Open Access

Svenja Deuchler, Clemens Wagner, Pankaj Singh, Michael Müller, Rami Al-Dwairi, Rachid Benjilali, Markus Schill, Hanns Ackermann, Dimitra Bon, Thomas Kohnen, Benjamin Schoene, Michael Janusz Koss, Frank H. Koch

• Purpose: To evaluate the efficacy of the virtual reality training simulator Eyesi to prepare surgeons for performing pars plana vitrectomies and its potential to predict the surgeons’ performance. Methods: In a preparation phase, four participating vitreoretinal surgeons performed repeated simulator training with predefined tasks. If a surgeon was assigned to perform a vitrectomy for the management of complex retinal detachment after a surgical break of at least 60 hours it was randomly decided whether a warmup training on the simulator was required (n = 9) or not (n = 12). Performance at the simulator was measured using the built-in scoring metrics. The surgical performance was determined by two blinded observers who analyzed the video-recorded interventions. One of them repeated the analysis to check for intra-observer consistency. The surgical performance of the interventions with and without simulator training was compared. In addition, for the surgeries with simulator training, the simulator performance was compared to the performance in the operating room. Results: Comparing each surgeon’s performance with and without warmup trainingshowed a significant effect of warmup training onto the final outcome in the operating room. For the surgeries that were preceeded by the warmup procedure, the performance at the simulator was compared with the operating room performance. We found that there is a significant relation. The governing factor of low scores in the simulator were iatrogenic retinal holes, bleedings and lens damage. Surgeons who caused minor damage in the simulation also performed well in the operating room. Conclusions: Despite the large variation of conditions, the effect of a warmup training as well as a relation between the performance at the simulator and in the operating room was found with statistical significance. Simulator training is able to serve as a warmup to increase the average performance.