Predicting postoperative outcomes in lumbar spinal fusion: Development of a machine learning model

i) Retrospective cross-sectional study
ii) Aim: to develop a machine-learning algorithm to predict surgical outcomes in patients with degenerative lumbar spondylolisthesis (DLS) undergoing spinal fusion surgery, only using preoperative data.
iii) XGBoost model demonstrated the best performance in the validation set, AUC = 0.81 (95% CI 0.67-0.95).
iv) Composition of the erector spinae and severity of lumbar spinal stenosis identified as the most important features.

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