Background: Conventional percutaneous coronary intervention (CV-PCI) remains a standard treatment approach for coronary artery disease (CAD); however, robotic PCI (RB-PCI) is gaining attention due to possible radiation reduction.
Objectives: This meta-analysis aims to compare periprocedural outcomes of RB-PCI with those of CV-PCI using a Bayesian framework.
Methods: A comprehensive literature search was conducted across multiple databases, including PubMed, Scopus, and Cochrane Library, to identify studies comparing RB-PCI and CV-PCI. A Bayesian non-informative random-effects model was applied to synthesize the data, providing posterior estimates with credible intervals (Crl).
Results: A total of ten studies and one report encompassing 3587 cases (RB-PCI and CV-PCI) were included. No significant differences were observed between RB-PCI and CV-PCI in terms of procedure time (MD 5.99; 95 % Crl -3.44 to 15.40), fluoroscopy time (MD -0.03; 95 % Crl -2.22 to 2.05), contrast volume (MD -5.87; 95 % CrI -17.85 to 6.55), or dose area product (MD -786.96; 95 % Crl -2374.70 to 773.10). Additionally, there was no significant difference in complications.
Conclusion: This Bayesian meta-analysis indicates that RB-PCI offers procedural efficiency and clinical outcomes comparable to those of CV-PCI, with no significant differences in key procedural parameters. The outcomes of this synthesis may question the cost-effectiveness of this technology in the management of CAD, as the benefits of RB-PCI are limited to radiation reduction. Lack of high-quality randomized trials leads to lower certainty of current evidence.
Keywords: Bayesian statistics; CorPath GRX; Coronary artery disease; Percutaneous coronary intervention.
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