Utilization Patterns, Outcomes & Complications of 300 Consecutive Robotic-Assisted Spinal Procedures and 1454 screws by a Single Surgeon
DOI:
https://doi.org/10.17161/kjm.vol17.22662Abstract
Introduction. Literature related to robotic spine procedures report relatively high accuracy with low robot-abandonment, however, several are multi-center, multi-surgeon series with high variability or report on previous generation robot systems. This study reviewed all single-surgeon consecutive robot-assisted cases using a single robotic-platform and report utilization patterns, outcomes, and robot-related complications.
Methods. A review of robotic spine surgeries performed by a single surgeon at an institution was performed. All cases utilized the same robotic-navigation system.
Results. Between August 2019 and July 2023, 300 consecutive robotic cases were identified. 53.3% were female with mean age 65.3yrs (range 20-92) and BMI 29.5 (19-47). Spinal pathologies included: Degenerative (88.7%), Deformity (16.3%), Trauma (10.0%), Neoplastic (5.7%), and Spondylodiskitis (1.7%). Cases were performed Open (10.3%), Minimally Invasive (MIS; 85.3%) and Hybrid (Open and MIS; 4.3%). Imaging sources included: Pre-Operative CT-merge (84.9%) and Intra-Operative 3D scan (15.1%). Patient tracker placement was: Posterior Superior Iliac Spine (81.6%) and spinous process (18.4%). Spine regions and screws placed included (% cases; # screws): Cervical (0.3%; 2), Thoracic (13.7%; 137), Lumbar/Sacral (96.3%; 1,231), Pelvic (12.7%; 78). There were 1,448 total screws placed. Mean total robot time was 38.75min (range 13-97; n = 228 cases). Six screws (0.4%) in six cases were malpositioned and removed intraoperatively. There was 0% robot abandonment, 0 returns to Operating Room and 0 neurologic deficits.
Conclusions. This report demonstrates that modern robotic platforms can be used across all spinal regions, using various imaging sources, with high accuracy and low complication rates.
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Copyright (c) 2024 Peter Klug, B.S., Andrew Diederich, M.D., Damon Mar, Ph.D., Brandon Carlson, M.D., MPH
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All articles in the Kansas Journal of Medicine are licensed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND 4.0).