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Record W2978743357 · doi:10.1097/prs.0000000000005911

Reevaluating the Current Model of Rhinoplasty Training and Future Directions: A Role for Focused, Maneuver-Specific Simulation

2019· review· en· W2978743357 on OpenAlexaffabout
Dino Zammit, Nirros Ponnudurai, Tyler Safran, Mirko S. Gilardino

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2019
Typereview
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsMcGill University
Fundersnot available
KeywordsRhinoplastyMedicineNosePhysical therapySurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Rhinoplasty is known for its complexity in planning and execution. For trainees, knowledge acquisition is often adequately attained. The mastery of skills, however, occurs by means of hands-on exposure, which continues to be a challenge. This article discusses the positive progress made in rhinoplasty training, and objectively demonstrates a need for more hands-on rhinoplasty exposure for residents. METHODS: A systematic review was performed in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Concurrently, an online survey was developed, assessing resident comfort and training in rhinoplasty, and e-mailed to Canadian and U.S. plastic surgery training programs. RESULTS: ONE HUNDRED THIRTY-EIGHT: residents completed the survey, 62 junior (first- to third-year residents) and 76 senior residents (fourth- to sixth-year residents). Seventy-two percent of senior residents (95 percent of sixth-year residents) reported adequate rhinoplasty exposure, as opposed to 13 percent of junior residents. Seventy-five percent of senior residents most often participated as observers or first assistants, 25 percent participated as co-surgeons, and 73.9 percent did not perform a key rhinoplasty step more than five times. Residents felt the three most difficult steps of rhinoplasty were nasal osteotomy (76.1 percent), caudal septum/anterior nasal spine manipulation (65.2 percent), and nasal tip sutures (55.8 percent), and 73.9 percent felt that simulator training would substantially improve confidence. CONCLUSIONS: Despite sufficient exposure to rhinoplasties, residents were least confident in performing rhinoplasties relative to other aesthetic procedures, likely because of the high proportion of rhinoplasty exposure that is observational as opposed to hands-on acquisition of surgical maneuvers in the operating room. The survey established the maneuvers residents find the most difficult, and as programs adopt competency-based training, developing rhinoplasty simulators targeting specific identified steps may help improve competence for rhinoplasty skills.

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)0.036
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.001
Science and technology studies0.0020.007
Scholarly communication0.0100.011
Open science0.0050.003
Research integrity0.0040.007
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 head0.173
GPT teacher head0.358
Teacher spread0.185 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations20
Published2019
Admission routes2
Has abstractyes

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