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Record W2746966805 · doi:10.7759/cureus.1575

Modelling and Manufacturing of a 3D Printed Trachea for Cricothyroidotomy Simulation

2017· article· en· W2746966805 on OpenAlexaffabout
Gregory Doucet, Stephen F. Ryan, Michael Bartellas, Michael H. Parsons, Adam Dubrowski, Tia Renouf

Bibliographic record

VenueCureus · 2017
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedicineRapid prototypingFlexibility (engineering)3d printedMedical simulationSimulation3D printing3d printerComputer scienceBiomedical engineeringMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Cricothyroidotomy is a life-saving medical procedure that allows for tracheal intubation. Most current cricothyroidotomy simulation models are either expensive or not anatomically accurate and provide the learner with an unrealistic simulation experience. The goal of this project is to improve current simulation techniques by utilizing rapid prototyping using 3D printing technology and expert opinions to develop inexpensive and anatomically accurate trachea simulators. In doing so, emergency cricothyroidotomy simulation can be made accessible, accurate, cost-effective and reproducible. Three-dimensional modelling software was used in conjunction with a desktop three-dimensional (3D) printer to design and manufacture an anatomically accurate model of the cartilage within the trachea (thyroid cartilage, cricoid cartilage, and the tracheal rings). The initial design was based on dimensions found in studies of tracheal anatomical configuration. This ensured that the landmarking necessary for emergency cricothyroidotomies was designed appropriately. Several revisions of the original model were made based on informal opinion from medical professionals to establish appropriate anatomical accuracy of the model for use in rural/remote cricothyroidotomy simulation. Using an entry-level desktop 3D printer, a low cost tracheal model was successfully designed that can be printed in less than three hours for only $1.70 Canadian dollars (CAD). Due to its anatomical accuracy, flexibility and durability, this model is great for use in emergency medicine simulation training. Additionally, the model can be assembled in conjunction with a membrane to simulate tracheal ligaments. Skin has been simulated as well to enhance the realism of the model. The result is an accurate simulation that will provide users with an anatomically correct model to practice important skills used in emergency airway surgery, specifically landmarking, incision and intubation. This design is a novel and easy to manufacture and reproduce, high fidelity trachea model that can be used by educators with limited resources.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.341
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations27
Published2017
Admission routes2
Has abstractyes

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