Philip Zeuschner1, Irmengard Meyer1, Stefan Siemer1, Michael Stoeckle1, Gudrun Wagenpfeil2, Stefan Wagenpfeil2, Matthias Saar1, Martin Janssen3,4. 1. Department of Urology and Pediatric Urology, Saarland University, Homburg/Saar, Germany. 2. Department of Medical Biometry, Epidemiology and Medical Informatics, Saarland University, Homburg/Saar, Germany. 3. Department of Urology and Pediatric Urology, Saarland University, Homburg/Saar, Germany. martin.janssen@ukmuenster.de. 4. Department of Urology and Pediatric Urology, University Hospital of Munster, Münster, Germany. martin.janssen@ukmuenster.de.
Abstract
BACKGROUND: Robot-assisted partial nephrectomy (RAPN) has become widely accepted, but its different underlying types of learning curves have not been comparatively analyzed to date. This study aimed to determine and compare the impact that the learning curve of the department, the console surgeon, and the bedside assistant as well as patient-related factors has on the perioperative outcomes of RAPN. METHODS: The study retrospectively analyzed 500 consecutive transperitoneal RAPNs (2007-2018) performed in a tertiary referral center by 7 surgeons and 37 bedside assistants. Patient characteristics and surgical data were obtained. Experience (EXP) was defined as the current number of RAPNs performed by the department, the surgeon, and the assistant. As the primary outcome, the impact of EXP and patient-related factors on perioperative outcomes were analyzed and compared. As the secondary outcome, a cutoff between "experienced" and "inexperienced" was defined. Correlation and regression analysis, receiver operating characteristic curve analysis, Fisher's exact test, and the Mann-Whitney U test were performed, with p values lower than 0.05 denoting significance. RESULTS: The EXP of the department, the surgeon, and the assistant each has a major influence on perioperative outcome in RAPN irrespective of patient-related factors. Perioperative outcomes improve significantly with EXP greater than 100 for the department, EXP greater than 35 for the surgeon, and EXP greater than 15 for the assistant. CONCLUSIONS: The perioperative results of RAPN are influenced by three different types of learning curves including those for the surgical department, the console surgeon, and the assistant. The influence of the bedside assistant clearly has been underestimated to date because it has a significant impact on the perioperative outcomes of RAPN.
BACKGROUND: Robot-assisted partial nephrectomy (RAPN) has become widely accepted, but its different underlying types of learning curves have not been comparatively analyzed to date. This study aimed to determine and compare the impact that the learning curve of the department, the console surgeon, and the bedside assistant as well as patient-related factors has on the perioperative outcomes of RAPN. METHODS: The study retrospectively analyzed 500 consecutive transperitoneal RAPNs (2007-2018) performed in a tertiary referral center by 7 surgeons and 37 bedside assistants. Patient characteristics and surgical data were obtained. Experience (EXP) was defined as the current number of RAPNs performed by the department, the surgeon, and the assistant. As the primary outcome, the impact of EXP and patient-related factors on perioperative outcomes were analyzed and compared. As the secondary outcome, a cutoff between "experienced" and "inexperienced" was defined. Correlation and regression analysis, receiver operating characteristic curve analysis, Fisher's exact test, and the Mann-Whitney U test were performed, with p values lower than 0.05 denoting significance. RESULTS: The EXP of the department, the surgeon, and the assistant each has a major influence on perioperative outcome in RAPN irrespective of patient-related factors. Perioperative outcomes improve significantly with EXP greater than 100 for the department, EXP greater than 35 for the surgeon, and EXP greater than 15 for the assistant. CONCLUSIONS: The perioperative results of RAPN are influenced by three different types of learning curves including those for the surgical department, the console surgeon, and the assistant. The influence of the bedside assistant clearly has been underestimated to date because it has a significant impact on the perioperative outcomes of RAPN.
Authors: Giovanni E Cacciamani; Tania Gill; Luis Medina; Akbar Ashrafi; Matthew Winter; Renè Sotelo; Walter Artibani; Inderbir S Gill Journal: J Urol Date: 2018-05-03 Impact factor: 7.450
Authors: Emmanuel Mitsinikos; George A Abdelsayed; Zoe Bider; Patrick S Kilday; Peter A Elliott; Pooya Banapour; Gary W Chien Journal: J Endourol Date: 2016-12-07 Impact factor: 2.942
Authors: Philip Zeuschner; Philippe Becker; Julia Heinzelbecker; Johannes Linxweiler; Stefan Siemer; Michael Stöckle; Matthias Saar Journal: Urologe A Date: 2022-01-17 Impact factor: 0.639