The objective of this study was to calibrate an updated predictive model incorporating novel clinical, radiographic, and prophylactic measures to assess the risk of proximal junctional kyphosis (PJK) and failure (PJF).
Operative patients with adult spinal deformity (ASD) and baseline and 2-year postoperative data were included. PJK was defined as ≥ 10° in sagittal Cobb angle between the inferior uppermost instrumented vertebra (UIV) endplate and superior endplate of the UIV + 2 vertebrae. PJF was radiographically defined as a proximal junctional sagittal Cobb angle ≥ 15° with the presence of structural failure and/or mechanical instability, or PJK with reoperation. Backstep conditional binary supervised learning models assessed baseline demographic, clinical, and surgical information to predict the occurrence of PJK and PJF. Internal cross validation of the model was performed via a 70%/30% cohort split. Conditional inference tree analysis determined thresholds at an alpha level of 0.05.
Seven hundred seventy-nine patients with ASD (mean 59.87 ± 14.24 years, 78% female, mean BMI 27.78 ± 6.02 kg/m2, mean Charlson Comorbidity Index 1.74 ± 1.71) were included. PJK developed in 50.2% of patients, and 10.5% developed PJF by their last recorded visit. The six most significant demographic, radiographic, surgical, and postoperative predictors of PJK/PJF were baseline age ≥ 74 years, baseline sagittal age-adjusted score (SAAS) T1 pelvic angle modifier > 1, baseline SAAS pelvic tilt modifier > 0, levels fused > 10, nonuse of prophylaxis measures, and 6-week SAAS pelvic incidence minus lumbar lordosis modifier > 1 (all p < 0.015). Overall, the model was deemed significant (p < 0.001), and internally validated receiver operating characteristic analysis returned an area under the curve of 0.923, indicating robust model fit.
PJK and PJF remain critical concerns in ASD surgery, and efforts to reduce the occurrence of PJK and PJF have resulted in the development of novel prophylactic techniques and enhanced clinical and radiographic selection criteria. This study demonstrates a validated model incorporating such techniques that may allow for the prediction of clinically significant PJK and PJF, and thus assist in optimizing patient selection, enhancing intraoperative decision making, and reducing postoperative complications in ASD surgery.