Background Ileus is common after elective colorectal surgery, and is associated with increased adverse events and prolonged hospital stay. The aim was to assess the role of non‐steroidal anti‐inflammatory drugs (NSAIDs) for reducing ileus after surgery. Methods A prospective multicentre cohort study was delivered by an international, student‐ and trainee‐led collaborative group. Adult patients undergoing elective colorectal resection between January and April 2018 were included. The primary outcome was time to gastrointestinal recovery, measured using a composite measure of bowel function and tolerance to oral intake. The impact of NSAIDs was explored using Cox regression analyses, including the results of a centre‐specific survey of compliance to enhanced recovery principles. Secondary safety outcomes included anastomotic leak rate and acute kidney injury. Results A total of 4164 patients were included, with a median age of 68 (i.q.r. 57–75) years (54·9 per cent men). Some 1153 (27·7 per cent) received NSAIDs on postoperative days 1–3, of whom 1061 (92·0 per cent) received non‐selective cyclo‐oxygenase inhibitors. After adjustment for baseline differences, the mean time to gastrointestinal recovery did not differ significantly between patients who received NSAIDs and those who did not (4·6 versus 4·8 days; hazard ratio 1·04, 95 per cent c.i. 0·96 to 1·12; P = 0·360). There were no significant differences in anastomotic leak rate (5·4 versus 4·6 per cent; P = 0·349) or acute kidney injury (14·3 versus 13·8 per cent; P = 0·666) between the groups. Significantly fewer patients receiving NSAIDs required strong opioid analgesia (35·3 versus 56·7 per cent; P < 0·001). Conclusion NSAIDs did not reduce the time for gastrointestinal recovery after colorectal surgery, but they were safe and associated with reduced postoperative opioid requirement.

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Background Postoperative acute kidney injury (AKI) is a common complication of major gastrointestinal surgery with an impact on short- and long-term survival. No validated system for risk stratification exists for this patient group. This study aimed to validate externally a prognostic model for AKI after major gastrointestinal surgery in two multicentre cohort studies. Methods The Outcomes After Kidney injury in Surgery (OAKS) prognostic model was developed to predict risk of AKI in the 7 days after surgery using six routine datapoints (age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker). Validation was performed within two independent cohorts: a prospective multicentre, international study (‘IMAGINE’) of patients undergoing elective colorectal surgery (2018); and a retrospective regional cohort study (‘Tayside’) in major abdominal surgery (2011–2015). Multivariable logistic regression was used to predict risk of AKI, with multiple imputation used to account for data missing at random. Prognostic accuracy was assessed for patients at high risk (greater than 20 per cent) of postoperative AKI. Results In the validation cohorts, 12.9 per cent of patients (661 of 5106) in IMAGINE and 14.7 per cent (106 of 719 patients) in Tayside developed 7-day postoperative AKI. Using the OAKS model, 558 patients (9.6 per cent) were classified as high risk. Less than 10 per cent of patients classified as low-risk developed AKI in either cohort (negative predictive value greater than 0.9). Upon external validation, the OAKS model retained an area under the receiver operating characteristic (AUC) curve of range 0.655–0.681 (Tayside 95 per cent c.i. 0.596 to 0.714; IMAGINE 95 per cent c.i. 0.659 to 0.703), sensitivity values range 0.323–0.352 (IMAGINE 95 per cent c.i. 0.281 to 0.368; Tayside 95 per cent c.i. 0.253 to 0.461), and specificity range 0.881–0.890 (Tayside 95 per cent c.i. 0.853 to 0.905; IMAGINE 95 per cent c.i. 0.881 to 0.899). Conclusion The OAKS prognostic model can identify patients who are not at high risk of postoperative AKI after gastrointestinal surgery with high specificity. Presented to Association of Surgeons in Training (ASiT) International Conference 2018 (Edinburgh, UK), European Society of Coloproctology (ESCP) International Conference 2018 (Nice, France), SARS (Society of Academic and Research Surgery) 2020 (Virtual, UK).

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large multi-centre organization. Methods Anonymised clinical datasets from multiple radiation therapy centres within the organisation were collected, re-contoured and reviewed to commission the Smart Segmentation function and construct a custom breast model. Once the model was established, the performances of the model for various breast patients were analysed, and the contouring efficiency before and after the implementation of the automated segmentation function was compared. Results By using a heuristic approach and a deformable registration approach, the established breast model was proven to provide a contouring quality that was comparable to manual delineation. The average DICE score was above 0.7 (0.732), which was less than the common variation between different observers 2. The model contained a total of 17 structures, including both basic structures such as lungs and heart, and structures that were considered difficult to manually delineate such as brachial plexuses and different levels of lymph nodes. In addition, running the automated contouring tool on average took less than 8 minutes, providing marginal time savings in contouring. Conclusions Smart Segmentation® is shown to be an effective automated breast contouring tool that can decrease the time spent in manual contouring and reduce the variation between different observers, thereby improving both the efficiency and the quality of the contouring process in radiation therapy.