Rapid learning curve assessment in an ex vivo training system for microincisional glaucoma surgery

Abstract

Abstract Increasing prevalence and cost of glaucoma have increased the demand for surgeons well trained in newer, microincisional surgery. These procedures occur in a highly confined space, making them difficult to learn by observation or assistance alone as is currently done. We hypothesized that our ex vivo outflow model is sensitive enough to allow computing individual learning curves to quantify progress and refine techniques. Seven trainees performed nine trabectome-mediated ab interno trabeculectomies in pig eyes (n = 63). An expert surgeon rated the procedure using an Operating Room Score (ORS). The extent of outflow beds accessed was measured with canalograms. Data was fitted using mixed effect models. ORS reached a half-maximum on an asymptote after only 2.5 eyes. Surgical time decreased by 1.4 minutes per eye in a linear fashion. The ablation arc followed an asymptotic function with a half-maximum inflection point after 5.3 eyes. Canalograms revealed that this progress did not correlate well with improvement in outflow, suggesting instead that about 30 eyes are needed for true mastery. This inexpensive pig eye model provides a safe and effective microsurgical training model and allows objective quantification of outcomes for the first time.