Evidence map›Paper›PMID 38383688›Full record

ArticleSurgical endoscopy2024

Validity and reliability evidence support task-specific metrics for laparoscopic fundoplication.

Alexis Desir, Carolina Marques, Emile Farah, Shruti R Hegde, Carla Holcomb, Daniel J Scott, Ganesh Sankaranarayanan

Abstract read
PubMed Publisher
In one paragraph

Article in Surgical endoscopy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.7field-weighted citation impact, top 18% 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.

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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Machine Learning-Based Automated Assessment of Intracorporeal Suturing in Laparoscopic Fundoplication.Global surgical education : journal of the Association for Surgical Education · 2025
    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

7 authors at 2 institutions in 1 country.

Alexis DesirDepartment of Surgery, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, 75390, USA.
Carolina MarquesArtificial Intelligence and Medical Simulation Lab, Department of Surgery, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, 75390, USA.
Emile FarahDepartment of Surgery, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, 75390, USA.
Shruti R HegdeDepartment of Surgery, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, 75390, USA.
Carla HolcombDepartment of Surgery, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, 75390, USA.
Daniel J ScottDepartment of Surgery, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, 75390, USA.
Ganesh SankaranarayananDepartment of Surgery, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, 75390, USA. Ganesh.Sankaranarayanan@utsouthwestern.edu.ORCID 0000-0003-1556-2797
The University of Texas Southwestern Medical Center · USSouthwestern Medical Center · US

Funding

R01EB025247: Development and Validation of a Virtual Laparoscopic Hiatal Hernia Simulator (VLaHHS)R01EB025247 · NIBIB · UT SOUTHWESTERN MEDICAL CENTER · PI SANKARANARAYANAN, GANESH · 2019 to 2023
$2.4M
NIBIB NIH HHS EB025247
6 · The paper itself

Abstract

backgroundLaparoscopic hiatal hernia repair (LHHR) is a complex operation requiring advanced surgical training. Surgical simulation offers a potential solution for learning complex operations without the need for high surgical volume. Our goal is to develop a virtual reality (VR) simulator for LHHR; however, data supporting task-specific metrics for this procedure are lacking. The purpose of this study was to develop and assess validity and reliability evidence of task-specific metrics for the fundoplication phase of LHHR.

methodsIn phase I, structured interviews with expert foregut surgeons were conducted to develop task-specific metrics (TSM). In phase II, participants with varying levels of surgical expertise performed a laparoscopic Nissen fundoplication procedure on a porcine stomach explant. Video recordings were independently assessed by two blinded graders using global and TSM. An intraclass correlation coefficient (ICC) was used to assess interrater reliability (IRR). Performance scores were compared using a Kruskal-Wallis test. Spearman's rank correlation was used to evaluate the association between global and TSM.

resultsPhase I of the study consisted of 12 interviews with expert foregut surgeons. Phase II engaged 31 surgery residents, a fellow, and 6 attendings in the simulation. Phase II results showed high IRR for both global (ICC = 0.84, p < 0.001) and TSM (ICC = 0.75, p < 0.001). Significant between-group differences were detected for both global (χ

conclusionWe developed task-specific metrics for LHHR and using a fundoplication model, we documented significant reliability and validity evidence. We anticipate that these LHHR task-specific metrics will be useful in our planned VR simulator.

Indexed as

FundoplicationLaparoscopyAnimalsClinical CompetenceComputer SimulationHumansReproducibility of ResultsStomachSwineNissen fundoplicationSurgical educationTask-specific metricsVR simulator

Identifiers

PMID38383688
OpenAlexW4391994269

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.