Multivariate Analysis and Machine Learning Model Risk Prediction of Recurrent Pain After PLIF Surgery for Degenerative Lumbar Spine Disease At Long-term Follow-up

Multivariate Analysis and Machine Learning Model Risk Prediction of Recurrent Pain After PLIF Surgery for Degenerative Lumbar Spine Disease At Long-term Follow-up

The study was a clinical retrospective study designed to investigate risk factors for long-term recurrent pain after PLIF in patients with lumbar degenerative disease and to improve patient outcomes

Inclusion Criteria:

1. confirmed diagnosis of lumbar degenerative disease (spinal stenosis, disc herniation with lumbar instability, and lumbar spondylolisthesis), with no significant symptomatic relief after conservative treatment for more than 3 months, and in need of surgical intervention;
2. lumbar spinal fusion surgical treatment with PLIF;
3. grouping based on the presence or absence of a lumbar or limb pain with VAS ≥3 at the 12-18 month postoperative follow-up;
4. observational indicators including individual factors, surgical factors, spine-pelvis sagittal balance parameters, and paravertebral muscle parameters.

Exclusion Criteria:

(1) those with a history of lumbar spine trauma, inflammation, tumor, or surgery; (2) those with congenital or acquired severe lumbar vertebral deformity; (3) those with severe neurological dysfunction; (4) those with incomplete baseline and follow-up data.