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Feasibility and learning curve for robotic surgery in a small hospital: A retrospective cohort study.
Shima, Takafumi; Arita, Asami; Sugimoto, Satoshi; Takayama, Shoichi; Yamamoto, Masashi; Lee, Sang-Woong; Okuda, Junji.
Afiliação
  • Shima T; Minimally Invasive and Robot Surgery Center, Toyonaka Keijinkai Hospital, Shoji, Toyonaka-shi, Osaka, Japan.
  • Arita A; Department of General and Gastroenterological Surgery, Osaka Medical and Pharmaceutical University, Daigaku-machi, Takatsuki-shi, Osaka, Japan.
  • Sugimoto S; Minimally Invasive and Robot Surgery Center, Toyonaka Keijinkai Hospital, Shoji, Toyonaka-shi, Osaka, Japan.
  • Takayama S; Minimally Invasive and Robot Surgery Center, Toyonaka Keijinkai Hospital, Shoji, Toyonaka-shi, Osaka, Japan.
  • Yamamoto M; Minimally Invasive and Robot Surgery Center, Toyonaka Keijinkai Hospital, Shoji, Toyonaka-shi, Osaka, Japan.
  • Lee SW; Minimally Invasive and Robot Surgery Center, Toyonaka Keijinkai Hospital, Shoji, Toyonaka-shi, Osaka, Japan.
  • Okuda J; Department of General and Gastroenterological Surgery, Osaka Medical and Pharmaceutical University, Daigaku-machi, Takatsuki-shi, Osaka, Japan.
Medicine (Baltimore) ; 102(23): e34010, 2023 Jun 09.
Article em En | MEDLINE | ID: mdl-37335658
ABSTRACT
Robotic surgery rates, typified by the use of the da Vinci Surgical System, have increased in recent years. However, robotic surgery is mostly performed in large hospitals and has not been fully implemented in small hospitals. Therefore, we aimed to verify the feasibility of robotic surgery in small hospitals and verify the number of cases in which perioperative preparation for robotic surgery is stable by creating a learning curve in small hospitals. Forty robot-assisted rectal cancer surgeries performed in large and small hospitals by a surgeon with extensive experience in robotic surgery were validated. Draping and docking times were recorded as perioperative preparation times. Unexpected surgical interruptions, intraoperative adverse events, conversion to laparoscopic or open surgery, and postoperative complications were recorded. Cumulative sum analysis was used to derive the learning curve for perioperative preparation time. Draping times were significantly longer in the small hospital group (7 vs 10 minutes, P = .0002), while docking times were not significantly different (12 vs 13 minutes, P = .098). Surgical interruptions, intraoperative adverse events, and conversions were not observed in either group. There were no significant differences in the incidence of severe complications (25% [5/20] vs 5% [1/20], P = .184). In the small hospital group, phase I of the draping learning curve was completed in 4 cases, while phase I of the docking learning curve was completed in 7 cases. Robotic surgery is feasible for small hospitals, and the preoperative preparation time required for robotic surgery stabilizes relatively early.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Observational_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Observational_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article