Resecciones pulmonares anatómicas por vía robótica: análisis de la curva de aprendizaje

Abstract

IntroductionRobotic surgery has become a safe and effective approach for the treatment of pulmonary surgical pathology. However, the adoption of new surgical techniques requires the evaluation of the learning curve. The objective of this study is to analyze the learning curve of robotic anatomical lung resections. MethodsRetrospective analysis of all robotic anatomical lung resections performed by the same surgeon between June 2018 and March 2020. The learning curve was evaluated using CUSUM charts to estimate trend changes in surgical time, surgical failure and the occurrence of post-operative cardiorespiratory complications throughout the sequence of cases. ResultsThe study included a total of 73 cases. The median duration of all complications was 120min (interquartile range: 90-150min), the prevalence of surgical failure was 23.29%, while 4/73 patients had any postoperative cardiorespiratory complication. Based on the CUSUM analysis, the learning curve was divided into 3 different phases: phase i (from the first to the 14th intervention), phase ii (between the 15th and 30th intervention) and phase iii (from the 31st intervention). ConclusionsThe learning curve for robotic anatomical lung resections can be divided into 3 phases. The technical competence that guarantees satisfactory perioperative outcomes was achived in phase iii from the 31st intervention.