, and larger global SVA (AUC=0.739).

Conclusions: Impressively, 75.6% of patients undergoing cervical deformity correction sustained any kind of complication. While the most reliable predictor of the occurrence of a complication involved a cluster of risk factors, a radiographic baseline sagittal parameter of cervical SVA was the strongest isolated predictor for complications across categories. Although these findings are specific to a cervical deformity population with moderate to severe deformities, collectively they can be utilized for pre-operative risk assessment and patient education.