[New approach of learning curve for robotic-assisted gynecologic oncology surgery].
Fiche publication
Date publication
mars 2015
Auteurs
Membres identifiés du Cancéropôle Est :
Pr MARCHAL Frédéric
Tous les auteurs :
Yaribakht S, Guillemin F, Harter V, Malartic C, Marchal F
Lien Pubmed
Résumé
OBJECTIVES: Define the phases composing the learning curve of total hysterectomy (TH) and radical hysterectomy with pelvic lymphadenectomy (RHPL) robot-assisted performed by a single surgeon with no prior experience in laparoscopic surgery. METHODS: We retrospectively analyzed 72 procedures (TH, n=34 and RHPL, n=38) conducted between 2002 and 2011. The surgeon console time (CT) was used to determine the learning curve of TH and RHPL using CUSUM analysis. Epidemiological data, perioperative and postoperative complications were compared from the different phases of the learning curve. RESULTS: CUSUM analysis of surgeon console time (CUSUMCT) identified two learning phases for the TH group (phase 1: initial learning, phase 2: surgical skill increase). For the RHPL group, three learning phases were identified (phase 1: initial learning, phase 2: extending surgical indications, phase 3: control of surgical skills). Perioperative and postoperative complication rates did not differ significantly between the learning phases. Surgeon CT decreased from the 9th case (P=0.01) for the TH group and from the 13th case (P=0.04) for the RHPL group. DISCUSSION: CUSUM analysis of the learning curve in robotic-assisted gynecologic oncology surgery identified two phases of learning curve for simple procedures such as total hysterectomy and three phases for more complex procedures as radical hysterectomy with pelvic lymphadenectomy.
Référence
Gynecol Obstet Fertil. 2015 Mar 23. pii: S1297-9589(15)00043-0