Evidence map›Paper›PMID 40514589›Full record

SynthesisJournal of robotic surgery2025

Determining the metrics of competence in robotic hysterectomy: a systematic review.

Kayla Arcamo, Sita Murugappan, Kirsten Larkins, Helen Mohan, Anthony Costello, Adam Pendlebury, Orla McNally, Rosie McBain

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of robotic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

8 authors.

Kayla ArcamoInternational Medical Robotics Academy, Parkville, Melbourne, Australia. arcamo.kayla@gmail.com.
Sita MurugappanInternational Medical Robotics Academy, Parkville, Melbourne, Australia.
Kirsten LarkinsPeter MacCallum Cancer Centre, Parkville, Melbourne, Australia.
Helen MohanUniversity of Melbourne, Parkville, Melbourne, Australia.
Anthony CostelloInternational Medical Robotics Academy, Parkville, Melbourne, Australia.
Adam PendleburyInternational Medical Robotics Academy, Parkville, Melbourne, Australia.
Orla McNallyInternational Medical Robotics Academy, Parkville, Melbourne, Australia.
Rosie McBainInternational Medical Robotics Academy, Parkville, Melbourne, Australia. rosie.mcbain@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapidly increasing use of robotic-assisted surgery in gynecology, there is a clear need for a structured robotic hysterectomy curriculum. To develop an effective training program, valid performance metrics that reliably assess skill level is required. As part of robotic curriculum development with IMRA using Kern's framework, this systematic review aims to identify proposed metrics of competence and assess their validity within the context of robotic hysterectomy training. A systematic literature search of OVID MEDLINE and EMBASE was conducted following the PRISMA guidelines, with keywords related to 'hysterectomy', 'robot-assisted', and 'metric'. The study aims, methods, outcomes, description of metrics, measurements of metrics, and metrics validity were extracted and analyzed. The initial search yielded 531 articles, of which 3 were included. Three additional articles were identified through citation and website searching, resulting in a total of six articles being included in this review. Development and identification of both simulator and intraoperative metrics greatly varied between the studies. Several studies utilized an expert consensus-based methodology, such as a modified Delphi methodology, to develop performance metrics. All metrics were assessed for content, construct, and predictive validity. Two studies were able to demonstrate predictive validity; however, there was limited correlation between virtual reality simulator metrics and intraoperative scores. This review highlights the lack of standardized and validated metrics specific to robotic hysterectomy, as well as the inability of established assessment tools to differentiate between robotic surgical skill level. This forms the context for ongoing work at IMRA to develop a granular assessment tool to assess skill acquisition as part of a robotic hysterectomy curriculum.

Indexed as

Clinical CompetenceHysterectomyRobotic Surgical ProceduresCurriculumFemaleHumansMetrics of competenceRobotic hysterectomyRobotic hysterectomy curriculumRobotic surgical education

Identifiers

PMID40514589
PMCPMC12165868

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.