Evidence map›Paper›PMID 35729407›Full record

ArticleSurgical endoscopy2022

Establishing validity evidence for device-assisted advanced laparoscopic suturing tasks using simulation.

Elif Bilgic, Allan Okrainec, John Paige, Saba Balvardi, Sofia Valanci, Caterina Masino, Pepa Kaneva, Mohammed Alabri, Katherine M McKendy, Yusuke Watanabe and 2 more

Abstract read
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In one paragraph

Article in Surgical endoscopy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

12 authors.

Elif BilgicSteinberg Centre for Simulation and Interactive Learning, McGill University, Montreal, QC, Canada.ORCID http://orcid.org/0000-0003-2170-5897
Allan OkrainecTemerty Advanced Surgical Education and Simulation Centre, University Health Network, Toronto, ON, Canada.
John PaigeDepartment of Surgery, School of Medicine, LSU Health New Orleans, New Orleans, LA, USA.
Saba BalvardiSteinberg-Bernstein Centre for Minimally Invasive Surgery, McGill University Health Centre, Montreal, QC, Canada.
Sofia ValanciSteinberg-Bernstein Centre for Minimally Invasive Surgery, McGill University Health Centre, Montreal, QC, Canada.
Caterina MasinoTemerty Advanced Surgical Education and Simulation Centre, University Health Network, Toronto, ON, Canada.
Pepa KanevaSteinberg-Bernstein Centre for Minimally Invasive Surgery, McGill University Health Centre, Montreal, QC, Canada.
Mohammed AlabriSteinberg-Bernstein Centre for Minimally Invasive Surgery, McGill University Health Centre, Montreal, QC, Canada.
Katherine M McKendySteinberg-Bernstein Centre for Minimally Invasive Surgery, McGill University Health Centre, Montreal, QC, Canada.
Yusuke WatanabeDepartment of Gastroenterological Surgery II, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan.
Melina C VassiliouSteinberg-Bernstein Centre for Minimally Invasive Surgery, McGill University Health Centre, Montreal, QC, Canada.
Gerald M FriedSteinberg Centre for Simulation and Interactive Learning, McGill University, Montreal, QC, Canada. gerald.fried@mcgill.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLaparoscopic suturing (LS) is an essential technique required for a wide range of procedures, and it is one of the most challenging for surgical trainees to master. We designed and collected validity evidence for advanced LS tasks using an automated suturing device and evaluated the perceived educational value of the tasks.

methodsThis project was a multicentre prospective study involving McGill University, University of Toronto (UofT), and Louisiana State University (LSU) Health New Orleans. Novice (NS) and experienced (ES) surgeons performed suturing under tension (UT) and continuous suturing (CS) tasks. ES performed the tasks twice to establish proficiency benchmarks, and they were interviewed to develop formative feedback tools (FFT). Participants were assessed on completion time, error, Global Operative Assessment of Laparoscopic Skills (GOALS), and FFT. Data were analyzed using descriptive and inferential statistical methods.

resultsTwenty-seven participants (13 ES, 14 NS, median age 34 years; 85% male) completed the study. Eight were attending surgeons, 7 fellows, 4 PGY5, 5 PGY4, and 3 PGY3 (18 from McGill, 5 UofT, and 4 LSU). Comparing ES and NS, for UT task, ES had significantly greater task scores (570 [563-648] vs 323 [130-464], p value 0.00036) and GOALS scores (14 [13-16] vs 10 [8-12], p value 0.0038). Similarly, for CS, ES had significantly greater task scores (976 [959-1010] vs 785 [626-856], p value 0.00009) and GOALS scores (16 [12-17] vs 12.5 [8.25-15], p value 0.028). After FFTs were developed, comparing ES and NS, for both UT and CS tasks, ES had significantly greater FFT scores (UT 25 [24-26] vs 17 [14-20], p value 0.0016 and CS 30 [27-32] vs 22[17.2-25.8], p value 0.00061).

conclusionIn conclusion, preliminary validity evidence was provided for the tasks. Once further validity evidence is established, incorporating the tasks into the training curricula could improve trainee skills and help to meet the need for better advanced suturing models.

Indexed as

LaparoscopySuture TechniquesAdultClinical CompetenceFemaleHumansMaleProspective StudiesSuturesAdvanced laparoscopic suturingAssessmentDevice-assisted laparoscopic suturingSimulation

Identifiers

PMID35729407

What OpenQuestion holds

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Registered trials

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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.