Abstract

Cumulative sum (CUSUM) analysis, first developed to assess industrial quality control, was then used to monitor cardiac surgery performance more than 10 years ago. This analysis may be more sensitive than the standard statistical tools to analyse surgical results. The aim of this study is to assess a single surgeon's learning curve with right anterior minithoracotomy (RAMT) for aortic valve replacement (AVR) using risk-adjusted CUSUM curves and to compare the short- and medium-term results of these patients with a propensity-matched cohort of patients who had standard AVR (SAVR). The first 100 patients who underwent RAMT by a single surgeon were analysed, using risk-adjusted CUSUM curves. Predicted risks of failure for individual patients were derived from our institutional database, using logistic regression modelling. Perioperative death or one or more of 10 adverse events constituted failure. Finally, RAMT patients were matched to 100 SAVR patients operated by the same surgeon in the same period, using a propensity score analysis. The author's RAMT experience was associated with a low risk of cumulative failures from the outset, and no learning curve effect was observed. A cluster of surgical failure was individuated at the end of the CUSUM curve (between patients 90 and 100). The predicted risk of failure for the study population constantly increased over the time. After propensity score matching, no baseline differences were observed between RAMT and SAVR patients. The mortality rate was similar between groups (P = 0.8). However, the RAMT group had a lower need for mechanical-assisted ventilation (P = 0.02), transfusion requirements (P = 0.001), post-operative atrial fibrillation (P = 0.01) and post-operative intensive care unit and hospital stay (P = 0.001). Three-year survival was similar between groups (RAMT 94.5% vs. SAVR 92.8%). AVR can be safely performed through an RAMT with results comparable with the standard sternotomy technique. Patients undergoing this technique are not exposed to an increased operative risk also during the surgeon's initial experience. CUSUM analysis is a valuable tool to assess the learning curve of new surgical techniques and to implement continuous performance monitoring.

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