Learning Curve in Robot-Assisted Laparoscopic Liver Resection.
Hepatectomy
Laparoscopic
Learning curve
Robot
Journal
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
ISSN: 1873-4626
Titre abrégé: J Gastrointest Surg
Pays: United States
ID NLM: 9706084
Informations de publication
Date de publication:
09 2019
09 2019
Historique:
received:
20
11
2017
accepted:
08
01
2018
pubmed:
9
11
2018
medline:
21
7
2020
entrez:
9
11
2018
Statut:
ppublish
Résumé
The objective of this study was to evaluate the learning curve effect on the safety and feasibility of robot-assisted liver resection (RALR). In 140 consecutive cases, all data about demographic, surgical procedure, postoperative course were collected prospectively and analyzed. Risk-adjusted cumulative sum model was used for determining the learning curve based on the need for conversion. Among all 140 patients, no patients suffered from any organ dysfunction postoperatively and the operative mortality was 0%. The CUSUM analysis showed that at the 30th consecutive patient, the open conversion rate reached to the average value, and it further improved thereafter. In the last 70 patients, only 3 patients (4.3%) required conversion and 7 patients (10%) needed blood transfusion. Only 1 patient (1.3%) out of 79 patients with HCC had a positive resection margin. Univariate analyses showed the following risk factors associated with significantly higher risks of conversion (P < 0.05): tumor number > 1, lesions in segments 1/4a/7/8, right posterior sectionectomy, and lesions which were beyond the indications of the Louisville statement. Multivariate logistic analysis revealed that both tumor number > 1 (OR: 2.10, P < 0.05) and right posterior sectionectomy (OR: 11.19, P < 0.01) were risk factors of conversion. The robotic approach for hepatectomy is safe and feasible. A learning curve effect was demonstrated in this study after the 30th consecutive patient. The long-term oncological outcomes of robotic hepatectomy still need further investigation.
Sections du résumé
BACKGROUND
The objective of this study was to evaluate the learning curve effect on the safety and feasibility of robot-assisted liver resection (RALR).
METHODS
In 140 consecutive cases, all data about demographic, surgical procedure, postoperative course were collected prospectively and analyzed. Risk-adjusted cumulative sum model was used for determining the learning curve based on the need for conversion.
RESULTS
Among all 140 patients, no patients suffered from any organ dysfunction postoperatively and the operative mortality was 0%. The CUSUM analysis showed that at the 30th consecutive patient, the open conversion rate reached to the average value, and it further improved thereafter. In the last 70 patients, only 3 patients (4.3%) required conversion and 7 patients (10%) needed blood transfusion. Only 1 patient (1.3%) out of 79 patients with HCC had a positive resection margin. Univariate analyses showed the following risk factors associated with significantly higher risks of conversion (P < 0.05): tumor number > 1, lesions in segments 1/4a/7/8, right posterior sectionectomy, and lesions which were beyond the indications of the Louisville statement. Multivariate logistic analysis revealed that both tumor number > 1 (OR: 2.10, P < 0.05) and right posterior sectionectomy (OR: 11.19, P < 0.01) were risk factors of conversion.
CONCLUSIONS
The robotic approach for hepatectomy is safe and feasible. A learning curve effect was demonstrated in this study after the 30th consecutive patient. The long-term oncological outcomes of robotic hepatectomy still need further investigation.
Identifiants
pubmed: 30406576
doi: 10.1007/s11605-018-3689-x
pii: 10.1007/s11605-018-3689-x
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
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