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Robotic lobectomy: flattening the learning curve.
Jonathan M Hernandez1,2, Leigh Ann Humphries3, W Brent Keeling3,4
1Division of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, FOB-2, Tampa, FL, 33612, USA. Jonathan.Hernandez@Moffitt.org.
Journal of Robotic Surgery
|September 18, 2016
Summary
Robotic pulmonary resection can be efficient for experienced surgeons. Specific techniques and patient selection may flatten the learning curve for robotic lobectomy, reducing complications and hospital stays.
Area of Science:
- Thoracic Surgery
- Minimally Invasive Surgery
- Robotic Surgery
Background:
- Robotic pulmonary resection is perceived to have a steep learning curve.
- Institutions aim to minimize complications, operative times, and hospital stays with robotic surgery.
Purpose of the Study:
- To evaluate outcomes of robotic lobectomy using specific techniques.
- To assess if specialized robotic approaches can mitigate the learning curve in pulmonary resection.
Main Methods:
- Retrospective review of 20 patients undergoing robotic lobectomy.
- Utilized single docking, innovative retraction, and single interspace port placement.
- Focused on techniques analogous to open procedures.
Main Results:
- Mean operative time was 203 ± 53 minutes; median hospital stay was 3 days.
- Complication rate was 20% (atelectasis, myocardial infarction, atrial fibrillation); no fatalities.
- Two conversions to open procedures were necessary.
Conclusions:
- Robotic pulmonary resection outcomes can be comparable to established programs.
- Experienced surgeons may flatten the learning curve with appropriate patient selection and technique.
- Robotic lobectomy offers a viable minimally invasive option for lung cancer resection.
