Literature DB >> 32232680

A review of clinical and oncological outcomes following the introduction of the first robotic colorectal surgery programme to a university teaching hospital in Ireland using a dual console training platform.

Christina A Fleming1, Daniel Westby2, Mohammad Fahad Ullah2, Helen M Mohan2, Rishabh Sehgal2, Jarlath C Bolger2, Donal P O'Leary2, Emma McNamara2, Grzegorz Korpanty3, Mazen El Bassiouni4, Eoghan Condon2, John Calvin Coffey2,5, Colin Peirce2,5.   

Abstract

Robotic-assisted surgery is evolving, with improving clinical and cancer outcomes. The aim of this study was to present the clinical and cancer outcomes of patients undergoing robotic-assisted colorectal surgery (RAS-CR) at University Hospital Limerick (UHL) since its introduction to the 100th case, using the daVinci Xi dual-console surgical system. The RAS-CR programme at UHL commenced in June 2016 and the 100th case was performed in July 2019. All patient-related data were recorded prospectively during the perioperative period by the RAS-CR team. Statistical analysis was performed using SPSS, version 22. One hundred patients were operated on, comprising of 47 males and 53 females. The median age was 65 years (IQR 13.0; range 25-84) with 69% of cases performed for cancer [N = 39 rectal cancer, N = 30 colon cancer], 20% for benign disease and 11% for dysplasia. Median length of stay for cancer operations was 6.5 days for colon cancer cases (5.0 days when cases with complications were excluded) and 7.0 days for rectal cancer cases. Median operative time was 255 mins (IQR 130 min; all cases), median docking time was 33 mins (IQR 20 mins) and median intra-operative blood loss was 80 ml (IQR 70 ml). Thirty-one patients developed a post-operative complication (5% anastomotic leak; 13% SSI). In cancer cases, median nodal harvest was 14 nodes (IQR10) and an R0 resection was achieved in 98.6% (n = 68) of cancer cases. Three patients (4.3%) developed metastatic disease at a median interval of 16.5 months. Clinical and operative outcomes remained stable over time from case 1 to 100. Structured introduction of a RAS-CR programme with appropriate governance and continuous audit results in favourable clinical and cancer outcomes and provides an excellent training opportunity for surgical residents.

Entities:  

Keywords:  Colorectal surgery; Dual console; Robotic surgery; Surgical outcomes; daVinci surgical system

Year:  2020        PMID: 32232680     DOI: 10.1007/s11701-020-01073-8

Source DB:  PubMed          Journal:  J Robot Surg        ISSN: 1863-2483


  6 in total

1.  Initial Experience in Rectal Cancer Surgery for the Next Generation of Robotic Surgeons Trained in a Dual Console System.

Authors:  Manabu Yamamoto; Keigo Ashida; Kazushi Hara; Ken Sugezawa; Chihiro Uejima; Akimitsu Tanio; Yuji Shishido; Kozo Miyatani; Takehiko Hanaki; Kyoichi Kihara; Tomoyuki Matsunaga; Naruo Tokuyasu; Teruhisa Sakamoto; Yoshiyuki Fujiwara
Journal:  Yonago Acta Med       Date:  2021-06-23       Impact factor: 1.641

Review 2.  Operating on the Mesentery in Robotic Colonic Surgery-General Techniques.

Authors:  Jonathan Coulter; Colin Peirce
Journal:  Clin Colon Rectal Surg       Date:  2022-04-13

Review 3.  Teaching and Training Surgeons in Robotic Colorectal Surgery.

Authors:  Mark K Soliman; Alison J Tammany
Journal:  Clin Colon Rectal Surg       Date:  2021-09-03

4.  Attitudes and access of Irish general surgery trainees to robotic surgical training.

Authors:  Lauren V O'Connell; Cathal Hayes; Mohamed Ismail; Diarmuid S O'Ríordáin; Adnan Hafeez
Journal:  Surg Open Sci       Date:  2022-03-30

5.  Robotic versus laparoscopic right hemicolectomy: a case-matched study.

Authors:  Enda Hannan; Gerard Feeney; Mohammad Fahad Ullah; Claire Ryan; Emma McNamara; David Waldron; Eoghan Condon; John Calvin Coffey; Colin Peirce
Journal:  J Robot Surg       Date:  2021-08-02

6.  Robotic colorectal surgery in elderly patients: A single-centre experience.

Authors:  Enda Hannan; Gerard Feeney; Mohammad Fahad Ullah; Eoghan Condon; John Calvin Coffey; Colin Peirce
Journal:  Int J Med Robot       Date:  2022-06-26       Impact factor: 2.483

  6 in total

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