Evaluation of a Pediatric Surgical Risk Calculator for Postoperative Outcomes in Spinal Deformity

Study DesignRetrospective Cohort Study.ObjectivesTo evaluate the accuracy of the ACS-NSQIP Pediatric Surgical Risk Calculator in predicting postoperative complications and mortality following pediatric spinal deformity surgery. Predicted risks were compared with observed outcomes from the ACS-NSQIP Pediatric database, stratified by scoliosis etiology, fusion level, and surgical approach.MethodsWe performed a retrospective analysis of pediatric patients who underwent spinal deformity correction between 2012 and 2023 using the ACS-NSQIP Pediatric database. Patients were categorized as idiopathic or neuromuscular scoliosis. Predicted risks were compared with observed 30-day outcomes including mortality, surgical site infection, pneumonia, and urinary tract infection. Predictive performance was assessed using the Brier score across discrimination and calibration dimensions.ResultsA total of 58,010 patients were included (45,211 idiopathic; 12,799 neuromuscular). Overall, the calculator predicted a 2.74% complication rate vs an observed rate of 9.54% (Brier: 0.00462; 5.35% of maximum), reflecting poor discrimination and substantially underestimated absolute risk. The most frequent complications were surgical site infection (2.12%), pneumonia (0.99%), and urinary tract infection (0.64%), each demonstrating adequate individual-level discrimination and calibration. Stratified analyses showed adequate performance for idiopathic scoliosis patients undergoing 0-12 level fusions, while discrimination was poor for ≥13 level fusions. Performance was substantially worse among neuromuscular scoliosis patients across all fusion levels. Surgical approach did not meaningfully affect performance.ConclusionsThe calculator reliably predicts select individual complications but underestimates overall risk in high-complexity cases, particularly extensive fusions and neuromuscular scoliosis. Incorporating deformity-specific and surgical complexity variables may improve preoperative risk stratification and counseling.