Decision Tree-based Modelling for Identification of Predictors of Blood Loss and Transfusion Requirement After Adult Spinal Deformity Surgery

Multilevel fusions and complex osteotomies to restore global alignment in adult spinal deformity (ASD) surgery can lead to increased operative time and blood loss. In this regard, we assessed factors predictive of perioperative blood product transfusion in patients undergoing long posterior spinal fusion for ASD. A single-institution retrospective review was conducted on 909 patients with ASD, age > 18 years, who underwent surgery for ASD with greater than 4 levels fused. Using conditional inference tree analysis, a machine learning methodology, we sought to predict the combination of variables that best predicted increased risk for intraoperative percent blood volume lost and perioperative blood product transfusion. Among the 909 patients included in the study, 377 (41.5%) received red blood cell (RBC) transfusion. The conditional inference tree analysis identified greater than 13 levels fused, American Society of Anesthesiologists (ASA) score > 1, a history of hypertension, 3-column osteotomy, pelvic fixation, and operative time > 8 hours, as significant risk factors for perioperative RBC transfusion. The best predictors for the subgroup with the highest risk for intraoperative percent blood volume lost (subgroup mean: 53.1% ± 42.9%) were greater than 13 levels fused, ASA score > 1, preoperative hemoglobin