Evidence map›Paper›PMID 33251703›Full record

ArticleBJU international2021

Objective assessment of intraoperative skills for robot-assisted radical prostatectomy (RARP): results from the ERUS Scientific and Educational Working Groups Metrics Initiative.

Alexandre Mottrie, Elio Mazzone, Peter Wiklund, Markus Graefen, Justin W Collins, Ruben De Groote, Paolo Dell'Oglio, Stefano Puliatti, Anthony G Gallagher

Registry-linked trialOpen access · hybridAbstract read
In one paragraph

Article in BJU international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07669974 (A Randomized Non-Inferiority Trial Comparing Two Training Modalities for Achieving Proficiency in Robot-Assisted Radical Prostatectomy), which is not on this map. Cited by 39 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 4 pooled it
8.0field-weighted citation impact, top 2% of its field
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.

NCT07669974 narecruitingnot on this mapstarted 2026, after this paper: background citation

A Randomized Non-Inferiority Trial Comparing Two Training Modalities for Achieving Proficiency in Robot-Assisted Radical Prostatectomy

TypeinterventionalSponsorOrsi AcademyRan2026 to 2027Enrolled56ConditionsRobot-Assisted Radical Prostatectomy Training, ProstatectomyArmsIMRA-Enhanced Training Pathway, Standard Training Pathway
3 · Its place in the literature

Who cites it

39 citing papers in PubMed, 4 syntheses or guidelines pooled it, 65 citations in OpenAlex.

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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

9 authors at 8 institutions in 6 countries.

Alexandre MottrieOrsi Academy, Melle, Belgium.
Elio MazzoneOrsi Academy, Melle, Belgium.ORCID 0000-0003-1932-1800
Peter WiklundDepartment of Urology, Karolinska Institutet, Stockholm, Sweden.
Markus GraefenMartini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany.
Justin W CollinsOrsi Academy, Melle, Belgium.ORCID 0000-0003-2228-1213
Ruben De GrooteOrsi Academy, Melle, Belgium.
Paolo Dell'OglioOrsi Academy, Melle, Belgium.ORCID 0000-0002-2771-2919
Stefano PuliattiOrsi Academy, Melle, Belgium.
Anthony G GallagherOrsi Academy, Melle, Belgium.
Onze Lieve Vrouwziekenhuis Hospital · BEAzienda Socio Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda · ITMount Sinai Health System · USUniversität Hamburg · DEUniversity College Hospital · GBUniversity of Modena and Reggio Emilia · ITUniversity of Ulster · GBVita-Salute San Raffaele University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop and seek consensus from procedure experts on the metrics that best characterise a reference robot-assisted radical prostatectomy (RARP) and determine if the metrics distinguished between the objectively assessed RARP performance of experienced and novice urologists, as identifying objective performance metrics for surgical training in robotic surgery is imperative for patient safety. MATERIALS AND

methodsIn Study 1, the metrics, i.e. 12 phases of the procedure, 81 steps, 245 errors and 110 critical errors for a reference RARP were developed and then presented to an international Delphi panel of 19 experienced urologists. In Study 2, 12 very experienced surgeons (VES) who had performed >500 RARPs and 12 novice urology surgeons performed a RARP, which was video recorded and assessed by two experienced urologists blinded as to subject and group. Percentage agreement between experienced urologists for the Delphi meeting and Mann-Whitney U- and Kruskal-Wallis tests were used for construct validation of the newly identified RARP metrics.

resultsAt the Delphi panel, consensus was reached on the appropriateness of the metrics for a reference RARP. In Study 2, the results showed that the VES performed ~4% more procedure steps and made 72% fewer procedure errors than the novices (P = 0.027). Phases VIIa and VIIb (i.e. neurovascular bundle dissection) best discriminated between the VES and novices. LIMITATIONS: VES whose performance was in the bottom half of their group demonstrated considerable error variability and made five-times as many errors as the other half of the group (P = 0.006).

conclusionsThe international Delphi panel reached high-level consensus on the RARP metrics that reliably distinguished between the objectively scored procedure performance of VES and novices. Reliable and valid performance metrics of RARP are imperative for effective and quality assured surgical training.

Indexed as

BenchmarkingClinical CompetenceRobotic Surgical ProceduresConsensusHumansMaleMedical ErrorsProstatectomyProstatic Neoplasmsconstruct validation#EndoUrology#PCSMproficiency-based metricsproficiency-based training#Prostate Cancerrobot-assisted radical prostatectomysurgical training#uroonc

Identifiers

PMID33251703
PMCPMC8359192
OpenAlexW3107091751

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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.