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Record W6981076360

The development and validation of a synthetic septoplasty surgical training model

2018· dissertation· en· W6981076360 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typedissertation
Languageen
FieldArts and Humanities
TopicLandscape and Cultural Studies
Canadian institutionsnot available
FundersMcGill University
KeywordsSeptoplastyReplicaNasal septumLikert scaleRhinoplastyResection
DOInot available

Abstract

fetched live from OpenAlex

Background: Septoplasty surgery is a core competency for an otolaryngologist.It is performed through the relatively small nostrils and involves multiple steps, which make the procedure difficult to observe and learn.Objective: To develop and validate a high fidelity septoplasty training tool built using three-dimensional printing technology.Methods: One deviated nasal septum case was chosen from among multiple computed tomography (CT) scans.The radiographic data were exported and underwent segmentation to obtain a complete computer model and used to create a synthetic replica of a deviated nasal septum using additive manufacturing.Each printed prototype was examined by two experienced otolaryngologists and changes were made as needed.The final physical replica was then evaluated for septoplasty simulation by 20 otolaryngologists with different levels of training.A survey was completed by each participant after the simulation, and observations associated with each simulation were obtained, including the time needed to complete the simulation and the rate of complications , such as the number of flap perforations that occurred. Results:The fabricated physical replica of the nasal septum incorporated two different materials mixed to obtain different stiffnesses that approximated the properties of the nasal septum, and allowed the users to perform the basic steps of septoplasty, such as flap elevation and deviation resection.The replica was anatomically correct.The steps required to complete the simulation were found to be realistic, with scores of 4.05 (0.82) and 4.2 (1), respectively, on a 5-point Likert scale.Ninety-two percent of the residents v desired the replica to be implemented into their teaching curriculum.There was a significant difference (p < 0.05) between the expert, intermediate, and novice groups in the (i) time taken, (ii) nares cut, and (ii) task-specific checklist answers.However, for other performance metrics, no significant differences were found.The septoplasty taskspecific checklist and global assessment tool also yielded significant differences between results from trainees with different levels of experience. Conclusion:The replica presents a new and innovative option for the training of junior trainees in a safe environment.This is the first physical replica of the nasal septum introduced for this purpose.The findings of the study support the validity of the replica for surgical training purposes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.236
Teacher spread0.195 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2018
Admission routes1
Has abstractyes

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