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Record W3036345379 · doi:10.5489/cuaj.6460

Are basic robotic surgical skills transferable from the simulator to the operating room? A randomized, prospective, educational study

2020· article· en· W3036345379 on OpenAlexaffvenue
Ahmad Almarzouq, Jason Hu, Yasser A. Noureldin, Anne Yin, Maurice Anidjar, Franck Bladou, Simon Tanguay, Wassim Kassouf, Armen Aprikian, Sero Andonian

Bibliographic record

VenueCanadian Urological Association Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMedicineAnastomosisProstatectomyDa Vinci Surgical SystemRandomized controlled trialSimulationRobotic surgerySurgeryPhysical therapyComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: We aimed to assess the transferability of basic robotic skills from the simulator to the operating room (OR) while performing robotic-assisted radical prostatectomy (RARP). METHODS: Fourteen urology residents were randomized into two groups: group A was required to practice three sessions (nine tasks each) on the simulator, whereas group B was required to practice (same nine tasks) until they reached competency. Both groups were recorded while practicing on the da Vinci Surgical Skills Simulator. Both groups were then recorded while performing bladder mobilization during RARP. Senior residents from both groups were also recorded while performing urethro-vesical anastomosis during RARP. Recordings were assessed blindly using the validated Global Evaluative Assessment of Robotic Skills (GEARS) tool by C-SATS. Spearman's correlation coefficient (rho) was used to assess correlation between GEARS scores from practice sessions on the da Vinci Simulator and the GEARS scores from bladder mobilization and urethro-vesical anastomosis during RARP. RESULTS: There was no difference in total GEARS scores between the two groups in the OR. Total GEARS scores for "ring and rail 2" and "suture sponge" tasks correlated with the total GEARS scores during urethro-vesical anastomosis (rho=0.86, p=0.007; rho=0.90, p=0.002, respectively). GEARS' efficiency component during "energy and dissection" task on the da Vinci Simulator correlated with GEARS' efficiency component during bladder mobilization (rho=0.62, p=0.03). GEARS' force sensitivity component during "ring and rail 2" and "dots and needles" tasks on the da Vinci Simulator correlated with GEARS' force sensitivity component during bladder mobilization (rho=0.58, p=0.047; rho =0.65, p=0.02, respectively). CONCLUSIONS: Objective assessments of urology residents on the da Vinci Surgical Skills Simulator tasks ring and rail 2 and suture sponge correlated with their objective assessments of bladder mobilization and urethro-vesical anastomosis. Therefore, basic robotic skills could be transferred from the simulator to the OR.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.019
GPT teacher head0.263
Teacher spread0.243 · 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 designObservational
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

Citations22
Published2020
Admission routes2
Has abstractyes

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