The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

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

Abstract 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

High-order Boussinesq-type model for integrated nearshore dynamics

A two-dimensional high-order Boussinesq-type model was derived to simulate wave propagation and relevant processes in the nearshore zone. Because of its enhanced nonlinear character, the model can describe more accurately the amplitude dispersion compared to its weakly nonlinear counterpart. Extension to the surf zone was accomplished using the eddy-viscosity concept for simulating breaking waves. Swash-zone dynamics were simulated by applying a modified narrow-slot technique. Bottom friction and subgrid turbulent mixing were also incorporated. The model can estimate the wave-induced current field, including the undertow effect. The numerical model relied on a generalized multistep predictor-corrector scheme, and the waves were generated using the source function method. Both the one-horizontal-dimensional (1DH) and two-horizontal-dimensional (2DH) versions were validated against a variety of experimental tests, including regular and irregular wave propagation and breaking on plane beaches and submerged shoals. Breaking and run-up of a solitary wave were also modeled. Furthermore, a wave overtopping test was also included. Oblique long-crested irregular wave incidence and a test including a rip channel were simulated to check the model's performance. The agreement, in general, is satisfactory, and most of the nearshore phenomena were accurately reproduced

A Coastal Flood Early-Warning System Based on Offshore Sea State Forecasts and Artificial Neural Networks

An integrated methodological approach to the development of a coastal flood early-warning system is presented in this paper to improve societal preparedness for coastal flood events. The approach consists of two frameworks, namely the Hindcast Framework and the Forecast Framework. The aim of the former is to implement a suite of high-credibility numerical models and validate them according to past flooding events, while the latter takes advantage of these validated models and runs a plethora of scenarios representing distinct sea-state events to train an Artificial Neural Network (ANN) that is capable of predicting the impending coastal flood risks. The proposed approach was applied in the flood-prone coastal area of Rethymno in the Island of Crete in Greece. The performance of the developed ANN is good, given the complexity of the problem, accurately predicting the targeted coastal flood risks. It is capable of predicting such risks without requiring time-consuming numerical simulations; the ANN only requires the offshore wave characteristics (height, period and direction) and sea-water-level elevation, which can be obtained from open databases. The generic nature of the proposed methodological approach allows its application in numerous coastal regions

Boussinesq-type modeling of sediment transport and coastal morphology

A two horizontal dimensional compound model is developed to simulate coastal sediment transport and bed morphology evolution due to wave action. The wave module is a higher-order Boussinesq-type model. The bed load in the surf zone is computed from an advanced semi-empirical formula while the suspended load can be calculated through the solution of the advection-diffusion equation for the sediment or alternatively from a simplified formula. The estimation of the sediment transport in the swash zone is based on the ballistic theory. The unified sediment transport module is valid under combined waves and currents including the wave asymmetry and phase-lag effects. The bathymetry is updated through the sediment conservation equation and the morphological accelerator factor technique accounts for extended simulation time. The model is validated against a number of short-term tests in one horizontal dimension. The response is generally good with most of the morphological features being reproduced in the cross-shore direction. A comparison between various sediment transport formulae and a sensitivity analysis are also performed illustrating the need for inclusion of the phase-lag effects