Predictors of operative difficulty in robotic low anterior resection for rectal cancer. Academic Article uri icon

Overview

abstract

  • AIM: This study evaluates the relationship of tumour and anatomical features with operative difficulty in robotic low anterior resection performed by four experienced surgeons in a high-volume colorectal cancer practice. METHODS: Data from 382 patients who underwent robotic low anterior resection by four expert surgeons between January 2016 and June 2019 were included in the analysis. Operating time was used as a measure of operative difficulty. Univariate and multivariate mixed models were used to identify associations between baseline characteristics and operating time, with surgeon as a random effect, thereby controlling for variability in surgeon speed and proficiency. In an exploratory analysis, operative difficulty was defined as conversion to laparotomy, a positive margin or an incomplete mesorectum. RESULTS: Median operating time was 4.28 h (range 1.95-11.33 h) but varied by surgeon from 3.45 h (1.95-6.10 h) to 5.93 h (3.33-11.33 h) (P < 0.001). Predictors of longer operating time in multivariate analysis were male sex, higher body mass index, neoadjuvant radiotherapy, low tumour height, greater sacral height and larger mesorectal area at the S5 vertebral level. Conversion occurred in two cases (0.5%), and incomplete mesorectum and positive margins were found in nine (2.4%) and 19 (5.0%) patients, respectively. Neoadjuvant radiotherapy and larger pelvic outlet were the only characteristics associated with the exploratory measure of difficulty. CONCLUSION: Predicting operative difficulty based on easy to identify, preoperative radiological and clinical variables is feasible in robotic anterior resection.

publication date

  • June 3, 2022

Research

keywords

  • Laparoscopy
  • Proctectomy
  • Rectal Neoplasms
  • Robotic Surgical Procedures
  • Robotics

Identity

Scopus Document Identifier

  • 85132869070

Digital Object Identifier (DOI)

  • 10.1111/codi.16212

PubMed ID

  • 35656853