ReviewJournal of Korean medical science2022
Congenital Heart Surgery Skill Training Using Simulation Models: Not an Option but a Necessity.
Review in Journal of Korean medical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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.
Who cites it
7 citing papers in PubMed.
- Printing the future of surgical education: a randomized trial of digital tools in cardiovascular training.Cardiovascular diagnosis and therapy · 2026Article
- Future Applications for 3-dimensional Printed Virtual Surgical Planning in Microsurgery.Plastic and reconstructive surgery. Global open · 2025Article
- Analysis and Visualization of Inter-/Intra-surgeon Variability Using Surgical Simulation for Partial Anomalous Pulmonary Venous Connection Repair.Pediatric cardiology · 2025Article
- The Pocket Strabismus Surgical Skills Trainer: design and validation.Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus · 2025Article
- Evaluation of the Efficacy and Accuracy of Super-Flexible Three-Dimensional Heart Models of Congenital Heart Disease Made via Stereolithography Printing and Vacuum Casting: A Multicenter Clinical Trial.Journal of cardiovascular development and disease · 2024Article
- Longitudinal Evaluation of Congenital Cardiovascular Surgical Performance and Skills Retention Using Silicone-Molded Heart Models.World journal for pediatric & congenital heart surgery · 2024Article
- Patient-Specific 3D-Printed Models in Pediatric Congenital Heart Disease.Children (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Congenital heart surgery (CHS) is technically demanding, and its training is extremely complex and challenging. Training of the surgeon's technical skills has relied on a preceptorship format in which the trainees are gradually exposed to patients in the operating room under the close tutelage of senior staff surgeons. Training in the operating room is an inefficient process and the concept of a learning curve is no longer acceptable in terms of patient outcomes. The benefits of surgical simulation in training of congenital heart surgeons are well known and appreciated. However, adequate surgical simulation models and equipment for training have been scarce until the recent development of three-dimensionally (3D) printed models. Using comprehensive 3D printing and silicone-molding techniques, realistic simulation training models for most congenital heart surgical procedures have been produced. Newly developed silicone-molded models allow efficient CHS training in a stress-free environment with instantaneous feedback from the proctors and avoids risk to patients. The time has arrived when all congenital heart surgeons should consider surgical simulation training before progressing to real-life operating in a similar fashion to the aviation industry where all pilots are required to complete simulation training before flying a real aircraft. It is argued here that simulation training is not an option anymore but should be a mandatory component of CHS training.
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Registered trials
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.