Evidence map›Paper›PMID 28078455›Full record

Trial reportSurgical endoscopy2017

Retention of laparoscopic and robotic skills among medical students: a randomized controlled trial.

Megan S Orlando, Lauren Thomaier, Melinda G Abernethy, Chi Chiung Grace Chen

Registry-linked trialAbstract readRandomized Controlled Trial
PubMed Publisher
In one paragraph

Trial report in Surgical endoscopy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02370407 (Assessment of the Transferability of Skills From Robotic to Laparoscopic Simulation Platforms in Surgical Skill Naive Participants), which is not on this map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 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.

NCT02370407 nacompletednot on this map

Assessment of the Transferability of Skills From Robotic to Laparoscopic Simulation Platforms in Surgical Skill Naive Participants

TypeinterventionalSponsorJohns Hopkins UniversityRan2014 to 2015Enrolled40ConditionsSurgical Simulation EducationArmsa laparoscopic simulator (Fundamentals of Laparoscopic Surgery (FLS), VT Medical Inc, Waltham, MA), Mimic da Vinci robotic simulator
3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  15. Medical Students' Attitude Towards Robotic Surgery: A Cross-Sectional Survey.Journal of medical education and curricular development
    Article
  16. Development of a Senior Medical Student Robotic Surgery Training Elective.Journal of medical education and curricular development
    Article
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

4 authors.

Megan S OrlandoDivision of Female Pelvic Medicine and Reconstructive Surgery, Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, 301 Mason Lord Drive Suite 3200, Baltimore, MD, 21224, USA.
Lauren ThomaierDivision of Female Pelvic Medicine and Reconstructive Surgery, Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, 301 Mason Lord Drive Suite 3200, Baltimore, MD, 21224, USA.
Melinda G AbernethyDivision of Female Pelvic Medicine and Reconstructive Surgery, Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, 301 Mason Lord Drive Suite 3200, Baltimore, MD, 21224, USA.
Chi Chiung Grace ChenDivision of Female Pelvic Medicine and Reconstructive Surgery, Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, 301 Mason Lord Drive Suite 3200, Baltimore, MD, 21224, USA. cchen127@jhmi.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough simulation training beneficially contributes to traditional surgical training, there are less objective data on simulation skills retention.

objectiveTo investigate the retention of laparoscopic and robotic skills after simulation training.

methodsWe present the second stage of a randomized single-blinded controlled trial in which 40 simulation-naïve medical students were randomly assigned to practice peg transfer tasks on either laparoscopic (N = 20, Fundamentals of Laparoscopic Surgery, Venture Technologies Inc., Waltham, MA) or robotic (N = 20, dV-Trainer, Mimic, Seattle, WA) platforms. In the first stage, two expert surgeons evaluated participants on both tasks before (Stage 1: Baseline) and immediately after training (Stage 1: Post-training) using a modified validated global rating scale of laparoscopic and robotic operative performance. In Stage 2, participants were evaluated on both tasks 11-20 weeks after training.

resultsOf the 40 students who participated in Stage 1, 23 (11 laparoscopic and 12 robotic) underwent repeat evaluation. During Stage 2, there were no significant differences between groups in objective or subjective measures for the laparoscopic task. Laparoscopic-trained participants' performances on the laparoscopic task were improved during Stage 2 compared to baseline measured by time to task completion, but not by the modified global rating scale. During the robotic task, the robotic-trained group demonstrated superior economy of motion (p = .017), Tissue Handling (p = .020), and fewer errors (p = .018) compared to the laparoscopic-trained group. Robotic skills acquisition from baseline with no significant deterioration as measured by modified global rating scale scores was observed among robotic-trained participants during Stage 2.

conclusionRobotic skills acquired through simulation appear to be better maintained than laparoscopic simulation skills. CLINICAL TRIAL: This study is registered on ClinicalTrials.gov (NCT02370407).

Indexed as

Education, MedicalAdultClinical CompetenceComputer SimulationFemaleHumansLaparoscopyMaleRoboticsRobotic Surgical ProceduresSimulation TrainingLaparoscopyRobotic skillsSimulationSurgical simulationSurgical training

Identifiers

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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.