Evidence map›Paper›PMID 38217749›Full record

SynthesisJournal of robotic surgery2024

Measures of performance and proficiency in robotic assisted surgery: a systematic review.

Charlotte El-Sayed, A Yiu, J Burke, P Vaughan-Shaw, J Todd, P Lin, Z Kasmani, C Munsch, L Rooshenas, M Campbell and 1 more

Erratum issuedAbstract readSystematic ReviewLetter
PubMed Publisher
In one paragraph

Synthesis in Journal of robotic surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 3 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

11 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Instructional Design for Surgical Novices Based on Cognitive Load Theory: Implications for Urologic Surgery Training.International journal of urology : official journal of the Japanese Urological Association · 2026
    Review
  6. Article
  7. Article
  8. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Charlotte El-SayedRCS England/HEE Robotics Research Fellow, University of Birmingham, Birmingham, United Kingdom. c.el-sayed@nhs.net.ORCID http://orcid.org/0000-0002-5994-5645
A YiuRCS England/HEE Robotics Research Fellow, University of Birmingham, Birmingham, United Kingdom.
J BurkeRCS England/HEE Robotics Research Fellow, University of Birmingham, Birmingham, United Kingdom.
P Vaughan-ShawRCS England/HEE Robotics Research Fellow, University of Birmingham, Birmingham, United Kingdom.
J ToddRCS England/HEE Robotics Research Fellow, University of Birmingham, Birmingham, United Kingdom.
P LinRCS England/HEE Robotics Research Fellow, University of Birmingham, Birmingham, United Kingdom.
Z KasmaniRCS England/HEE Robotics Research Fellow, University of Birmingham, Birmingham, United Kingdom.
C MunschRCS England/HEE Robotics Research Fellow, University of Birmingham, Birmingham, United Kingdom.
L RooshenasRCS England/HEE Robotics Research Fellow, University of Birmingham, Birmingham, United Kingdom.
M CampbellRCS England/HEE Robotics Research Fellow, University of Birmingham, Birmingham, United Kingdom.
S P BachRCS England/HEE Robotics Research Fellow, University of Birmingham, Birmingham, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robotic assisted surgery (RAS) has seen a global rise in adoption. Despite this, there is not a standardised training curricula nor a standardised measure of performance. We performed a systematic review across the surgical specialties in RAS and evaluated tools used to assess surgeons' technical performance. Using the PRISMA 2020 guidelines, Pubmed, Embase and the Cochrane Library were searched systematically for full texts published on or after January 2020-January 2022. Observational studies and RCTs were included; review articles and systematic reviews were excluded. The papers' quality and bias score were assessed using the Newcastle Ottawa Score for the observational studies and Cochrane Risk Tool for the RCTs. The initial search yielded 1189 papers of which 72 fit the eligibility criteria. 27 unique performance metrics were identified. Global assessments were the most common tool of assessment (n = 13); the most used was GEARS (Global Evaluative Assessment of Robotic Skills). 11 metrics (42%) were objective tools of performance. Automated performance metrics (APMs) were the most widely used objective metrics whilst the remaining (n = 15, 58%) were subjective. The results demonstrate variation in tools used to assess technical performance in RAS. A large proportion of the metrics are subjective measures which increases the risk of bias amongst users. A standardised objective metric which measures all domains of technical performance from global to cognitive is required. The metric should be applicable to all RAS procedures and easily implementable. Automated performance metrics (APMs) have demonstrated promise in their wide use of accurate measures.

Indexed as

RoboticsRobotic Surgical ProceduresSurgeonsClinical CompetenceCurriculumHumansAssessmentCurriculumMetricPerformanceRobotic surgeryTraining

Identifiers

What OpenQuestion holds

Textmetadata
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.