Development of Risk Stratification Predictive Models for Cervical Deformity Surgery.

BACKGROUND

As corrective surgery for cervical deformity (CD) increases, so does the rate of complications and reoperations. To minimize suboptimal postoperative outcomes, it is important to develop a tool that allows for proper preoperative risk stratification.

OBJECTIVE

To develop a prognostic utility for identification of risk factors that lead to the development of major complications and unplanned reoperations.

METHODS

CD patients age 18 years or older were stratified into 2 groups based on the postoperative occurrence of a revision and/or major complication. Multivariable logistic regressions identified characteristics that were associated with revision or major complication. Decision tree analysis established cutoffs for predictive variables. Models predicting both outcomes were quantified using area under the curve (AUC) and receiver operating curve characteristics.

RESULTS

A total of 109 patients with CD were included in this study. By 1 year postoperatively, 26 patients experienced a major complication and 17 patients underwent a revision. Predictive modeling incorporating preoperative and surgical factors identified development of a revision to include upper instrumented vertebrae > C5, lowermost instrumented vertebrae > T7, number of unfused lordotic cervical vertebrae > 1, baseline T1 slope > 25.3°, and number of vertebral levels in maximal kyphosis > 12 (AUC: 0.82). For developing a major complication, a model included a current smoking history, osteoporosis, upper instrumented vertebrae inclination angle < 0° or > 40°, anterior diskectomies > 3, and a posterior Smith Peterson osteotomy (AUC: 0.81).

CONCLUSION

Revisions were predicted using a predominance of radiographic parameters while the occurrence of major complications relied on baseline bone health, radiographic, and surgical characteristics.