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Surgery. 2019 Feb;165(2):450-454. doi: 10.1016/j.surg.2018.06.011. Epub 2018 Jul 27.

Defining the learning curve in robot-assisted thoracoscopic lobectomy.

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Section of Thoracic Surgery, Yale School of Medicine, New Haven, Connecticut. Electronic address:
Section of Thoracic Surgery, Yale School of Medicine, New Haven, Connecticut.
Yale School of Public Health, New Haven, Connecticut.
Division of Thoracic Surgery, Keck School of Medicine, University of Southern California, Los Angeles, California.



Robot-assisted thoracoscopic lobectomy has been shown to be a safe approach to pulmonary lobectomy. This study sought to define, mathematically, the learning curve for RATS lobectomy.


Patients undergoing robot-assisted thoracoscopic lobectomy at a single institution from 2010 through 2016 were considered. Covariates included patient demographics, comorbidities, operating time, length of stay, estimated blood loss, and postoperative complications. A cumulative sum analysis of operating time was performed to define the learning curve.


A total of 101 patients were included. Three distinct phases of the learning curve were identified: cases 1-22, cases 23-63, and cases 64-101. There was a statistically significant difference in operating time and estimated blood loss between phases 1 and 2 (P < .05, P = .016, respectively) and between phases 1 and 3 (P < .05, P = .006, respectively). There was no statistically significant difference in comorbidities, chest tube duration, length of stay, postoperative complications, or conversion rate across the learning curve.


Based on operating time, the learning curve for robot-assisted thoracoscopic lobectomy is 22 cases, with mastery achieved after 63 cases. No differences in length of stay, chest tube duration, conversion rate, or complication rate were observed in the learning curve. Other factors not measured in this study may play a role in the learning process and warrant further study.


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