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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]

A robotic small bowel resection followed by Kono-S anastomosis was offered to the patient. Once we get close to finishing the posterior wall closing, we put in another stay stich that will be another 00 braided suture that is going to allow us to expose the area of the anastomosis that we are suturing at this moment. During the next step we will measure the diameter of the anastomosis, score the small bowel and confirm that the length of the scoring is around 7 cm. Scoring starts 1 cm to the end of the small bowel and finishes 7 cm proximal or distal to the starting point. [Extracted from the article]