Evidence map›Paper›PMID 41152527›Full record

ArticleSurgical endoscopy2026

International expert consensus-driven surgical process model for robot-assisted hysterectomy: Delphi study results.

Krystel Nyangoh Timoh, Soline Galuret, Thomas Hébert, Henri Azaïs, Marc Barahona, Sven Becker, Pierre Adrien Bolze, Thomas Boisramé, Bruno Borghese, Marie Carbonnel and 29 more

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Article in Surgical endoscopy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
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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

39 authors.

Krystel Nyangoh TimohDepartment of Obstetrics and Gynecology, Rennes University Hospital, INSERM U1099, Laboratoire Traitement du Signal Et de L'Image (LTSI), Service de Gynécologie Et Obstétrique, CHU de Rennes, Rennes University, INSERM, LTSI-UMR 1099, 16 Boulevard de Bulgarie, 35000, Rennes, France. Krystel.NYANGOH.TIMOH@chu-rennes.fr.ORCID 0000-0003-4751-9080
Soline GaluretINSERM, Rennes University, LTSI-UMR 1099, Rennes, France.
Thomas HébertUniversity Hospital of Tours, Tours, France.
Henri AzaïsDepartment of Gynecological Oncological and Breast Surgery, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Européen Georges-Pompidou, Paris, France.
Marc BarahonaDepartment of Gynecology, Bellvitge University Hospital, University of Barcelona (UB), IDIBELL, Barcelona, Spain.
Sven BeckerDepartment of Gynecology and Obstetrics, University Hospital of Frankfurt, Frankfurt, Germany.
Pierre Adrien BolzeDepartment of Gynecological Surgery and Oncology-Obstetrics, Pierre Bénite, Université Lyon 1, CICLY EA3738, Hospices Civils de Lyon, University Hospital Lyon Sud, Lyon, France.
Thomas BoisraméDepartment of Obstetrics and Gynecology, Strasbourg University Hospital, Strasbourg, France.
Bruno BorgheseDepartment of Obstetrics and Gynecology II and Reproductive Medicine, Cochin Hospital, AP-HP, Paris Cité University, Paris, France.
Marie CarbonnelDepartment of Gynecology and Obstetrics, Foch Hospital, University of Versailles Saint Quentin en Yvelines-Paris Saclay, Suresnes, France.
Vito CelaAzienda Ospedalero Universitaria Pisana, Pisa, Italy.
Céline ChauleurINSERM, Department of Gynecology and Obstetrics, North Hospital, Saint-Etienne University, Saint Priest en Jarez, U1059, Saint-Étienne, France.
Tony ChalhoubSt George's University Hospital NHS Foundation Trust, London, UK.
Tak Hong CheungDepartement of Obstetrics and Gynecology, Prince of Wales Hospital, the Chinese University of Hong Kong, Hong Kong, China.
François ClosonDepartment of Obstetrics and Gynecology, University of Liège, Hôpital de La Citadelle, Liège, Belgium.
Patrice CrochetINSERM NORDIC UMR 1239 Team Adrenal and Gonadal Physiopathology (AGoPath), Department of Obstetrics and Gynecology, Charles Nicolle Hospital, University of Rouen, Rouen, France.
Yohann DabiDepartment of Gynecology, Obstetrics and Reproductive Medicine, Sorbonne University - Tenon Hospital, Assistance Publique des Hôpitaux de Paris (AP-HP), Paris, France.
Laurent De LandsheereDepartment of Obstetrics and Gynecology, University of Liège, Hôpital de La Citadelle, Liège, Belgium.
Emilie FallerInstitut de Santé Pelvienne Des Deux Rives, Maison Médicale Des Deux Rives, Clinique Rhena, Strasbourg, France.
Francesco FanfaniUniversità Cattolica del Sacro Cuore, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italy.
Tristan GauthierDepartment of Gynecology, University Hospital of Limoges, Mother and Child Hospital, Limoges, France.
Walter GotliebDivision of Gynecologic Oncology, McGill University - Jewish General Hospital, Montreal, Canada.
Manuel Maria IanieriUnit of Gynecology and Obstetrics, Policlinico Abano Terme, Abano Terme, Italy.
Thomas IndDepartment of Gynecological Oncology, Royal United Hospitals, Bath, UK.
Tae Joong KimDepartment of Obstetrics and Gynecology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Martin KoskasDepartment of Obstetrics and Gynecology, Hospital Bichat, Paris Cité University, Paris, France.
Joseph NgDepartment of Obstetrics and Gynecology, National University Hospital of Singapore, Singapore, Singapore.
Benjamin MerlotIFEMEndo, Clinique Tivoli-Ducos, Bordeaux, France.
Jiheum PaekDepartment of Obstetrics and Gynecology, Ajou University School of Medicine, Suwon, Republic of Korea.
Charles-André PhilipDepartment of Obstetrics and Gynecological Surgery, Femme Mère Enfant University Hospital, Hospices Civils de Lyon, University of Lyon, Lyon, France.
Diego RaimondoIRCCS Azienda Ospedaliero-Universitaria Di Bologna, Bologna, Italy.
Horace RomanIFEMEndo, Clinique Tivoli-Ducos, Bordeaux, France.
Maria RosendalDepartment of Gynecology and Obstetrics, Kolding Hospital, Kolding, Denmark.
Renato SeracchioliIRCCS Azienda Ospedaliero-Universitaria Di Bologna, Bologna, Italy.
Tommaso SimonciniDepartment of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.
Phuong Lien TranDepartment of Obstetrics and Gynecology, University Hospital of South Reunion, Saint Pierre Réunion, France.
Claire Marie TouretteDepartement of Obstetrics and Gynecology, Centre Hospitalier Universitaire La Conception Assistance Publique Des Hôpitaux de Marseille (APHM), Marseille, France.
Arnaud HuaulméINSERM, Rennes University, LTSI-UMR 1099, Rennes, France.
Pierre JanninINSERM, Rennes University, LTSI-UMR 1099, Rennes, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the widespread use of robot-assisted total laparoscopic hysterectomy (rTLH), there is still significant variability in how the procedure is performed, leading to inconsistencies in surgical outcomes and challenges in training. While existing curricula focus on technical skills, they lack formal models that capture procedural logic and variability. An expert-validated, standardized SPM is essential for improving reproducibility, enhancing surgical education, and enabling integration with artificial intelligence (AI)-driven systems. We sought to develop the first consensus-based surgical process model (SPM) for standard rTLH SPM (e.g., normal BMI, non-enlarged uterus) using a Delphi methodology involving international experts.

methodsA five-round Delphi study was conducted from November 2023 to October 2024 with 35 expert robotic gynecologic surgeons from 10 countries. Panelists iteratively reviewed, refined, and reached consensus on the phases, steps, and SPM paths of rTLH. Consensus was defined as ≥ 75% agreement on Likert scale responses.

resultsThe final SPM comprises 7 phases and 34 surgical steps, each precisely defined through expert consensus. Seven validated SPM paths were identified, reflecting real-world procedural variability while preserving a common surgical practice centered on uterine pedicle dissection.

conclusionsThis study provides the first internationally validated SPM for rTLH, offering a formal, adaptable representation of the procedure. The model supports improved training and objective performance assessment, and serves as a foundational tool for surgical data science and AI applications in robotic gynecologic surgery.

Indexed as

HysterectomyLaparoscopyRobotic Surgical ProceduresArtificial IntelligenceClinical CompetenceConsensusDelphi TechniqueFemaleHumansDelphiExpert consensusHysterectomyLaparoscopyRobot-assisted surgerySurgical process model

Identifiers

What Socratic holds

Textmetadata
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Registered trials

None linked

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 Socratic graph.