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Virtual reality ureteroscopy simulator as a valid tool for assessing endourological skills

2006· article· en· W1866444129 on OpenAlex
Edward D. Matsumoto, Kenneth T. Pace, R. John D’A. Honey

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Urology · 2006
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsUreteroscopyMedicineRating scaleChecklistVirtual realityCystoscopySimulationTask (project management)Medical physicsPhysical therapySurgeryUreterComputer scienceArtificial intelligencePsychologyInternal medicine

Abstract

fetched live from OpenAlex

AIM: Virtual reality (VR) simulators are now commercially available for various surgical skills training. The Uro Mentor VR Ureteroscopy Simulator by Symbionix is one system that may revolutionize the way we assess and teach surgical residents. Surgical educators may no longer have to depend on the operating room as the sole venue for teaching residents technical skills. We validated performance on this new system with previously developed assessment tools and compared it to performance on a high fidelity ureteroscopy bench model. METHODS: Urology residents (n = 16) were assessed on their ability to perform cystoscopy, guidewire insertion, semirigid ureteroscopy and basket extraction of a distal ureteric stone on the VR simulator. A blinded examiner assessed subject performance using a checklist, global rating scale and a pass/fail rating. In addition, computer-generated parameters including time to complete task, scope and instrument trauma and the number of attempts to insert a guidewire were analysed. Performance on the VR simulator was compared to performance on a high fidelity ureteroscopy bench model. RESULTS: Senior residents (n = 8) scored significantly higher on their global rating scale (29.4 +/- 2.5 vs 20.8 +/- 0.9, P = 0.005), checklist (19.1 +/- 1.1 vs 15.2 +/- 0.9, P = 0.02), pass/fail rating (chi(2) = 7.3, P = 0.007) and required less time to complete the task (352.9 +/- 55.7 s vs 576.8 +/- 67.4 s., P = 0.02) than the junior residents (n = 8) on the VR simulator. Junior residents also had a significantly higher incidence of scope trauma (4 vs 0.6, P = 0.02). No significant differences were noted in instrument trauma and the number of attempts to insert the guidewire. Global rating scale performance on the VR simulator correlated well to performance on the high fidelity ureteroscopy bench model (r = 0.7, P = 0.002) as did time to complete task (r = 0.7, P = 0.004). CONCLUSIONS: The Uro Mentor VR Ureteroscopy Simulator is a useful tool in assessing resident endourological skills. Performance on the VR simulator is comparable to a validated high fidelity ureteroscopy bench model. Future studies will assess the utility of VR simulators in surgical skills training.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.036
GPT teacher head0.388
Teacher spread0.352 · 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