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Robotic anatomical lung resections: Analysis of the learning curve
M Teresa Gómez Hernández1, Marta Fuentes Gago1, Nuria Novoa Valentín1
1Departamento de Cirugía Torácica, Hospital Universitario de Salamanca, Salamanca, Spain.
Introduction:
Robotic 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.
Methods:
Retrospective 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.
Results:
The study included a total of 73 cases. The median duration of all complications was 120 min (interquartile range: 90-150 min), 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).
Conclusions:
The 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.
