Machine learning approach to predict venous thromboembolism among patients undergoing multi-level spinal posterior instrumented fusion

Background: The absence of consensus for prophylaxis of venous thromboembolism (VTE) in spine surgery underscores the importance of identifying patients at risk. This study incorporated machine learning (ML) models to assess key risk factors of VTE in patients who underwent posterior spinal instrumented fusion.