Evidence map›Paper›PMID 40957606›Full record

Trial reportThe Thoracic and cardiovascular surgeon2026

A Novel Competency-Based Simulation Model for Thoracoscopic Lung Resection.

Ganwei Liu, Feng Yang, Zuli Zhou, Guanchao Jiang

Abstract readRandomized Controlled TrialComparative Study
In one paragraph

Trial report in The Thoracic and cardiovascular surgeon, 2026. 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. Review
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.

Ganwei LiuDepartment of Thoracic Surgery, Peking University People's Hospital, Beijing, People's Republic of China.
Feng YangDepartment of Thoracic Surgery, Peking University People's Hospital, Beijing, People's Republic of China.
Zuli ZhouDepartment of Thoracic Surgery, Peking University People's Hospital, Beijing, People's Republic of China.
Guanchao JiangDepartment of Thoracic Surgery, Peking University People's Hospital, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Simulation-based thoracic surgery training is increasingly incorporating physical models to enhance traditional learning methods. Conventional box trainers, though useful for basic skills, often lack anatomical accuracy and tactile feedback, limiting their relevance for complex procedures like thoracoscopic lung resection. High-fidelity 3D-printed lung models offer realistic anatomy and procedural flow, but their educational impact remains underexplored.Fifty-two surgical residents without prior thoracoscopic experience were randomly assigned to a high-fidelity lung model group or a conventional Fundamentals of Laparoscopic Surgery (FLS) box trainer group. All participants completed a baseline thoracic anatomy test and received standardized educational materials. The lung model group received structured simulation training on procedural anatomy and operative steps, while the FLS group practiced fundamental laparoscopic tasks. After training, participants repeated the anatomy test and performed a thoracoscopic lung wedge resection in a live animal model. Performance was assessed using the Objective Structured Assessment of Technical Skill (OSATS) and a 5-point confidence scale.A total of 52 surgical residents participated in the study, with 26 assigned to the high-fidelity lung model group and 26 to the FLS trainer group. Baseline anatomy scores were similar between groups (65.42  ±  6.10 vs. 66.12  ±  5.92;

Indexed as

Clinical CompetenceEducation, Medical, GraduateHigh Fidelity Simulation TrainingInternship and ResidencyLungModels, AnatomicPneumonectomyPrinting, Three-DimensionalSimulation TrainingSurgeonsThoracoscopyAnimalsCurriculumFemaleHumansLearning Curve

Identifiers

PMID40957606
PMCPMC12912906

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.