Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Palliative pelvic exenteration: A systematic review of patient-centered outcomes

Objective: Palliative pelvic exenteration (PPE) is a technically complex operation with high morbidity and mortality rates, considered in patients with limited life expectancy. There is little evidence to guide practice. We performed a systematic review to evaluate the impact of PPE on symptom relief and quality of life (QoL). Methods: A systematic review was conducted according to the PRISMA guidelines using Ovid MEDLINE, EMBASe, and PubMed databases for studies reporting on outcomes of PPE for symptom relief or QoL. Descriptive statistics were used on pooled patient cohorts. Results: Twenty-three historical cohorts and case series were included, comprising 509 patients. No comparative studies were found. Most malignancies were of colorectal, gynaecological and urological origin. Common indications for PPE were pain, symptomatic fistula, bleeding, malodour, obstruction and pelvic sepsis. The pooled median postoperative morbidity rate was 53.6% (13\u2013100%), the median in-hospital mortality was 6.3% (0\u201366.7%), and median OS was 14 months (4\u201340 months). Some symptom relief was reported in a median of 79% (50\u2013100%) of the patients, although the magnitude of effect was poorly measured. Data for QoL measures were inconclusive. Five studies discouraged performing PPE in any patient, while 18 studies concluded that the procedure can be considered in highly selected patients. Conclusion: Available evidence on PPE is of low-quality. Morbidity and mortality rates are high with a short median OS interval. While some symptom relief may be afforded by this procedure, evidence for improvement in QoL is limited. A highly selective individualised approach is required to optimise the risk:benefit equation

Predicting outcomes of pelvic exenteration using machine learning

Aim: We aim to compare machine learning with neural network performance in predicting R0 resection (R0), length of stay > 14 days (LOS), major complication rates at 30 days postoperatively (COMP) and survival greater than 1 year (SURV) for patients having pelvic exenteration for locally advanced and recurrent rectal cancer. Method: A deep learning computer was built and the programming environment was established. The PelvEx Collaborative database was used which contains anonymized data on patients who underwent pelvic exenteration for locally advanced or locally recurrent colorectal cancer between 2004 and 2014. Logistic regression, a support vector machine and an artificial neural network (ANN) were trained. Twenty per cent of the data were used as a test set for calculating prediction accuracy for R0, LOS, COMP and SURV. Model performance was measured by plotting receiver operating characteristic (ROC) curves and calculating the area under the ROC curve (AUROC). Results: Machine learning models and ANNs were trained on 1147 cases. The AUROC for all outcome predictions ranged from 0.608 to 0.793 indicating modest to moderate predictive ability. The models performed best at predicting LOS > 14 days with an AUROC of 0.793 using preoperative and operative data. Visualized logistic regression model weights indicate a varying impact of variables on the outcome in question. Conclusion: This paper highlights the potential for predictive modelling of large international databases. Current data allow moderate predictive ability of both complex ANNs and more classic methods

Safety of hospital discharge before return of bowel function after elective colorectal surgery

Background: Ileus is common after colorectal surgery and is associated with an increased risk of postoperative complications. Identifying features of normal bowel recovery and the appropriateness for hospital discharge is challenging. This study explored the safety of hospital discharge before the return of bowel function. Methods: A prospective, multicentre cohort study was undertaken across an international collaborative network. Adult patients undergoing elective colorectal resection between January and April 2018 were included. The main outcome of interest was readmission to hospital within 30 days of surgery. The impact of discharge timing according to the return of bowel function was explored using multivariable regression analysis. Other outcomes were postoperative complications within 30 days of surgery, measured using the Clavien\u2013Dindo classification system. Results: A total of 3288 patients were included in the analysis, of whom 301 (9\ub72 per cent) were discharged before the return of bowel function. The median duration of hospital stay for patients discharged before and after return of bowel function was 5 (i.q.r. 4\u20137) and 7 (6\u20138) days respectively (P < 0\ub7001). There were no significant differences in rates of readmission between these groups (6\ub76 versus 8\ub70 per cent; P = 0\ub7499), and this remained the case after multivariable adjustment for baseline differences (odds ratio 0\ub790, 95 per cent c.i. 0\ub755 to 1\ub746; P = 0\ub7659). Rates of postoperative complications were also similar in those discharged before versus after return of bowel function (minor: 34\ub77 versus 39\ub75 per cent; major 3\ub73 versus 3\ub74 per cent; P = 0\ub7110). Conclusion: Discharge before return of bowel function after elective colorectal surgery appears to be safe in appropriately selected patients