Software supported robotic PCI in coronary arteries – comparison from the ROBO.pci trial

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Abstract Background Robotic percutaneous coronary interventions (rPCI) have proven to be efficient and safe. The robotics software has recently been updated and now allows precise and fully controlled navigation of devices and wires to fit the various morphologic conditions of coronary arteries and calcified segments. Objectives In the present study we aimed to compare the different robotic wiring modalities supported by the new software. Study design rPCI performed using the updated robotics software was compared with rPCI using the manually executed wire positioning. Lesion crossing was performed with each method under identical circumstances, crossing the same lesion and measuring the wire times. Measurements were started at the ostium of the guiding catheter and were stopped at a pre-defined individual coronary anatomical landmark. Results Eleven consecutive patients with 11 lesions were enrolled in this trial. The mean age of patients was 63±6 years with typical cardiovascular comorbidities and 54% (6/11) presented with three-vessel disease. All patients underwent PCI in an elective setting with stable chronic coronary syndrome. The majority of lesions were located in the LCX (45%, 5/11) followed by the LAD (27%, 3/11) and the RCA (27%, 3/11). All lesions were de novo ACC/AHA grade B2/C lesions, and the procedure was performed by experienced (high-volume) interventional cardiologists. The lesion crossing times were not significantly different (manual crossing 15.00 [IQR: 40] sec vs. rPCI without software support 18.00 [IQR: 18] sec vs. rPCI with software support 13.00 [IQR: 47] sec; p=n.s.). Summary rPCI without software support tends to be slower than rPCI with software support. There was no statistical significance. rPCI was found to be safe and feasible and the new software tends to reduced procedural time, which could reduce operators' health risks and improve patients' outcomes. Further randomized controlled trials are needed to evaluate the long-term benefits. Funding Acknowledgement Type of funding sources: None.

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