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Quality over quantity: early performance predicts suturing proficiency in robotic surgery simulation
Júlia Iaroseski1,2, André Vicente Bigolin3, Sofia Galvão Lima4
1Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil. julia.iaroseski@gmail.com.
Journal of Robotic Surgery
|July 20, 2026
Summary
Early simulator performance scores, not just training time, predict proficiency in robotic surgery suturing. This suggests individualized training pathways for better surgical skill development.
Area of Science:
- Medical Education
- Surgical Simulation
- Robotic Surgery
Background:
- Simulation-based training is crucial for robotic surgery.
- Objective metrics are used, but early performance prediction is unclear.
Purpose of the Study:
- To determine if early simulator performance predicts later proficiency in complex robotic suturing tasks.
- To analyze the association between early training metrics and final suturing performance.
Main Methods:
- Retrospective observational cohort study of 57 participants.
- Analysis of simulation training data (time, repetitions, mean scores) from Basic, Essential, and Fundamentals modules.
- Correlation analysis with the final simulator-derived Suture Score.
Main Results:
- Mean performance scores in Basic and Fundamentals modules correlated with shorter suturing time (p < 0.05).
- Basic module mean score associated with higher final Suture Score (p = 0.037).
- Total simulation time and repetitions did not correlate significantly with final proficiency (p > 0.05).
Conclusions:
- Early simulator performance scores are more predictive of robotic suturing proficiency than training duration.
- Findings support individualized, performance-based training pathways in robotic surgery.
