Status:
COMPLETED
Development and Validation of Interpretable Machine Learning Models Incorporating Paraspinal Muscle Quality for to Predict Cage Subsidence Risk Followingposterior Lumbar Interbody Fusion
Lead Sponsor:
Hao Liu
Conditions:
Degenerative Lumbar Diseases
Cage
Eligibility:
All Genders
Brief Summary
The study focuses on identifying risk factors for cage subsidence after posterior lumbar interbody fusion (PLIF) and developing an interpretable machine learning model to predict these risks. It analy...
Eligibility Criteria
Inclusion
- confirmed lumbar disc herniation, spinal stenosis, or spondylolisthesis based on clinical and imaging findings;
- patients who failed conservative treatment for ≥3 months or experienced recurrence and underwent surgery for the first time;
- minimum 12-month follow-up.
Exclusion
- prior spinal surgery;
- spinal deformity or severe instability;
- lumbar tuberculosis, infection, tumor, or severe bone destruction;
- incomplete or lost follow-up.
Key Trial Info
Start Date :
March 1 2025
Trial Type :
OBSERVATIONAL
Allocation :
ACTUAL
End Date :
March 15 2025
Estimated Enrollment :
720 Patients enrolled
Trial Details
Trial ID
NCT06888739
Start Date
March 1 2025
End Date
March 15 2025
Last Update
March 21 2025
Active Locations (1)
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1
The First Affiliated Hospital of Soochow University Medical Record and Imaging System
Jiangsu, SuZhou, China, 215006