Evidence map›Paper›PMID 38351030›Full record

ArticleScientific reports2024

Concomitant training in robotic and laparoscopic liver resections of low-to-intermediate difficulty score: a retrospective analysis of the learning curve.

Lorenzo Bernardi, Emanuele Balzano, Raffaello Roesel, Davide Ghinolfi, Filippo Vagelli, Giacomo Menconi, Antonietta Petrusic, Francesco Mongelli, Pietro Majno-Hurst, Paolo De Simone and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. Observational
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  12. Application of Robotic Surgery in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Lorenzo Bernardi *Department of Surgery, Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland.
Emanuele Balzano *Hepato-Biliary Surgery and Liver Transplant Division, Azienda Ospedaliera Universitaria Pisana (AOUP), University of Pisa, Via Paradisa, 2, 56124, Pisa, Italy. e.balzano@ao-pisa.toscana.it.
Raffaello RoeselDepartment of Surgery, Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland.
Davide GhinolfiHepato-Biliary Surgery and Liver Transplant Division, Azienda Ospedaliera Universitaria Pisana (AOUP), University of Pisa, Via Paradisa, 2, 56124, Pisa, Italy.
Filippo VagelliHepato-Biliary Surgery and Liver Transplant Division, Azienda Ospedaliera Universitaria Pisana (AOUP), University of Pisa, Via Paradisa, 2, 56124, Pisa, Italy.
Giacomo MenconiHepato-Biliary Surgery and Liver Transplant Division, Azienda Ospedaliera Universitaria Pisana (AOUP), University of Pisa, Via Paradisa, 2, 56124, Pisa, Italy.
Antonietta PetrusicDepartment of Surgery, Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland.
Francesco MongelliDepartment of Surgery, Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland.
Pietro Majno-HurstDepartment of Surgery, Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland.
Paolo De SimoneHepato-Biliary Surgery and Liver Transplant Division, Azienda Ospedaliera Universitaria Pisana (AOUP), University of Pisa, Via Paradisa, 2, 56124, Pisa, Italy.
Alessandra CristaudiDepartment of Surgery, Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the setting of minimally invasive liver surgery (MILS), training in robotic liver resections (RLR) usually follows previous experience in laparoscopic liver resections (LLR). The aim of our study was to assess the learning curve of RLR in case of concomitant training with LLR. We analyzed consecutive RLRs and LLRs by a surgeon trained simultaneously in both techniques (Surg1); while a second surgeon trained only in LLRs was used as control (Surg2). A regression model was used to adjust for confounders and a Cumulative Sum (CUSUM) analysis was carried out to assess the learning phases according to operative time and difficulty of the procedures (IWATE score). Two-hundred-forty-five procedures were identified (RobSurg1, n = 75, LapSurg1, n = 102, LapSurg2, n = 68). Mean IWATE was 4.0, 4.3 and 5.8 (p < 0.001) in each group. The CUSUM analysis of the adjusted operative times estimated the learning phase in 40 cases (RobSurg1), 40 cases (LapSurg1), 48 cases (LapSurg2); for IWATE score it was 38 cases (RobSurg1), 33 cases (LapSurg1), 38 cases (LapSurg2) respectively. Our preliminary experience showed a similar learning curve of 40 cases for low and intermediate difficulty RLR and LLR. Concomitant training in both techniques was safe and may be a practical option for starting a MILS program.

Indexed as

LaparoscopyRobotic Surgical ProceduresHepatectomyHumansLearning CurveLiverOperative TimeRetrospective Studies

Identifiers

PMID38351030
PMCPMC10864263

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.