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Record W4289345266 · doi:10.3171/2022.5.focus22188

High-fidelity, simulation-based microsurgical training for neurosurgical residents

2022· article· en· W4289345266 on OpenAlexafffundabout
Brendan Santyr, Mohamad Abbass, Alan Chalil, Amirti Vivekanandan, Daria Krivosheya, Lynn Denning, Thomas Mattingly, Faizal Haji, Stephen P. Lownie

Bibliographic record

VenueNeurosurgical FOCUS · 2022
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsDalhousie UniversityQueen's UniversityWestern University
FundersAcademic Medical Organization of Southwestern Ontario
KeywordsCurriculumMedicineMicrosurgeryNeurosurgeryFidelityRating scaleMedical educationMedical physicsScale (ratio)Physical therapyAnastomosisSimulation trainingSurgeryPhysical medicine and rehabilitationPsychologySimulationComputer science

Abstract

fetched live from OpenAlex

OBJECTIVE: Simulation is increasingly recognized as an important supplement to operative training. The live rat femoral artery model is a well-established model for microsurgical skills simulation. In this study, the authors present an 11-year experience incorporating a comprehensive, longitudinal microsurgical training curriculum into a Canadian neurosurgery program. The first goal was to evaluate training effectiveness, using a well-studied rating scale with strong validity. The second goal was to assess the impact of the curriculum on objective measures of subsequent operating room performance during postgraduate year (PGY)-5 and PGY-6 training. METHODS: PGY-2 neurosurgery residents completed a 1-year curriculum spanning 17 training sessions divided into 5 modules of increasing fidelity. Both perfused duck wing and live rat vessel training models were used. Three modules comprised live microvascular anastomosis. Trainee performance was video recorded and blindly graded using the Objective Structured Assessment of Technical Skills Global Rating Scale. Eleven participants who completed the training curriculum and 3 subjects who had not participated had their subsequent operative performances evaluated when they were at the PGY-5 and PGY-6 levels. RESULTS: Eighteen participants completed 106 microvascular anastomoses during the study. There was significant improvement in 6 measurable skills during the curriculum. The mean overall score was significantly higher on the fifth attempt compared with the first attempt for all 3 live anastomotic modules (p < 0.001). Each module had a different improvement profile across the skills assessed. Those who completed the microvascular skills curriculum demonstrated a greater number of independent evaluations during superficial surgical exposure, deep exposure, and primary maneuvers at the PGY-5 and PGY-6 levels. CONCLUSIONS: High-fidelity microsurgical simulation training leads to significant improvement in microneurosurgical skills. Transfer of acquired skills to the operative environment and durability for at least 3 to 4 years show encouraging preliminary results and are subject to ongoing investigation.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.070
GPT teacher head0.338
Teacher spread0.268 · 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 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

Citations14
Published2022
Admission routes3
Has abstractyes

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