Evidence map›Paper›PMID 40470119›Full record

ArticleCJC pediatric and congenital heart disease2025

Pilot Study on Integrating 3D-Printed Models Into Undergraduate Medical Education for Congenital Heart Disease.

Wan Cheol Kim, Suyeon Sarah Kim, Victor Neira, John Lewis Sapp, Osama Elkhateeb

Abstract read
In one paragraph

Article in CJC pediatric and congenital heart disease, 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. 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

5 authors.

Wan Cheol KimDivision of Cardiology, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, Nova Scotia, Canada.
Suyeon Sarah KimDivision of Cardiology, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, Nova Scotia, Canada.
Victor NeiraDepartment of Anesthesia, Queen Elizabeth II Health Sciences Centre, Halifax, Nova Scotia, Canada.
John Lewis SappDivision of Cardiology, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, Nova Scotia, Canada.
Osama ElkhateebDivision of Cardiology, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, Nova Scotia, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aimed to assess the feasibility and effectiveness of implementing 3-dimensional (3D)-printed heart models in the education of medical students in a Canadian Medical School. Methods: Three types of 3D-printed models-normal, unrepaired tetralogy of Fallot (TOF), and surgically repaired adult TOF-were provided for medical students in their second year of training after a 30-minute lecture. The repaired TOF model depicted a transannular patch, ventricular septal defect closure, and right ventricular outflow tract resection. Knowledge acquisition was measured by comparing pre- and postsession tests consisting of 5 questions. Learner satisfaction ratings were measured with questionnaires completed after the session. A statistical analysis was performed using the Results: Twenty-two medical students participated in the study with 20 students submitting complete data for analysis. The students' score on 5 questions improved after the 3D-printed model session. The average number of correct answers in the test was 2.1 ± 1.0 before the session and 4.3 ± 0.9 after the session ( Conclusions: An educational session that integrated 3D-printed anatomic models to teach congenital heart disease anatomy significantly enhanced knowledge outcomes. Learner assessment of the impact of the use of the 3D models was highly favourable.

Identifiers

PMID40470119
PMCPMC12130995

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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.