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Updated: Jun 5, 2026

Simulator Training for Endovascular Neurosurgery
Published on: May 6, 2020
Simulation-Based Training for Coronary Artery Bypass Grafting: Systematic Review and Meta-analysis
Abubakar I Sidik1, Kow Entsua-Mensah2, Vladislav V Dontsov3
1Department of Cardiovascular Surgery, Peoples Friendship University of Russia (RUDN University), Moscow, Russia.
Background:
Declining operative exposure and increasing procedural complexity have challenged traditional apprenticeship models in coronary artery bypass grafting (CABG) training. Simulation-based training (SBT) has emerged as a strategy to support technical skill acquisition outside the operating room. This systematic review and meta-analysis evaluated the effectiveness of SBT in improving technical performance and procedural efficiency for CABG anastomosis.
Methods:
A comprehensive search of PubMed, Scopus, and Web of Science identified studies published between 2000 and 2025 that reported quantitative outcomes following SBT for CABG. Randomized controlled trials, quasi-experimental studies, and pre-post designs were eligible.
Results:
Eleven studies with 372 participants met the inclusion criteria. Pooled analysis showed a large improvement in overall technical performance (standardized mean difference 2.18, 95% CI 1.73-2.63; p < 0.00001) and a substantial reduction in anastomosis completion time (standardized mean difference 2.00, 95% CI 0.92-3.08; p = 0.0003). Subgroup analyses demonstrated significant benefits across simulator categories (tissue-based, hybrid, and synthetic) and fidelity levels, with no statistically significant differences between trainee levels. Most studies had low to moderate overall risk of bias.
Conclusions:
This review indicates that SBT meaningfully accelerates technical skill acquisition and improves procedural efficiency in CABG anastomosis across trainee levels and simulator types. These findings support the integration of structured simulation into cardiothoracic surgery training curricula. Future research should evaluate long-term skill retention, transferability to real patient surgery, and cost-effectiveness to guide optimal implementation.
