Search

For T4 rectal tumours and local recurrences (LR) of rectal cancer, a radical resection beyond TME, sometimes by multi-visceral resection, is important to obtain safe margins and improve survival. The use of the laparoscopic approach (LA) for these cases is still controversial and associated with a high rate of conversion. However, robotic surgery might offer some advantages that can overcome some of the limitations of LA. Therefore, we aimed to analyse the postoperative outcomes and medium-term oncological results of robotic surgery for locally advanced rectal cancer (pathological T4) and LR. A retrospective analysis was performed including patients who had undergone robotic rectal resection in a single institution over an 11-year period, and had a T4 tumour confirmed in the pathological report. Primary endpoint was to analyse postoperative complications (30-day) and the rate of conversion. Secondary endpoints include pathological assessment of the quality of the specimen, local recurrence and survival [2-year disease-free survival (DFS) and overall survival (OS)]. A total of 41 patients were analysed, including a total of 24 patients (60%) that required a multivisceral resection. The median distance from the tumour to the anorectal junction was 7 (4–12) cm. Conversion to open surgery was necessary in 2 cases (5%). The overall morbidity rate was 78% (n = 32), with 37% of major complications, most of them urinary (n = 7). Median length of hospital stay (LOS) was 13 (7–27) days. The 30-day mortality rate was 7% (n = 3). An R0 resection was achieved in 85.4% of the cases (n = 35) due to 6 cases of the positive circumferential resection margin. 2-year disease-free survival (DFS) and overall survival (OS) for the T4 tumours were 72% and 85%, respectively. There were 8 cases of local recurrence (22.2%); 6 of them met the selection criteria for salvage surgery. Robotic surgery for locally advanced T4 rectal cancer and multi-visceral resections is safe and feasible, with a low rate of conversion and an acceptable rate of postoperative morbidity in this subgroup of patients. Oncological results have shown to be comparable with the laparoscopic series published, preserving a good quality of the resected specimen. However, comparative studies and a longer follow-up period is needed to confirm the oncologic findings and to support the general adoption of the robotic system for these complex interventions. [ABSTRACT FROM AUTHOR]

Aim: Predicting intra-abdominal infections (IAI) after colorectal surgery by means of clinical signs is challenging. A naïve logistic regression modeling approach has some limitations, for which reason we study two potential alternatives: the use of Bayesian networks, and that of logistic regression model. Methods: Data from patients that had undergone colorectal procedures between 2010 and 2017 were used. The dataset was split into two subsets: (i) that for training the models and (ii) that for testing them. The predictive ability of the models proposed was tested (i) by comparing the ROC curves from days 1 and 3 with all the subjects in the test set and (ii) by studying the evolution of the abovementioned predictive ability from day 1 to day 5. Results: In day 3, the predictive ability of the logistic regression model achieved an AUC of 0.812, 95% CI = (0.746, 0.877), whereas that of the Bayesian network was 0.768, 95% CI = (0.695, 0.840), with a p-value for their comparison of 0.097. The ability of the Bayesian network model to predict IAI does present significant difference in predictive ability from days 3 to 5: AUC(Day 3) = 0.761, 95% CI = (0.680, 0.841) and AUC(Day 5) = 0.837, 95% CI = (0.769, 0.904), with a p-value for their comparison of 0.006. Conclusions: Whereas at postoperative day 3, a logistic regression model with imputed data should be used to predict IAI; at day 5, when the predictive ability is almost identical, the Bayesian network model should be used. [ABSTRACT FROM AUTHOR]