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<p>To examine the learning curve and perioperative outcomes of robotic-assisted distal pancreatectomy (RDP) conducted at a single center and to contextualize these findings against existing literature.&#xa0;A single expert surgical team conducted RDP on 106 patients at the Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Soochow University, from January 2021 to December 2024. To explore the learning pattern of operative duration, cumulative sum (CUSUM) analysis was utilized. Breakpoints in textbook outcomes (TBO) for RDP were subsequently identified through the application of a two-segment regression model. Perioperative indicators before and after the breakpoints were compared.&#xa0;The cohort showed a median operative time of 230&#xa0;min, with 74.53% (<i>n</i> = 79) achieving TBO. The cubic regression model (R² = 0.958) provided the best fit for the operative-time learning curve, revealing two discrete operative phases: a premier learning phase (cases 1 − 45) together with a succeeding proficiency phase (cases 46 − 106). The TBO breakpoint occurred at case 85, corresponding to the mastery phase. The proficiency phase yielded marked improvements over the learning phase, including shorter operative times (258&#xa0;min vs. 200&#xa0;min), lower intraoperative blood loss (100 mL vs. 75 mL), and a reduced rate of major complications (Clavien-Dindo grade ≥ III: 13.33% vs. 1.64%) (all <i>P</i> &lt; 0.05). These phase transitions were consistent with benchmark thresholds reported in previous studies.&#xa0;Operative efficiency in RDP improved significantly after 45 cases, suggesting that technical safety and feasibility can be achieved relatively early. However, the attainment of consistent clinical success, as defined by TBO, required approximately 85 cases. Future initiatives should prioritize shortening RDP’s learning curve, minimizing early complications, and systematically enhancing surgical quality to ensure safer adoption.</p>

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Learning curve and perioperative outcomes of robotic-assisted distal pancreatectomy: a single-center study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月27日

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  • Yizhang Zhu,
  • Jiayue Zou,
  • Daobin Wang,
  • Danyang Shen,
  • Xiaofeng Xue,
  • Weigang Zhang,
  • Lei Qin

摘要

To examine the learning curve and perioperative outcomes of robotic-assisted distal pancreatectomy (RDP) conducted at a single center and to contextualize these findings against existing literature. A single expert surgical team conducted RDP on 106 patients at the Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Soochow University, from January 2021 to December 2024. To explore the learning pattern of operative duration, cumulative sum (CUSUM) analysis was utilized. Breakpoints in textbook outcomes (TBO) for RDP were subsequently identified through the application of a two-segment regression model. Perioperative indicators before and after the breakpoints were compared. The cohort showed a median operative time of 230 min, with 74.53% (n = 79) achieving TBO. The cubic regression model (R² = 0.958) provided the best fit for the operative-time learning curve, revealing two discrete operative phases: a premier learning phase (cases 1 − 45) together with a succeeding proficiency phase (cases 46 − 106). The TBO breakpoint occurred at case 85, corresponding to the mastery phase. The proficiency phase yielded marked improvements over the learning phase, including shorter operative times (258 min vs. 200 min), lower intraoperative blood loss (100 mL vs. 75 mL), and a reduced rate of major complications (Clavien-Dindo grade ≥ III: 13.33% vs. 1.64%) (all P < 0.05). These phase transitions were consistent with benchmark thresholds reported in previous studies. Operative efficiency in RDP improved significantly after 45 cases, suggesting that technical safety and feasibility can be achieved relatively early. However, the attainment of consistent clinical success, as defined by TBO, required approximately 85 cases. Future initiatives should prioritize shortening RDP’s learning curve, minimizing early complications, and systematically enhancing surgical quality to ensure safer adoption.