RT Journal Article
SR Electronic
T1 Prospective, randomised and blinded comparison of proficiency-based progression full-physics virtual reality simulator training versus invasive vascular experience for learning carotid artery angiography by very experienced operators
JF BMJ Simulation and Technology Enhanced Learning
JO BMJ STEL
FD The Association for Simulated Practice in Healthcare
SP 1
OP 5
DO 10.1136/bmjstel-2015-000090
VO 2
IS 1
A1 Cates, Christopher U
A1 Lönn, Lars
A1 Gallagher, Anthony G
YR 2016
UL http://stel.bmj.com/content/2/1/1.abstract
AB Introduction We assessed the transfer of training (ToT) of virtual reality simulation training compared to invasive vascular experience training for carotid artery angiography (CA) for highly experienced interventionists but new to carotid procedures.Methods Prospective, randomised and blinded.Setting Catheterisation and skills laboratories in the USA.Participants Experienced (mean volume=15 000 cases) interventional cardiologists (n=12) were randomised to train on virtual reality (VR) simulation to a quantitatively defined level of proficiency or to a traditional supervised in vivo patient case training.Outcome measures The observed performance differences in performing a CA between two matched groups were then blindly assessed using predefined metrics of performance.Results Experienced interventional cardiologists trained on the VR simulator performed significantly better than their equally experienced controls showing a significantly lower rate of objectively assessed intraoperative errors in CA. Performance showed 17–49% ToT from the VR to the in vivo index case.Discussion This is the first prospective, randomised and blinded clinical study to report that VR simulation training transfers improved procedural skills to clinical performance on live patients for experienced interventionists. This study, for the first time, demonstrates that VR simulation offers a powerful, safe and effective platform for training interventional skills for highly experienced interventionists with the greatest impact on procedural error reduction.