Related Experiment Video
Updated: Jun 19, 2026
Modified Posterior Vertebral Column Resection for Patients with Thoracolumbar Kyphotic Deformity
Published on: September 16, 2022
Machine learning-based identification of distinct risk factors for moderate versus severe proximal junctional
Dong-Ho Kang1, Jin-Sung Park1, Chong-Suh Lee2
1Department of Orthopedic Surgery, Spine Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, South Korea.
Background Context:
Proximal junctional kyphosis (PJK) is a well-recognized complication of adult spinal deformity surgery. However, traditional proximal junctional angle (PJA) thresholds (15°) and revision-predictive thresholds (28°) may represent distinct clinical entities with unique etiologies.
Purpose:
To analyze and compare predictive risk factors for moderate (PJA≥15°) and severe (PJA≥28°) PJK using machine learning.
Study Design/Setting:
Retrospective study.
Patient Sample:
A total of 374 patients who underwent adult spinal deformity surgery with a minimum 2-year follow-up.
Outcome Measures:
Development of moderate (PJA≥15°) and severe (PJA≥28°) PJK.
Methods:
Five machine learning algorithms (logistic regression, support vector machine, random forest, extreme gradient boosting, AutoGluon) were trained to predict moderate and severe PJK. Feature stability analysis identified robust predictors across models, and SHAP analysis elucidated the feature directionality.
Results:
The incidence of moderate and severe PJK was 17.4% (65 patients) and 11.0% (41 patients), respectively. Body mass index and L1 tilt were universally selected for moderate PJK. SHAP analysis showed that high relative lumbar lordosis (relative hyperlordosis) and L1 tilt were associated with increased predicted risk, whereas iliac screws were protective. The maldistributed lordosis distribution index and number of rods were consensus predictors of severe PJK. SHAP associated maldistributed lordosis distribution index, excessive postoperative lumbar lordosis, and high cement volume with an increased predicted risk of severe PJK.
Conclusions:
Moderate PJK appears to be driven by geometric stress concentration (eg, L1 tilt and relative hyperlordosis), whereas severe PJK stems from structural/distributional mismatch (eg, lordosis maldistribution and construct rigidity). Prevention strategies should be stratified according to these distinct mechanisms.
