Objective improvement with coronary anastomosis simulation training: meta-analysis

BACKGROUND: Coronary artery anastomosis training and assessment are vital for patient safety and for conferring a prognostic benefit. A systematic review and meta-analysis were performed to analyse the impact of simulation on coronary anastomosis proficiency in terms of time taken and skill score. METHODS: This review was conducted in accordance with PRISMA guidelines, searching PubMed, Embase and Cochrane databases on 10 October 2020, using the terms ‘Coronary anastomosis simulation’ or ‘vascular anastomosis simulation’ and ‘anastomosis simulation’. Studies included had objective measurement of scores of before and after simulation. Meta-analysis was performed using RevMan, version 5.4 (Cochrane Library). RESULTS: From a pool of 1687 articles, 12 articles evaluating the use of simulation in teaching coronary anastomosis were identified, with objective scores at baseline and after simulation. The 12 papers included 274 subjects. Data on 223 subjects could be extracted for analysis in performing coronary anastomosis in a simulated environment. Eight trials evaluated improvement in time and 12 trials evaluated performance using an objective evaluation score. In comparison with no formal simulation training, simulation was associated with improved skill in a five-point scale (standardized mean difference 1.68 (95 per cent c.i. 1.23 to 2.13; P < 0.001)) and time (mean difference 205.9 s (95 per cent c.i. 133.62 to 278.18; P < 0.001)) in trials included in the meta-analysis. Furthermore, novice cardiothoracic surgeons benefited more from simulation as regards time improvement compared with senior cardiothoracic surgeons (293 versus 120 s improvement; P = 0.003). Fidelity of simulator did not have a significant effect on rates of improvement. CONCLUSION: Simulation-based training in coronary anastomosis is associated with improved time efficiency and overall performance in comparison with no intervention. Further studies are necessary to determine the optimum timing of trainees progressing from simulation training to live operating.