Abstract
BACKGROUND: Robotic platforms have increased in sophistication for pedicle screw placement. Here, we review our institutional experience using ExcelsiusGPS to assess the accuracy rate of pedicle screw placement throughout the spine and characterize predictors of placement inaccuracy. STUDY DESIGN: Retrospective cohort study. METHODS: Patients from 2017 to 2022 undergoing spinal fusion surgery with ExelsiusGPS-assisted screw implantation at a single tertiary center were retrospectively identified. Patient demographics, preoperative symptoms, and operative details were collected. Postoperative computed tomography was used to classify screw placement accuracy according to the Gertzbein and Robbins scale (GRS). A stepwise multivariable ordered logistic regression analysis determined independent risk factors for clinically inaccurate screws (GRS C/D/E). RESULTS: One hundred and seventeen patients were included. Mean age was 60.6 ± 13.2 years, with 57% men, 72% white, and mean body mass index of 29.9 ± 6.4 kg/m(2). Seven hundred and twenty-eight screws were placed, predominantly in the thoracic (29.5%) and lumbar (52.6%) regions. Accuracy classification indicated 670 GRS A, 31 GRS B, 22 GRS C, 4 GRS D, and 1 GRS E screws. The clinically acceptable screw placement rate (GRS A/B) was 96%. Male gender (odds ratio [OR]: 2.12, P = 0.03), revision surgery (OR: 2.43, P = 0.02), and thoracic level screw insertion (OR: 2.33, P = 0.01) were independently associated with inaccurate screw placement and explained 8.7% of the variability seen. Of the 728 screws placed, 3 required revision after postoperative imaging revealed loosening or pedicle breach. CONCLUSION: ExcelsiusGPS-assisted screw insertion has high placement accuracy and low revision rates. Identification of predictors of inaccuracy illustrates that similar variables, such as placement in the thoracic spine and revision surgery status, apply to both freehand and robotic screw placement. CLINICAL RELEVANCE: Robotic spine surgery is an accurate, reliable tool that can improve patient outcomes. Factors like male gender, thoracic screw placement, and revision surgery status are associated with lower screw placement accuracy, and these factors should inform surgical decision-making when using robotic assistance.