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Thorac Cardiovasc Surg 2021; 69(06): 551-556
DOI: 10.1055/s-0039-1696952
Original Thoracic

Successful Sleeve Resection as a Marker for Proficiency for Robotic Pulmonary Resection

Tugba Cosgun
1   Department of Thoracic Surgery, Demiroglu Bilim University, Istanbul, Turkey
,
Erkan Kaba
1   Department of Thoracic Surgery, Demiroglu Bilim University, Istanbul, Turkey
,
Kemal Ayalp
2   Istanbul Florence Nightingale Hospital, Istanbul, Turkey
,
Alper Toker
2   Istanbul Florence Nightingale Hospital, Istanbul, Turkey
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Abstract

Background Robot technology is a revolutionary technique to overcome limitations of minimal invasive surgery. The proficiency level varies from study to study. We considered the first sleeve lobectomy as a benchmark procedure to evaluate the proficiency level.

Methods We retrospectively analyzed 197 patients who underwent robot-assisted thoracoscopic surgery (RATS) for primary lung cancer between December 2011 and May 2018. Patients were divided into two groups based on undergoing surgery earlier period (EP) or later period (LP) than the first sleeve lobectomy by RATS (May 25, 2015). The preoperative, operative, and short- and long-term postoperative outcomes were compared. Seven-year survival was also compared between two periods for T1N0 and T2N0 diseases.

Results Preoperative features were similar. The mean operative time was 166.8 ± 55.1 and 142.4 ± 43.9 minutes in EP and LP, respectively (p = 0.005). The mean number of dissected lymph nodes in LP was also significantly higher than that in EP (24.4 ± 9.4 vs. 20.8 ± 10.4, p = 0.035). The complication rate was significantly lower in LP (29/86 vs. 25/111, p = 0.048). The extended resection (ER) rate was significantly higher in LP (p = 0.023). The 7-year survival was comparable in EP and LP in both patients with T1N0 and T2N0 (p = 0.28 and p = 0.11, respectively).

Conclusion Perioperative outcomes, such as duration of surgery, number of dissected lymph nodes, complications, and ERs are favorable in patients who underwent surgeries after the first sleeve resection. The first sleeve lobectomy may be considered as the benchmark procedure for the proficiency level in RATS.

Keywords

lung cancer - learning curve - proficiency - robot-assisted thoracoscopic surgery

Authors' Contribution

Conception and design: T. Cosgun and A Toker; administrative support: T. Cosgun and E. Kaba; provision of study materials or patients: K. Ayalp and A. Toker; collection and assembly of data: T. Cosgun; data analysis and interpretation: T Cosgun; and article writing and final approval of article: all authors.




Publication History

Received: 23 April 2019

Accepted: 02 August 2019

Article published online:
15 September 2019

© 2019. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Owen RM, Force SD, Gal AA. et al. Routine intraoperative frozen section analysis of bronchial margins is of limited utility in lung cancer resection. Ann Thorac Surg 2013; 95 (06) 1859-1865 , discussion 1865–1866
    CrossrefPubMedGoogle Scholar
  • 2 Tomaszek SC, Kim Y, Cassivi SD. et al. Bronchial resection margin length and clinical outcome in non-small cell lung cancer. Eur J Cardiothorac Surg 2011; 40 (05) 1151-1156
    PubMedGoogle Scholar
  • 3 Spaggiari L, Tessitore A, Casiraghi M. et al. Survival after extended resection for mediastinal advanced lung cancer: lessons learned on 167 consecutive cases. Ann Thorac Surg 2013; 95 (05) 1717-1725
    CrossrefPubMedGoogle Scholar
  • 4 Wright TP. Factors affecting the cost of airplanes. J Aeronaut Sci 1936; 3: 122-128
    Google Scholar
  • 5 Yao F, Wang J, Yao J, Hang F, Cao S, Cao Y. Video-assisted thoracic surgical lobectomy for lung cancer: description of a learning curve. J Laparoendosc Adv Surg Tech A 2017; 27 (07) 696-703
    CrossrefPubMedGoogle Scholar
  • 6 Maruthappu M, Duclos A, Orgill D, Carty MJ. A monitoring tool for performance improvement in plastic surgery at the individual level. Plast Reconstr Surg 2013; 131 (05) 702e-710e
    CrossrefPubMedGoogle Scholar
  • 7 Dawe SR, Windsor JA, Broeders JA, Cregan PC, Hewett PJ, Maddern GJ. A systematic review of surgical skills transfer after simulation-based training: laparoscopic cholecystectomy and endoscopy. Ann Surg 2014; 259 (02) 236-248
    CrossrefPubMedGoogle Scholar
  • 8 Maruthappu M, Duclos A, Lipsitz SR, Orgill D, Carty MJ. Surgical learning curves and operative efficiency: a cross-specialty observational study. BMJ Open 2015; 5 (03) e006679
    CrossrefPubMedGoogle Scholar
  • 9 Li X, Wang J, Ferguson MK. Competence versus mastery: the time course for developing proficiency in video-assisted thoracoscopic lobectomy. J Thorac Cardiovasc Surg 2014; 147 (04) 1150-1154
    CrossrefPubMedGoogle Scholar
  • 10 Dufourq N, Nicole Goldstein L, Botha M. Competence in performing emergency skills: how good do doctors really think they are?. Afr J Emerg Med 2017; 7 (04) 151-156
    CrossrefPubMedGoogle Scholar
  • 11 Toker A, Tanju S, Ziyade S, Kaya S, Dilege S. Learning curve in videothoracoscopic thymectomy: how many operations and in which situations?. Eur J Cardiothorac Surg 2008; 34 (01) 155-158
    CrossrefPubMedGoogle Scholar
  • 12 Zhao H, Bu L, Yang F, Li J, Li Y, Wang J. Video-assisted thoracoscopic surgery lobectomy for lung cancer: the learning curve. World J Surg 2010; 34 (10) 2368-2372
    CrossrefPubMedGoogle Scholar
  • 13 Bilgic E, Watanabe Y, Nepomnayshy D. et al; Simulation Committee of the Association for Surgical Education. Multicenter proficiency benchmarks for advanced laparoscopic suturing tasks. Am J Surg 2017; 213 (02) 217-221
    CrossrefPubMedGoogle Scholar
  • 14 Lin MW, Kuo SW, Yang SM, Lee JM. Robotic-assisted thoracoscopic sleeve lobectomy for locally advanced lung cancer. J Thorac Dis 2016; 8 (07) 1747-1752
    CrossrefPubMedGoogle Scholar
  • 15 Dindo D, Demartines N, Clavien PA. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg 2004; 240 (02) 205-213
    CrossrefPubMedGoogle Scholar
  • 16 Toker A, Kaba E, Ayalp K, Özyurtkan MO. Robotic lung resections: video-assisted thoracic surgery based approach. J Vis Surg 2017; 3: 15
    CrossrefPubMedGoogle Scholar
  • 17 Mazzella A, Olland A, Falcoz PE, Renaud S, Santelmo N, Massard G. Video-assisted thoracoscopic lobectomy: which is the learning curve of an experienced consultant?. J Thorac Dis 2016; 8 (09) 2444-2453
    CrossrefPubMedGoogle Scholar
  • 18 Osugi H, Takemura M, Higashino M. et al. Learning curve of video-assisted thoracoscopic esophagectomy and extensive lymphadenectomy for squamous cell cancer of the thoracic esophagus and results. Surg Endosc 2003; 17 (03) 515-519
    CrossrefPubMedGoogle Scholar
  • 19 Melfi FM, Mussi A. Robotically assisted lobectomy: learning curve and complications. Thorac Surg Clin 2008; 18 (03) 289-295 , vi–vii
    CrossrefPubMedGoogle Scholar
  • 20 Veronesi G, Galetta D, Maisonneuve P. et al. Four-arm robotic lobectomy for the treatment of early-stage lung cancer. J Thorac Cardiovasc Surg 2010; 140 (01) 19-25
    CrossrefPubMedGoogle Scholar
  • 21 Özyurtkan MO, Kaba E, Toker A. What happens while learning robotic lobectomy for lung cancer?. J Vis Surg 2017; 3: 27
    CrossrefPubMedGoogle Scholar
  • 22 Toker A, Özyurtkan MO, Kaba E, Ayalp K, Demirhan Ö, Uyumaz E. Robotic anatomic lung resections: the initial experience and description of learning in 102 cases. Surg Endosc 2016; 30 (02) 676-683
    CrossrefPubMedGoogle Scholar
  • 23 Melfi FM, Fanucchi O, Davini F, Mussi A. VATS-based approach for robotic lobectomy. Thorac Surg Clin 2014; 24 (02) 143-149 , v
    CrossrefPubMedGoogle Scholar
  • 24 Cosgun T, Kaba E, Ayalp K, Alomari MR, Toker A. Bronchial sleeve anastomosis and primary closures with the da Vinci system: an advanced minimally invasive technique. Video-assist Thorac Surg 2017; 2: 49 . Doi: 10.21037/vats.2017.08.06
    CrossrefPubMedGoogle Scholar
  • 25 Zhao Y, Jiao W, Ren X. et al. Left lower lobe sleeve lobectomy for lung cancer using the Da Vinci surgical system. J Cardiothorac Surg 2016; 11 (01) 59
    CrossrefPubMedGoogle Scholar
  • 26 Meyer M, Gharagozloo F, Tempesta B, Margolis M, Strother E, Christenson D. The learning curve of robotic lobectomy. Int J Med Robot 2012; 8 (04) 448-452
    CrossrefPubMedGoogle Scholar
  • 27 Cheufou DH, Mardanzai K, Ploenes T. et al. Effectiveness of robotic lobectomy-outcome and learning curve in a high volume center. Thorac Cardiovasc Surg 2018. Doi: 10.1055/s-0038-1639477
    Google Scholar
  • 28 Seder CW, Cassivi SD, Wigle DA. Navigating the pathway to robotic competency in general thoracic surgery. Innovations (Phila) 2013; 8 (03) 184-189
    CrossrefPubMedGoogle Scholar