Surgical Realignment After Anterior Multilevel Decompression Using Cages and Plate for 3-level to 5-level Degenerative Fusions: Lessons Learned From the Analysis of Geometric Changes, Reciprocal Coupling, and Prediction of Sagittal Cervical Balance.

STUDY

DESIGN

Retrospective, single-center case study.

OBJECTIVE

Postoperative cervical imbalance with cervical sagittal vertical axis (cSVA) >4 cm can be predicted in 3-level to 5-level anterior-only cervical multilevel fusion surgery (ACMS).

SUMMARY OF BACKGROUND DATA: Previous studies established correlations between cervical kyphosis (CK) correction and postoperative balance (cSVA ≤4 cm) with improved clinical outcomes. Understanding of what influences restoration of cervical lordosis (CL) in patients with degenerative disease with mild to moderate CK subjected to ACMS is important. To achieve a better understanding of geometric changes after ACMS, this study examines factors predicting perioperative alignment changes and regional interdependencies.

MATERIALS AND

METHODS

Analysis of patients with ACMS. Analysis included patient baseline characteristics, demographics and complications, and focused on radiographic measures including CL C2-7, fusion angle (FA), C7-Slope (C7S), T1-slope (T1S), T1-CL mismatch, and cSVA (cSVA ≤4 cm/>4 cm). We aimed to predict postoperative imbalance (cSVA >4 cm) and conducted a multivariable logistic regression analysis.

RESULTS

Inclusion of 126 patients with 3-level to 5-level ACMS, mean age was 56 years and 4 fusion levels on average. Preoperative CK was present in 9%, mean FA-correction was 8 degrees, maximum 46 degrees. Postoperatively, 14 patients had cSVA >4 cm. A neural network model for prediction of cSVA >4 cm was established including preoperative cSVA, preoperative CL and correction of FA. The model achieved high performance (positive predictive value=100%, negative predictive value=94%, specificity=100%, sensitivity=20%). Also, variables such as nonunion, chronic lumbar pain or thoracolumbar multilevel fusion influenced the postoperative cSVA >4 cm rate. Alignment analysis highlighted strong correlations between C7S/T1S and cSVA/C2-tilt ( r =0.06/ r =0.7, P <0.0001). A formula was established to transfer cSVA data into C2-tilt data.

CONCLUSION

This study identified independent variables predicting postoperative cSVA >4 cm including FA, which can be influenced by the surgeon. Our model supports the decision-making process targeting a postoperative cSVA ≤4 cm.