Thorac Cardiovasc Surg 2019; 67(07): 573-577
DOI: 10.1055/s-0038-1639477
Original Thoracic
Georg Thieme Verlag KG Stuttgart · New York

Effectiveness of Robotic Lobectomy—Outcome and Learning Curve in a High Volume Center

Danjouma Housmanou Cheufou
1   Department of Thoracic Surgery, Universitat Duisburg-Essen Medizinische Fakultat, Essen, Germany
,
Khaled Mardanzai
1   Department of Thoracic Surgery, Universitat Duisburg-Essen Medizinische Fakultat, Essen, Germany
,
Till Ploenes
1   Department of Thoracic Surgery, Universitat Duisburg-Essen Medizinische Fakultat, Essen, Germany
,
Dirk Theegarten
1   Department of Thoracic Surgery, Universitat Duisburg-Essen Medizinische Fakultat, Essen, Germany
,
Georgios Stamatis
1   Department of Thoracic Surgery, Universitat Duisburg-Essen Medizinische Fakultat, Essen, Germany
,
Sandra Kampe
2   Department of Anaesthesiology, Universitat Duisburg-Essen Medizinische Fakultat, Essen, Germany
,
Clemens Aigner
1   Department of Thoracic Surgery, Universitat Duisburg-Essen Medizinische Fakultat, Essen, Germany
› Author Affiliations
Further Information

Publication History

07 October 2017

12 February 2018

Publication Date:
06 April 2018 (online)

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Abstract

Background Robotic surgery has been developed as a sophisticated tool to expand possibilities in minimal invasive surgery. The learning curve for this method is short in various surgical fields; however, limited data exist on the learning curve in robotic thoracic surgery.

Methods This study analyzes a single center experience of robotic lobectomies using a prospectively kept database. Perioperative data and outcome of patients during the learning curve were compared with patients operated with increased institutional experience. The learning curve was defined as the initial 20 lobectomies.

Results Sixty-four robotic lobectomies were performed between January 2014 and February 2017. Indications, preoperative lung functions, comorbidities, patient age, and tumor stage were comparable between patients operated during the learning curve and thereafter. The mean operative time could be significantly reduced after the learning curve (286 ± 86 vs. 211 ± 62 minutes; p = 0.0003). The conversion rate dropped from 4 of 20 (20%) during the learning curve to 2 of 44 (4.5%, p = 0.07) thereafter. Chest tube duration (4.3 ± 2.9 vs. 3.8 ± 2.1 days) and hospital stay (8.3 ± 3.4 vs. 7.9 ± 4.5 days) were not different in the two phases. The number of resected lymph nodes increased from 11.2 ± 6.8 to 13.9 ± 6.5 (p = 0.0797). Lymph node upstaging was achieved in 8 (12.9%) cases. Ninety-day mortality was 0%, and 2-year overall survival was 83%.

Conclusions Robotic thoracic surgery can be safely performed and trained with low complication rates and contributes to the extension of minimal invasive thoracic surgery. The initial learning curve in our experience is overcome after 20 cases. However, to become proficient in more advanced procedures and to further reduce operative time, additional training is required. Prospective studies are required to clearly determine the role of robotic surgery in comparison to the video-assisted thoracoscopic surgery (VATS) procedures.