Robotic pancreatoduodenectomy: trends in technique and training challenges

Catherine H. Davis, Miral S. Grandhi, Victor P. Gazivoda, Alissa Greenbaum, Timothy J. Kennedy, Russell C. Langan, H. Richard Alexander, Henry A. Pitt, David A. August

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Background: More complex cases are being performed robotically. This study aims to characterize trends in robotic pancreatoduodenectomy (RPD) over time and assess opportunities for advanced trainees. Methods: Using the ACS-NSQIP database from 2014 to 2019, PD cases were characterized by operative approach (open-OPN, laparoscopic-LAP, robotic-ROB). Proficiency and postoperative outcomes were described by approach over time. Results: 24,268 PDs were identified, with the ROB approach increasing from 2.8% to 7.5%. Unplanned conversion increased over time for LAP (27.7–39.0%, p = 0.003) but was unchanged for ROB cases (14.8–14.7%, p = 0.257). Morbidity increased for OPN PD (35.5–36.8%, p = 0.041) and decreased for ROB PD (38.7–30.3%, p = 0.010). Mean LOS was lower in ROB than LAP/OPN (9.5 vs. 10.9 vs. 10.9 days, p < 0.00001). Approximately, 100 AHPBA, SSO, and ASTS fellows are being trained each year in North America; however, only about 5 RPDs are available per trainee per year which is far below that recommended to achieve proficiency. Conclusion: Over a 6-year period, a significant increase was observed in the use of RPD without a concomitant increase in conversion rates. RPD was associated with decreased morbidity and length of stay. Despite this shift, the number of cases being performed is not adequate for all fellows to achieve proficiency before graduation.

Original languageEnglish (US)
Pages (from-to)266-273
Number of pages8
JournalSurgical Endoscopy
Issue number1
StatePublished - Jan 2023

All Science Journal Classification (ASJC) codes

  • Surgery


  • Minimally invasive surgery
  • Pancreas cancer
  • Pancreatoduodenectomy
  • Robotic surgery
  • Surgical education
  • Surgical training


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