Evidence map›Paper›PMID 42133219›Full record

ArticleObesity surgery2026

Laparoscopic Roux-en-Y Gastric Bypass with the Maestro™ System: a Novel Collaborative Robotic Platform.

Dan Azagury, Fabrice Leclerc, Elisa Reitano, Marius Nedelcu, Henry Mercoli

Abstract read
In one paragraph

Article in Obesity surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Dan AzaguryStanford University School of Medicine, Stanford University, Stanford, USA.
Fabrice LeclercDigestive Surgery, Polyclinique de Franche Comté, Besançon, France.
Elisa ReitanoIHU mix Surg, Hôpitaux Universitaires de Strasbourg, Strasbourg, France.
Marius NedelcuELSAN, Hopital privé Bouchard, Marseille, France.
Henry MercoliDigestive Surgery, Polyclinique de Franche Comté, Besançon, France. docteur.mercoli@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLaparoscopic Roux-en-Y gastric bypass (LRYGB) is a cornerstone of bariatric surgery, yet its complexity poses challenges in visualization and retraction, often compounded by variability in surgical assistance. The Maestro™ is an Artificial Intelligence (AI)-powered surgical platform designed to elevate minimally invasive surgical performance and technique while keeping the surgeon at the patient's bedside during the procedure.

objectiveThis study aims to assess the effects of this innovative platform by comparing it with traditional L-RYGB.

methodsThis retrospective, matched cohort study included patients who underwent Maestro™ (MA-RYGB) and traditional laparoscopic Roux-en-Y gastric bypass (L-RYGB) at a single institution. The 54 Maestro™-assisted RYGB procedures were included prospectively. Each case was retrospectively matched in a 1:1 ratio with a baseline laparoscopic RYGB performed by the same surgical team. Operative time, in-room time, and related variables were recorded for both groups. Statistical Process Control (SPC) charts were generated to evaluate the process stability and variability for operative times.

resultsThe Maestro™ demonstrated a 19.3% reduction in operative time: MA-RYGB 62.9 min vs.75.1 min (p < 0.001). Operative times appeared more stable across consecutive cases in the Maestro cohort compared with conventional laparoscopy. Postoperative outcomes were comparable. No device-related complications or conversions occurred.

conclusionMaestro™ reduces procedure duration and was associated with a more stable operative course, without compromising safety. The use of the Maestro™ and may help standardize outcomes and operating room performance. This initial work suggests important implications for operative quality and efficiency with this promising new technology.

Indexed as

Artificial IntelligenceGastric BypassIntelligent SystemsLaparoscopyObesity, MorbidRobotic Surgical ProceduresAdultFemaleHumansMaleMiddle AgedOperative TimeRetrospective StudiesTreatment OutcomeArtificial intelligenceGastric bypassMaestro assistanceRobotic surgery

Identifiers

PMID42133219
PMCPMC13249781

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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.