Evidence map›Paper›PMID 39862146›Full record

ReviewFuture cardiology2025

Congenital cardiac surgical simulation: bridging global workforce gaps and optimizing outcomes.

Mimi X Deng, Dominique Vervoort, Israel Valverde, Shi-Joon Yoo, Brandon Peel, Rachel D Vanderlaan, David J Barron, Osami Honjo

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Future cardiology, 2025. 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

8 authors.

Mimi X DengDivision of Cardiac Surgery, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-0420-4791
Dominique VervoortDivision of Cardiac Surgery, University of Toronto, Toronto, ON, Canada.
Israel ValverdeDepartment of Cardiology, The Hospital for Sick Children, Toronto, ON, Canada.
Shi-Joon YooDepartment of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada.
Brandon PeelCenter for Image-Guided Innovation and Therapeutic Intervention (CIGITI), Hospital for Sick Children, Toronto, ON, Canada.
Rachel D VanderlaanDivision of Cardiac Surgery, University of Toronto, Toronto, ON, Canada.
David J BarronDivision of Cardiac Surgery, University of Toronto, Toronto, ON, Canada.
Osami HonjoDivision of Cardiac Surgery, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reaching competency in congenital heart surgery (CHS) requires lengthy and rigorous training. Due to patient safety, time limitations, and procedural complexity, the intraoperative setting is not ideal for technical practice. Surgical simulation using synthetic, biological, or virtual models is an increasingly valuable educational tool for technical training and assessment. In particular, three-dimensional (3D) models are especially favorable in CHS education for its high-fidelity demonstration of congenital heart defects. In countries where there is a deficit of local cardiac surgical expertise, simple and inexpensive innovation, such as expanding hands-on technical training programs involving 3D-models and hybrid teaching, may partially address the lack of CHS training opportunities and the consequent unmet need for surgical management of pediatric heart disease.

Indexed as

Cardiac Surgical ProceduresClinical CompetenceHeart Defects, CongenitalSimulation TrainingThoracic SurgeryHumans3D printingcongenital heart surgeryGlobal cardiac surgerypediatric cardiac surgerysurgical educationsurgical simulation

Identifiers

PMID39862146
PMCPMC11812351

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.