Multicenter retrospective study.Objective.
To validate and improve the predictive model for proximal junctional failure (PJF) with or without the bone mineral density (BMD) score.Summary of Background Data.
PJF is a serious complication of surgery for adult spinal deformity (ASD). A predictive model for PJF was recently reported that has good accuracy, but does not include BMD, a known PJF risk factor, as a variable.Methods.
We included 145 surgically treated ASD patients who were older than 50 at the time of surgery and had been followed up for at least 2 years. Variables included age, sex, body mass index (BMI), fusion level, upper and lower instrumented vertebral (UIV and LIV) level, primary or revision surgery, pedicle subtraction osteotomy (PSO), Schwab-SRS type, and BMD. PJF was defined as a ≥ 20° increase from baseline (immediately postoperative) of the proximal junctional angle with concomitant deterioration of at least 1 SRS-Schwab sagittal modifier grade, or any proximal junctional kyphosis requiring revision. Decision-making trees were constructed using the C5.0 algorithm with 10 different bootstrapped models, and validated by a 7:3 data split for training and testing; 112 patients were categorized as training and 33 as testing samples.Results.
PJF incidence was 20% in the training samples. Univariate analyses showed that BMD, BMI, pelvic tilt (PT), UIV level, and LIV level were PJF risk factors. Our predictive model was 100% accurate in the testing samples with an AUC of 1.0, indicating excellent fit. The best predictors were (strongest to weakest): PT, BMD, LIV level (pelvis), UIV level (lower thoracic), PSO, global alignment, BMI, pelvic incidence minus lumbar lordosis, and age.Conclusion.
A successful model was developed for predicting PJF that included BMD. Our model could inform physicians about patients with a high risk of developing PJF in the perioperative period.Conclusion.
Level of Evidence: 4