Predicting Risk of Post-Operative Morbidity and Mortality following Gynaecological Oncology Surgery (PROMEGO) : A Global Gynaecological Oncology Surgical Outcomes Collaborative Led Study

Acknowledgments We acknowledge support provided by a number of stakeholders, including GO SOAR collaborators and the University of Aberdeen. Conflicts of Interest F.G. declares funding from the NHS Grampian Endowment Fund, Medtronic, Karl Storz, the British Gynaecological Cancer Society outside of this work, and an honorarium from Astra Zeneca. M.I.K. declares funding in the field of artificial intelligence, provided by the Analytical Center for the Government of the Russian Federation, in accordance with the subsidy agreement (agreement identifier 000000D730321P5Q0002) and the agreement with the Ivannikov Institute for System Programming of the Russian Academy of Sciences dated 2 November 2021, No. 70-2021-00142. O.B. declares funding from Barts Charity (G-001522). All other authors declare no conflicts of interest.Peer reviewe

Modulating Meltpool Dynamics and Microstructure using Thermoelectric Magnetohydrodynamics in Additive Manufacturing

Meltpool modulation in Selective Laser Remelting Additive Manufacturing via an oscillating magnetic field generates Thermoelectric Magnetohydrodynamics (TEMHD) flow. Numerical predictions show that the resulting microstructure can be significantly altered. A multi-scale numerical model captures the meso-scale melt pool dynamics coupled to microscale solidification showing the microstructure evolution and solute redistribution. The results highlight the complex interaction of the various physical phenomena and also show the method's potential to disrupt the epitaxial growth defect. The model predictions are supported by preliminary experimental results that demonstrate the dependency of the melt pool depth on magnetic field orientation. The results highlight how a time-dependent field has the potential to provide an independent control mechanism to tailor microstructures

Towards a design process for computer-aided biomimetics

Computer-Aided Biomimetics (CAB) tools aim to support the integration of relevant biological knowledge into biomimetic problem-solving processes. Specific steps of biomimetic processes that require support include the identification, selection and abstraction of relevant biological analogies. Existing CAB tools usually aim to support these steps by describing biological systems in terms of functions, although engineering functions do not map naturally to biological functions. Consequentially, the resulting static, functional view provides an incomplete understanding of biological processes, which are dynamic, cyclic and self-organizing. This paper proposes an alternative approach that revolves around the concept of trade-offs. The aim is to include the biological context, such as environmental characteristics, that may provide information crucial to the transfer of biological information to an engineering application. The proposed design process is exemplified by an illustrative case study

Modulating meltpool dynamics and microstructure using thermoelectric magnetohydrodynamics in additive manufacturing

Meltpool modulation in Selective Laser Remelting Additive Manufacturing via an oscillating magnetic field generates Thermoelectric Magnetohydrodynamics (TEMHD) flow. Numerical predictions show that the resulting microstructure can be significantly altered. A multi-scale numerical model captures the meso-scale melt pool dynamics coupled to microscale solidification showing the microstructure evolution and solute redistribution. The results highlight the complex interaction of the various physical phenomena and also show the method’s potential to disrupt the epitaxial growth defect. The model predictions are supported by preliminary experimental results that demonstrate the dependency of the melt pool depth on magnetic field orientation. The results highlight how a time-dependent field has the potential to provide an independent control mechanism to tailor microstructures

Improving risk prediction model quality in the critically ill:data linkage study

Background: A previous National Institute for Health and Care Research study [Harrison DA, Ferrando-Vivas P, Shahin J, Rowan KM. Ensuring comparisons of health-care providers are fair: development and validation of risk prediction models for critically ill patients. Health Serv Deliv Res 2015;3(41)] identified the need for more research to understand risk factors and consequences of critical care and subsequent outcomes. Objectives: First, to improve risk models for adult general critical care by developing models for mortality at fixed time points and time-to-event outcomes, end-stage renal disease, type 2 diabetes, health-care utilisation and costs. Second, to improve risk models for cardiothoracic critical care by enhancing risk factor data and developing models for longer-term mortality. Third, to improve risk models for in-hospital cardiac arrest by enhancing risk factor data and developing models for longer-term mortality and critical care utilisation. Design: Risk modelling study linking existing data. Setting: NHS adult critical care units and acute hospitals in England. Participants: Patients admitted to an adult critical care unit or experiencing an in-hospital cardiac arrest. Interventions: None. Main outcome measures: Mortality at hospital discharge, 30 days, 90 days and 1 year following critical care unit admission; mortality at 1 year following discharge from acute hospital; new diagnosis of end-stage renal disease or type 2 diabetes; hospital resource use and costs; return of spontaneous circulation sustained for > 20 minutes; survival to hospital discharge and 1 year; and length of stay in critical care following in-hospital cardiac arrest. Data sources: Case Mix Programme, National Cardiac Arrest Audit, UK Renal Registry, National Diabetes Audit, National Adult Cardiac Surgery Audit, Hospital Episode Statistics and Office for National Statistics. Results: Data were linked for 965,576 critical care admissions between 1 April 2009 and 31 March 2016, and 83,939 in-hospital cardiac arrests between 1 April 2011 and 31 March 2016. For admissions to adult critical care units, models for 30-day mortality had similar predictors and performance to those for hospital mortality and did not reduce heterogeneity. Models for longer-term outcomes reflected increasing importance of chronic over acute predictors. New models for end-stage renal disease and diabetes will allow benchmarking of critical care units against these important outcomes and identification of patients requiring enhanced follow-up. The strongest predictors of health-care costs were prior hospitalisation, prior dependency and chronic conditions. Adding pre- and intra-operative risk factors to models for cardiothoracic critical care gave little improvement in performance. Adding comorbidities to models for in-hospital cardiac arrest provided modest improvements but were of greater importance for longer-term outcomes. Limitations: Delays in obtaining linked data resulted in the data used being 5 years old at the point of publication: models will already require recalibration. Conclusions: Data linkage provided enhancements to the risk models underpinning national clinical audits in the form of additional predictors and novel outcomes measures. The new models developed in this report may assist in providing objective estimates of potential outcomes to patients and their families. Future work: (1) Develop and test care pathways for recovery following critical illness targeted at those with the greatest need; (2) explore other relevant data sources for longer-term outcomes; (3) widen data linkage for resource use and costs to primary care, outpatient and emergency department data

Silver nanowire networks: Physical properties and potential integration in solar cells

peer reviewedWith the growing interest in flexible electronics and the increased utilization of Indium Tin Oxide electrodes for display and photovoltaic applications the need for new materials is emerging. In this work we present the electro-optical properties of Ag nanowire networks as an alternative transparent conductive material. A comparison of different film deposition techniques is made and indicates that the properties of the network are independent of the fabrication method. Analysis of the electrical behavior as a function of nanowire density is made and compared with theoretical results as well as Monte Carlo simulations. Thermal annealing is shown to reduce the sheet resistance from 1000 Ω/sq to 8 Ω/sq; this reduction is achieved by local sintering of the nanowire junctions. Experimental optimization of Ag nanowire electrodes was undertaken and a peak in the electro-optical properties is observed at approximately 100 mg/m². Finally a discussion of the potential integration of Ag nanowire networks into solar cells is undertaken; we observe that these electrodes show promise as an emerging transparent conductive material, especially for flexible applications

2019 international consensus on cardiopulmonary resuscitation and emergency cardiovascular care science with treatment recommendations : summary from the basic life support; advanced life support; pediatric life support; neonatal life support; education, implementation, and teams; and first aid task forces

The International Liaison Committee on Resuscitation has initiated a continuous review of new, peer-reviewed, published cardiopulmonary resuscitation science. This is the third annual summary of the International Liaison Committee on Resuscitation International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations. It addresses the most recent published resuscitation evidence reviewed by International Liaison Committee on Resuscitation Task Force science experts. This summary addresses the role of cardiac arrest centers and dispatcher-assisted cardiopulmonary resuscitation, the role of extracorporeal cardiopulmonary resuscitation in adults and children, vasopressors in adults, advanced airway interventions in adults and children, targeted temperature management in children after cardiac arrest, initial oxygen concentration during resuscitation of newborns, and interventions for presyncope by first aid providers. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the certainty of the evidence on the basis of the Grading of Recommendations, Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence to Decision Framework Highlights sections. The task forces also listed priority knowledge gaps for further research

The nationwide impact of COVID-19 on life support courses. A retrospective evaluation by Resuscitation Council UK

Aim: To determine the impact of the COVID-19 pandemic on Resuscitation Council UK Advanced Life Support (ALS) and Immediate Life Support (ILS) course numbers and outcomes. Methods: We conducted a before-after study using course data from the Resuscitation Council UK Learning Management System between January 2018 and December 2021, using 23 March 2020 as the cut-off between pre- and post-pandemic periods. Demographics and outcomes were analysed using chi-squared tests and regression models. Results: There were 90,265 ALS participants (51,464 pre-; 38,801 post-) and 368,140 ILS participants (225,628 pre-; 142,512 post-). There was a sharp decline in participants on ALS/ILS courses due to COVID-19. ALS participant numbers rebounded to exceed pre-pandemic levels, whereas ILS numbers recovered to a lesser degree with increased uptake of e-learning versions. Mean ALS course participants reduced from 20.0 to 14.8 post-pandemic (P < 0.001). Post-pandemic there were small but statistically significant decreases in ALS Cardiac Arrest Simulation Test pass rates (from 82.1 % to 80.1 % (OR = 0.90, 95 % CI = 0.86–0.94, P < 0.001)), ALS MCQ score (from 86.6 % to 86.0 % (mean difference = -0.35, 95 % CI −0.44 to −0.26, P < 0.001)), and overall ALS course results (from 95.2 %to 94.7 %, OR = 0.92, CI = 0.85–0.99, P = 0.023). ILS course outcomes were similar post-pandemic (from 99.4 % to 99.4 %, P = 0.037). Conclusion: COVID-19 caused a sharp decline in the number of participants on ALS/ILS courses and an accelerated uptake of e-learning versions, with the average ALS course size reducing significantly. The small reduction in performance on ALS courses requires further research to clarify the contributing factors