BACKGROUND: Minimally invasive techniques to treat great saphenous varicose veins include ultrasound-guided foam sclerotherapy (USGFS), radiofrequency ablation (RFA) and endovenous laser therapy (EVLT). Compared with conventional surgery (high ligation and stripping (HL/S)), proposed benefits include fewer complications, quicker return to work, improved quality of life (QoL) scores, reduced need for general anaesthesia and equivalent recurrence rates. The full text is available from: http://dx.doi.org/10.1002/14651858. CD005624.pub2.The abstract is also available in the Portuguese, French and Spanish languages from: http://summaries.cochrane.org/pt/CD005624/ablacaoendovenosa-por-radiofrequencia-e-laser-e-escleroterapia-com-espumaversus-cirurgia-convencional-para-o-tratamento-de-varizes. COMMENTSWith the advent of new techniques for treating varicose veins, many studies are needed in order to compare the new procedures with the gold-standard treatment, i.e. conventional surgery with removal of either the great or the small saphenous vein and excision of tributaries presenting insufficiency. In this review, many data were flawed or did not lead to a conclusion that would be capable of showing significant details regarding the best technique. It can be expected that treatments with laser, radiofrequency or foam sclerotherapy may lead to recanalization of the treated veins, since these do not remove the veins but only stop the flow of blood through the lumen. Recurrence of varicose veins within four months suggests that there was an error in marking out the varicose veins before the operation and failure of the planned removal of the saphenous vein or the dilated tributaries. Some technical details of the surgery may differ, such as segmental removal of the great saphenous vein under general anesthesia. This procedure is not customary in many centers, and complete removal of the saphenous vein with intrathecal or regional blockade is preferred. Other extremely necessary data include comparison of the costs of the fiber laser and radiofrequency equipment, costs of procedures and costs of hospitalization when necessary.

No abstract

Social deprivation is significantly associated with postoperative length of stay and survival in patients undergoing pelvic exenteration for primary rectal cancer.

No abstract

No abstract

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.

Background The multidisciplinary perioperative and anaesthetic management of patients undergoing pelvic exenteration is essential for good surgical outcomes. No clear guidelines have been established, and there is wide variation in clinical practice internationally. This consensus statement consolidates clinical experience and best practice collectively, and systematically addresses key domains in the perioperative and anaesthetic management. Methods The modified Delphi methodology was used to achieve consensus from the PelvEx Collaborative. The process included one round of online questionnaire involving controlled feedback and structured participant response, two rounds of editing, and one round of web-based voting. It was held from December 2019 to February 2020. Consensus was defined as more than 80 per cent agreement, whereas less than 80 per cent agreement indicated low consensus. Results The final consensus document contained 47 voted statements, across six key domains of perioperative and anaesthetic management in pelvic exenteration, comprising preoperative assessment and preparation, anaesthetic considerations, perioperative management, anticipating possible massive haemorrhage, stress response and postoperative critical care, and pain management. Consensus recommendations were developed, based on consensus agreement achieved on 34 statements. Conclusion The perioperative and anaesthetic management of patients undergoing pelvic exenteration is best accomplished by a dedicated multidisciplinary team with relevant domain expertise in the setting of a specialized tertiary unit. This consensus statement has addressed key domains within the framework of current perioperative and anaesthetic management among patients undergoing pelvic exenteration, with an international perspective, to guide clinical practice, and has outlined areas for future clinical research.

No abstract