STUDY DESIGN: 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. LEVEL OF EVIDENCE: 4.
STUDY DESIGN: 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 ASDpatients 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. LEVEL OF EVIDENCE: 4.
Authors: Sohrab Virk; Uwe Platz; Shay Bess; Douglas Burton; Peter Passias; Munish Gupta; Themistocles Protopsaltis; Han Jo Kim; Justin S Smith; Robert Eastlack; Khaled Kebaish; Gregory M Mundis; Pierce Nunley; Christopher Shaffrey; Jeffrey Gum; Virginie Lafage; Frank Schwab Journal: J Spine Surg Date: 2021-03
Authors: Rushikesh S Joshi; Darryl Lau; Justin K Scheer; Miquel Serra-Burriel; Alba Vila-Casademunt; Shay Bess; Justin S Smith; Ferran Pellise; Christopher P Ames Journal: Spine Deform Date: 2021-05-18
Authors: Yoshihiro Katsuura; Renaud Lafage; Han Jo Kim; Justin S Smith; Breton Line; Christopher Shaffrey; Douglas C Burton; Christopher P Ames; Gregory M Mundis; Richard Hostin; Shay Bess; Eric O Klineberg; Peter G Passias; Virginie Lafage Journal: Global Spine J Date: 2021-01-29