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Robotic versus traditional coronary artery bypass grafting (CABG): A dual-phase meta-analysis comparing human and
N Georginian1, C Wijeewera2, H T Tran3
1Macquarie University Hospital, 2 Technology Place Macquarie Park, Sydney, Australia.
Background:
Robotic-assisted coronary artery bypass grafting (CABG) is gaining attention as a viable alternative to traditional CABG with reported benefits secondary to reduced invasiveness of procedure. Despite this, advantages, the impact of robotic-assisted CABG on critical outcomes such as graft patency, mortality, and need for reintervention remains incompletely defined. The emergence of artificial intelligence (AI) based large language models (LLMs) promise the ability to rapidly deliver robust secondarily derived data, like that obtained from gold standard human meta-analyses. However, there is a lack of direct comparison between these modalities, preventing adoption of these tools in clinical practice.
Methods:
We conduct a dual-phase study, by first performing a rigorous, traditional human-led systematic review and meta-analysis comparing robotic-assisted CABG with traditional CABG with respect to graft patency, mortality, reintervention rates, and operative time. In the second phase, we compare outputs of flagship multimodal LLMs from five major vendors-OpenAI (GPT-4o), Anthropic (Claude Sonnet 4), xAI (Grok 3), Google (Gemini 2.5 Pro), and High-Flyer (DeepSeek-R1)-to the same clinical question, called via public, and domain specific API. Sensitivity analyses were performed excluding studies comparing robotic-assisted CABG with conventional minimally invasive direct CABG (MIDCAB) to address procedural heterogeneity.
Results:
Meta-analysis of 27 studies found no significant differences between robotic and conventional CABG in reintervention (OR 0.92, 95% CI 0.61-1.38), mortality (OR 0.65, 95% CI 0.38-1.13), or graft patency (P = 0.29). Sensitivity analysis excluding MIDCAB comparator studies did not materially alter these findings. Operative time analyses showed heterogeneous results: pooled estimates suggested shorter times with robotic CABG, but subgroup analyses revealed longer durations for multi-vessel procedures and shorter harvest times for single ITA grafts. Overall, robotic CABG demonstrated comparable outcomes to conventional surgery.
Conclusions:
Operative time findings were heterogeneous, with shorter durations observed in single-vessel procedures and longer operative times in multivessel robotic CABG. Domain-specific orchestration-such as that employed by CardioCanon-can substantially improve the clinical fidelity and interpretive quality of AI-generated evidence synthesis in cardiovascular surgery. Human oversight remains essential for robust use of AI and LLM in clinical research.
