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Development of Risk Stratification Predictive Models for Cervical Deformity Surgery.

Peter G Passias1, Waleed Ahmad1, Cheongeun Oh1

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Summary

This study identifies key risk factors for cervical deformity (CD) surgery complications and reoperations. Predictive models using radiographic and surgical data can improve patient outcomes and surgical planning.

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Area of Science:

  • Spine surgery
  • Orthopedics
  • Surgical outcomes

Background:

  • Corrective surgery for cervical deformity (CD) is increasing.
  • Complications and reoperations are significant concerns post-CD surgery.

Purpose of the Study:

  • Develop a prognostic tool for preoperative risk stratification in CD patients.
  • Identify risk factors for major complications and unplanned reoperations after CD surgery.

Main Methods:

  • Stratified 109 CD patients (age ≥ 18) into revision/major complication groups.
  • Used multivariable logistic regression and decision tree analysis.
  • Quantified predictive models using area under the curve (AUC).

Main Results:

  • Revision prediction model included specific vertebral levels, T1 slope, and kyphosis parameters (AUC: 0.82).
  • Major complication model included smoking, osteoporosis, instrumented vertebrae angle, diskectomies, and osteotomy (AUC: 0.81).

Conclusions:

  • Revisions are primarily predicted by radiographic parameters.
  • Major complications depend on bone health, radiographic, and surgical factors.