ArticleJTCVS open2023
Simulation-based assessment of robotic cardiac surgery skills: An international multicenter, cross-specialty trial.
Article in JTCVS open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05043064 (Validity Evidence for Simulation-based Assessment of Robotic Cardiac Surgical Skills and Examination of Learning Curves in Wet Labs), which is not on this map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Validity Evidence for Simulation-based Assessment of Robotic Cardiac Surgical Skills and Examination of Learning Curves in Wet Labs
Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Artificial intelligence-based action recognition and skill assessment in robotic cardiac surgery simulation: a feasibility study.Journal of robotic surgery · 2025Trial
- Proficiency in Robotic Cardiac Surgery: Toward a Brazilian Training Curriculum.Brazilian journal of cardiovascular surgery · 2026Review
- Simulation Training in Video-Assisted and Robotic-Assisted Cardiac Surgery: A Narrative Review.Journal of cardiovascular development and disease · 2026Review
- Article
- Exploring the future of robotic approaches in neonatal cardiac surgery: opportunities, barriers, and innovation pathways.Journal of robotic surgery · 2025Review
- Closing the data gap: leveraging pretrained neural networks for robotic surgical assessment on limited clinical data.Journal of robotic surgery · 2025Article
- The contribution of personalized video feedback to robotic partial nephrectomy training in realistic 3D tumor kidney models: design, production and implementation.Frontiers in surgery · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 9 institutions in 6 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aimed to investigate the validity of simulation-based assessment of robotic-assisted cardiac surgery skills using a wet lab model, focusing on the use of a time-based score (TBS) and modified Global Evaluative Assessment of Robotic Skills (mGEARS) score. Methods: We tested 3 wet lab tasks (atrial closure, mitral annular stitches, and internal thoracic artery [ITA] dissection) with both experienced robotic cardiac surgeons and novices from multiple European centers. The tasks were assessed using 2 tools: TBS and mGEARS score. Reliability, internal consistency, and the ability to discriminate between different levels of competence were evaluated. Results: The results demonstrated a high internal consistency for all 3 tasks using mGEARS assessment tool. The mGEARS score and TBS could reliably discriminate between different levels of competence for the atrial closure and mitral stitches tasks but not for the ITA harvesting task. A generalizability study also revealed that it was feasible to assess competency of the atrial closure and mitral stitches tasks using mGEARS but not the ITA dissection task. Pass/fail scores were established for each task using both TBS and mGEARS assessment tools. Conclusions: The study provides sufficient evidence for using TBS and mGEARS scores in evaluating robotic-assisted cardiac surgery skills in wet lab settings for intracardiac tasks. Combining both assessment tools enhances the evaluation of proficiency in robotic cardiac surgery, paving the way for standardized, evidence-based preclinical training and credentialing. Clinical trial registry number: NCT05043064.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.