Utilizing a comprehensive machine learning approach to identify patients at high risk for extended length of stay following spinal deformity surgery in pediatric patients with early onset scoliosis

i) Factors influencing LOS were operative time, age, BMI, ASA class, levels operated on, etiology, nutritional support, pulmonary and neurologic comorbidities
ii) The gradient boosting model performed best. Test accuracy = 0.723, area under curve (AUC) = 0.630, Brier score = 0.189, leading to a patient-specific risk calculator for prolonged LOS.

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