Abstract
Objective: Delayed gastric emptying (DGE) remains a major driver of prolonged length of stay and morbidity following the pancreatoduodenectomy. The objective of this study was to evaluate whether technical factors observed during video review of DGE during robotic pancreatoduodenectomy (RPD) could add to predictive models of DGE. Methods: Two blinded surgeons analyzed RPD videos with 90-day postoperative clinical data. DGE was classified according to ISGPS criteria. Clinical and technical variables were analyzed using multivariate analysis (MVA). Specific variables reviewed were: 1) type of anastomosis 2) angle of efferent limb 3) OSATS score of performing surgeon, 4) length of time to complete anastomosis, and 5) if performed by trainee. Results: Video was available for 172 RPD, 56% percent of all performed during time period. DGE was observed in 38 (21.1%): A=15 (40%), B=12 (32%), and C=11 (29%). Clinical variables (prior to inclusion of technical variables) that predicted DGE on MVA were age, duct size and non-pancreatic adenocarcinoma malignancies (p=0.0003; R2=0.112). As a group, trainees took longer to complete the anastomosis than attendings (p=0.029). On MVA, the best model of independent predictors of DGE included (p=0.0002; R2=0.1651): advanced age, small pancreatic duct, short [1st Interquartile Range] gastrotomy (<4.5 cm) length, stapled (compared to sutured) anastomosis, extreme efferent GJ angle from midline (>30°; middle figure best), and performance of anastomosis by trainee. Conclusion: Technical components of the gastrojejunostomy added to predictive models of DGE. This study establishes the framework for innovative prospective quality improvement projects targeting surgical micro-techniques available only through review of video databases.
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