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Accès ouvert déclaré 2026 article

Learning Curves and Complexity Evolution in Robotic Liver Surgery

2Citations signalées — pas une note de qualité
28Institutions déclarées
13Pays d’affiliation déclarés

Résumé fourni par la source

OBJECTIVE: To evaluate the institutional learning curve of robotic liver resection (RLR), its association with surgical complexity and outcomes in an international multicenter cohort. SUMMARY OF BACKGROUND DATA: RLR is increasingly adopted worldwide, but the dynamics of the learning process and its impact on surgical outcomes remain poorly defined. METHODS: This international, multicenter, retrospective cohort study included consecutive patients who underwent RLR between 06/2013 and 12/2024 across 22 expert centers. Based on the first 150 cases at each center, three phases were used to define the learning curve: operative time for competency, major complications for proficiency, and textbook outcome for mastery. Risk-adjusted generalized additive models were used to assess the learning process. Benchmark performance was compared to international reference values. RESULTS: Among 2,331 patients, the most common indications were hepatocellular carcinoma (36%), benign lesions (23%) and colorectal liver metastases (21%). Operative time decreased after achieving competency (case #62), from 240 to 220 minutes (P<0.001). Major morbidity reached a plateau during the proficiency phase (cases #63-138; 9% vs. 11%, P=0.144), while progression to mastery (cases #139-150) was associated with a higher rate of textbook outcome (76% vs. 87%, P=0.021). In contrast, conversion (5.1% vs. 4.9% vs. 2%), bile leak (4.0% vs. 5.3% vs. 3.8%), and 90-day mortality (0.7% vs. 0.9% vs. 0.9%) remained low and stable across all learning phases. Importantly, benchmark criteria for operative time, hospital stay, and textbook outcome were met across all complexity groups, including during the early learning phase. CONCLUSIONS: Robotic liver surgery shows progressive outcome improvement with early achievement of benchmark-level results and stable performance across increasing complexity. These findings indicate that, in experienced centers, RLR can be safely implemented and integrated into clinical practice, supporting its key role in modern hepatobiliary surgery.

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Contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Learning Curves and Complexity Evolution in Robotic Liver Surgery
Date Crossref
18/06/2026
Éditeur
Ovid Technologies (Wolters Kluwer Health)
Type
journal-article

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Institutions déclarées

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Sujets associés

Hepatocellular Carcinoma Treatment and PrognosisAdvanced Radiotherapy TechniquesCholangiocarcinoma and Gallbladder Cancer Studies

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