Abstract
Background and Objective: Robotic distal pancreatectomy (DP) is an emerging attractive approach, but its role compared with laparoscopic or open surgery remains unclear. Benchmark values are novel and objective tools for such comparisons. The aim of this study was to identify benchmark cutoffs for many outcome parameters for DP with or without splenectomy beyond the learning curve. Methods: This study analyzed outcomes from international expert centers from patients undergoing robotic DP for malignant or benign lesions. After excluding the first 10 cases in each center to reduce the effect of the learning curve, consecutive patients were included from the start of robotic DP up to June 2020. Benchmark patients had no significant comorbidities. Benchmark cutoff values were derived from the 75th or the 25th percentile of the median values of all benchmark centers. Benchmark values were compared with a laparoscopic control group from 4 high-volume centers and published open DP landmark series. Results: Sixteen centers contributed 755 cases, whereof 345 benchmark patients (46%) were included the analysis. Benchmark cutoffs included: operation time ≤300 minutes, conversion rate ≤3%, clinically relevant postoperative pancreatic fistula ≤32%, 3 months major complication rate ≤26.7%, and lymph node retrieval ≥9. The comprehensive complication index at 3 months was ≤8.7 without deterioration thereafter. Compared with robotic DP, laparoscopy had significantly higher conversion rates (5×) and overall complications, while open DP was associated with more blood loss and longer hospital stay. Conclusion: This first benchmark study demonstrates that robotic DP provides superior postoperative outcomes compared with laparoscopic and open DP. Robotic DP may be expected to become the approach of choice in minimally invasive DP.
| Original language | English |
|---|---|
| Journal | Annals of Surgery |
| Volume | 278 |
| Issue number | 2 |
| Pages (from-to) | 253-259 |
| Number of pages | 7 |
| ISSN | 0003-4932 |
| DOIs | |
| Publication status | Published - 01.08.2023 |
Funding
This study is supported by the LGID (Liver and Gastrointestinal Disease) Foundation and the Yvonne Jacob Foundation.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Research Areas and Centers
- Research Area: Luebeck Integrated Oncology Network (LION)
- Centers: University Cancer Center Schleswig-Holstein (UCCSH)
- Academic Focus: Biomedical Engineering
DFG Research Classification Scheme
- 2.22-25 General and Visceral Surgery
- 2.22-14 Hematology, Oncology
- 2.22-32 Medical Physics, Biomedical Technology
- 4.41-01 Automation, Mechatronics, Control Systems, Intelligent Technical Systems, Robotics
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