ArticlePlastic and reconstructive surgery. Global open2022
Intraoperative "Spare Parts": A Novel High-fidelity Suturing Model for Trainees.
Article in Plastic and reconstructive surgery. Global open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- A Comparison of Models for Teaching Suturing and Surgical Skills to Dental Students.International journal of dentistry · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many models exist to help the medical student learn how to suture at a competency level required to progress to suturing on patients. However, these models do not readily simulate the qualities of live human tissue. We propose a simple intraoperative high-fidelity model that places the excised autologous patient tissue (eg, panniculectomy and breast reduction) on a sterile side table to allow the trainee to practice their skills alongside the staff surgeon on comparable tissue for the remainder of the case. We believe that the adoption of this practice allows a unique opportunity for medical students to advance their suturing techniques in a low-stress environment with staff surgeon guidance, further preparing them to perform high-quality closures on live patients.
Identifiers
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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.