Learning curves of surgeon performance and team workflow during the first 100 hugo robotic-assisted small bowel length shortening with sleeve gastrectomy procedures.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος:	Learning curves of surgeon performance and team workflow during the first 100 hugo robotic-assisted small bowel length shortening with sleeve gastrectomy procedures.
Συγγραφείς:	Huang CK; College of Medicine, China Medical University, Taichung City, Taiwan.; Division of Metabolic & Bariatric Surgery, Department of Surgery, Medical University Hospital, Taichung City, Taiwan.; Body Science and Metabolic Disorders International Medical Center, Medical University Hospital, Taichung City, Taiwan., Lai LW; Body Science and Metabolic Disorders International Medical Center, Medical University Hospital, Taichung City, Taiwan., Hsin MC; Division of Metabolic & Bariatric Surgery, Department of Surgery, Medical University Hospital, Taichung City, Taiwan.; Body Science and Metabolic Disorders International Medical Center, Medical University Hospital, Taichung City, Taiwan., Huang SC; Department of Medicine, Chung Shan Medical University, Taichung City, Taiwan., Chang PC; Weight Management Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung City, Taiwan.; Division of Thoracic Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, No. 100, Tzyou 1st Road, Kaohsiung City, 80756, Taiwan., Jeng LB; College of Medicine, China Medical University, Taichung City, Taiwan.; Organ Transplantation Center, China Medical University Hospital, Taichung, 404, Taiwan.; Department of Surgery, China Medical University Hospital, Taichung, 404, Taiwan.; Cell Therapy Center, China Medical University Hospital, Taichung, 404, Taiwan., Chang TW; Weight Management Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung City, Taiwan. drchangtingwei@gmail.com.; Division of Thoracic Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, No. 100, Tzyou 1st Road, Kaohsiung City, 80756, Taiwan. drchangtingwei@gmail.com.
Πηγή:	Journal of robotic surgery [J Robot Surg] 2026 Oct 03; Vol. 20 (1). Date of Electronic Publication: 2026 Oct 03.
Τύπος έκδοσης:	Journal Article
Γλώσσα:	English
Στοιχεία περιοδικού:	Publisher: Springer Country of Publication: England NLM ID: 101300401 Publication Model: Electronic Cited Medium: Internet ISSN: 1863-2491 (Electronic) Linking ISSN: 18632483 NLM ISO Abbreviation: J Robot Surg Subsets: MEDLINE
Imprint Name(s):	Original Publication: London : Springer
Ιατρικοί όροι (MeSH):	Gastrectomy/methods , Gastrectomy/education , Robotic Surgical Procedures/methods , Robotic Surgical Procedures/education , Bariatric Surgery/methods , Bariatric Surgery/education , Intestine, Small/surgery , Surgeons/education , Learning Curve* , Workflow*, Humans ; Retrospective Studies ; Female ; Male ; Middle Aged ; Adult ; Operative Time
Περίληψη:	Evidence on Hugo RAS in bariatric surgery remains limited. We evaluated the first 100 Hugo RAS small bowel length shortening with sleeve gastrectomy (BOS-SG) procedures to determine whether surgeon-level technical performance (console time) and team-level workflow (docking time) evolved differently during implementation. This retrospective single-center cohort included consecutive cases performed between February 11 and July 30, 2025. Change points were assessed using segmented linear regression, Davies tests, 95% confidence intervals, and descriptive cumulative sum (CUSUM) analysis. Early and late phases were defined by the rounded docking-time breakpoint, the most stable interpretable workflow transition. Among 100 cases, median console time was 16.0 min (interquartile range [IQR], 15.0-21.2) and docking time was 5.0 min (IQR, 3.0-5.2). CUSUM peaks occurred at cases 24 and 28, respectively. Segmented regression identified a docking-time breakpoint at case 33.1 (95% CI, 26.2-40.0; Davies p < 0.001); the console-time segmented solution was early and was not retained. From early to late phase, console time decreased from 23.0 to 16.0 min (p < 0.001), docking time from 6.0 to 4.0 min descriptively, and total operative time from 95.0 to 77.0 min (p < 0.001). Complications occurred in 1/33 and 7/67 cases (p = 0.265). Hugo RAS BOS-SG implementation showed distinct, complementary learning trajectories. Docking time, a team-workflow metric, demonstrated the most stable transition around 30-40 cases, whereas console performance improved without a stable mid-series breakpoint. Console and docking time should be treated as noninterchangeable endpoints for platform adoption. (© 2026. The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.)
Competing Interests:	Declarations. Competing interests: The authors declare no competing interests. Ethics approval: This retrospective observational study was approved by the Institutional Review Board of China Medical University Hospital (approval no. CMUH115-REC2-157) and was conducted in accordance with the Declaration of Helsinki and applicable institutional requirements. Consent for publication: Written informed consent for publication of the clinical image shown in Fig. 1A was obtained from the participant. Consent to participate: Informed consent was obtained from all individual participants included in the study. Statement of human and animal rights: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Use of generative artificial intelligence: During preparation of this manuscript, OpenAI Codex and ChatGPT were used to assist with language drafting, formatting, and internal consistency checks. All analyses, interpretation, references, and manuscript content were reviewed and verified by the authors, who take full responsibility for the final work.
References:	Surg Endosc. 2021 May;35(5):1970-1975. (PMID: 33398577) Int J Colorectal Dis. 2026 Mar 10;41(1):. (PMID: 41807800) Obes Surg. 2023 Jul;33(7):2083-2089. (PMID: 37147465) Surg Endosc. 2022 May;36(5):3234-3245. (PMID: 34845550) Surg Endosc. 2026 Jan;40(1):384-390. (PMID: 41116056) Bariatr Surg Pract Patient Care. 2019 Sep 1;14(3):95-101. (PMID: 31572625) Surg Laparosc Endosc Percutan Tech. 2024 Dec 01;34(6):630-637. (PMID: 39445437) Int J Colorectal Dis. 2024 Sep 18;39(1):144. (PMID: 39289218) Front Surg. 2023 Oct 02;10:1278696. (PMID: 37850042) J Robot Surg. 2026 Feb 23;20(1):. (PMID: 41724894) J Robot Surg. 2025 Oct 12;19(1):682. (PMID: 41076601) Updates Surg. 2025 Nov;77(7):2037-2050. (PMID: 39617824) Obes Surg. 2023 Jan;33(1):3-14. (PMID: 36336720) J Robot Surg. 2026 Jul 27;20(1):. (PMID: 42503579) J Laparoendosc Adv Surg Tech A. 2024 Jan;34(1):77-81. (PMID: 38100311) Obes Surg. 2022 Sep;32(9):2994-3004. (PMID: 35773552) Minim Invasive Surg. 2012;2012:347131. (PMID: 23029610) J Robot Surg. 2025 Jun 14;19(1):289. (PMID: 40515857) J Robot Surg. 2024 Aug 6;18(1):303. (PMID: 39105863) Obes Surg. 2018 Nov;28(11):3466-3473. (PMID: 30069859) J Laparoendosc Adv Surg Tech A. 2026 Oct;36(10):751-757. (PMID: 41947695) Obes Surg. 2026 Jun;36(6):2925-2930. (PMID: 42029998) J Robot Surg. 2023 Dec;17(6):2881-2888. (PMID: 37816994) J Robot Surg. 2024 Sep 26;18(1):349. (PMID: 39325249) Obes Surg. 2012 Jul;22(7):1097-103. (PMID: 22527596) J Robot Surg. 2025 Dec 22;20(1):108. (PMID: 41427995)
Contributed Indexing:	Keywords: BOS-SG; Console and docking time; Hugo RAS; Learning curve; Robotic bariatric surgery; Sleeve gastrectomy
Entry Date(s):	Date Created: 20261003 Date Completed: 20261003 Latest Revision: 20261008
Update Code:	20261008
DOI:	10.1007/s11701-026-04011-2
PMID:	42828618
Βάση Δεδομένων:	MEDLINE

Περιγραφή
ISSN:	1863-2491
DOI:	10.1007/s11701-026-04011-2