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Impact of COVID-19 pandemic on incidence of long-term conditions in Wales: a population data linkage study using primary and secondary care health records
Get PDFBackground The COVID-19 pandemic has directly and indirectly had an impact on health service provision owing to surges and sustained pressures on the system. The effects of these pressures on the management of long-term or chronic conditions are not fully understood.Aim To explore the effects of COVID-19 on the recorded incidence of 17 long-term conditions.Design and setting This was an observational retrospective population data linkage study on the population of Wales using primary and secondary care data within the Secure Anonymised Information Linkage (SAIL) Databank.Method Monthly rates of new diagnosis between 2000 and 2021 are presented for each long-term condition. Incidence rates post-2020 were compared with expected rates predicted using time series modelling of pre-2020 trends. The proportion of annual incidence is presented by sociodemographic factors: age, sex, social deprivation, ethnicity, frailty, and learning disability.Results A total of 5 476 012 diagnoses from 2 257 992 individuals are included. Incidence rates from 2020 to 2021 were lower than mean expected rates across all conditions. The largest relative deficit in incidence was in chronic obstructive pulmonary disease corresponding to 343 (95% confidence interval = 230 to 456) undiagnosed patients per 100 000 population, followed by depression, type 2 diabetes, hypertension, anxiety disorders, and asthma. A GP practice of 10 000 patients might have over 400 undiagnosed long-term conditions. No notable differences between sociodemographic profiles of post- and pre-2020 incidences were observed.Conclusion There is a potential backlog of undiagnosed patients with multiple long-term conditions. Resources are required to tackle anticipated workload as part of COVID-19 recovery, particularly in primary care
Corporate Socio-political Activism and Retail Investors: Evidence from the Black Lives Matter Campaign
Get PDFThis study investigates retail investor responses to corporate engagement in corporate socio-political activism (CSA). Using manually collected evidence of companies’ support for the Black Lives Matter (BLM) campaign, we find that speaking up in support of BLM attracts retail investor attention. However, it influences their investment decisions only if speaking up is backed up by a monetary donation to BLM-related causes on the same day. This effect is observed for companies that have black directors on their board and companies headquartered in Democrat-leaning states. There is no corresponding increase in firm value. Our results suggest that retail investor preferences for companies that engage in CSA are likely guided by moral sentiment
Exploring the similarities and differences of variables collected by burn registers globally: protocol for a data dictionary review study
Get PDFIntroduction Burn registers can provide high-quality clinical data that can be used for surveillance, research, planning service provision and clinical quality assessment. Many countrywide and intercountry burn registers now exist. The variables collected by burn registers are not standardised internationally. Few international burn register data comparisons are completed beyond basic morbidity and mortality statistics. Data comparisons across registers require analysis of homogenous variables. Little work has been done to understand whether burn registers have sufficiently similar variables to enable useful comparisons. The aim of this project is to compare the variables collected in countrywide and intercountry burn registers internationally to understand their similarities and differences.Methods and analysis Burn register custodians will be invited to participate in the study and to share their register data dictionaries. Study objectives are to compare patient inclusion and exclusion criteria of each participating burn register; determine which variables are collected by each register, and if variables are required or optional, identify common variable themes; and compare a sample of variables to understand how they are defined and measured. All variable names will be extracted from each register and common themes will be identified. Detailed information will be extracted for a sample of variables to give a deeper insight into similarities and differences between registers.Ethics and dissemination No patient data will be used in this project. Permission to use each register’s data dictionary will be sought from respective register custodians. Results will be presented at international meetings and published in open access journals. These results will be of interest to register custodians and researchers wishing to explore international data comparisons, and countries wishing to establish their own burn register
Real-Time Demonstration of Concurrent Upstream and Inter-ONU Communications in Hybrid OFDM DFMA PONs
Get PDFThis paper presents the first real-time experimental demonstration of concurrent upstream and inter-ONU communications in a hybrid OFDM DFMA PON, enabled by a simple low-cost alteration to the remote node. Real-time FPGA-based DSP, incorporating a 128-pt FFT and a joint sideband processing technique, is used to demultiplex different sub-wavelength channels at the ONU and OLT receivers. The simple modification in the remote node removes the need for direct user-to-user data to pass via the OLT and core network thus providing ultra-low latency inter-ONU connectivity to support a variety of newly emerging latency sensitive 5G services. The presented PON is validated with two subwavelength bands, each capable of carrying one of two possible orthogonal channels ( I or Q ). The dynamic channel and subcarrier allocation allows flexible allocation of PON capacity between upstream and inter-ONU links for dynamic on-demand capacity allocation and also performance optimisation according to the different length dependent link characteristics. Moreover, the backscattering effect associated with upstream signals is shown to have negligible effect on the BER performance of the inter-ONU communications
Contingent convertible bonds in financial networks
Get PDFWe study the role of contingent convertible bonds (CoCos) in a complex network of interconnected banks. By studying the system’s phase transitions, we reveal that the structure of the interbank network is of fundamental importance for the effectiveness of CoCos as a financial stability enhancing mechanism. Our results show that, under some network structures, the presence of CoCos can increase (and not reduce) financial fragility, because of the occurring of unneeded triggers and consequential suboptimal conversions that damage CoCos investors. We also demonstrate that, in the presence of a moderate financial shock, lightly interconnected financial networks are more robust than highly interconnected networks. This makes them a potentially optimal choice for both CoCos issuers and buyers
Benefits of a Novel Bioplastic Coated Fertiliser on Nitrogen Use Efficiency in Turfgrass
No full textAgentic emotion regulation in high-risk sport: An in-depth analysis across climbing disciplines
Get PDFMindfulness-Based Stress Reduction for Our Time: A Curriculum that is up to the Task
Get PDFThere is current heightened public consciousness of the intersecting challenges of social and racial injustice, other forms of inequity, and the climate and biodiversity crisis. We examine how these current realities influence how we engage as Mindfulness-Based Stress Reduction (MBSR) and Mindfulness-Based Program (MBP) teachers and researchers. Although Kabat-Zinn developed MBSR as a vehicle to enable engagement with both the individual and the collective drivers of distress and flourishing, predominant research and practice trends within the MBP field have prioritised individual wellbeing, and have not been accessible to the full societal demographic. Furthermore, there is increasing recognition that the systemic social inequities that influence access to public services have not been addressed in the MBP field. In response, there is now an increasing trend exploring how MBP participation can influence ‘bigger than self’ concerns, with research, practice and theory suggesting that the inner personal transformation that mindfulness practice enables, supports individuals to compassionately reconnect to self, other and the natural world in ways that foster prosocial behaviour change, and enables awareness building of personal bias and conditioning. In this paper we present perspectives on ways of both retaining fidelity to the existing MBSR program, and simultaneously embracing anti-oppression teaching methods and content, and an inclusive recognition of the micro, meso and macro causes and conditions that drive distress and flourishing. We are a group of racially diverse MBP teachers and trainers from both sides of the Atlantic, who are engaged in training initiatives with people from Black, Latinex, Indigenous, Asian, and People of Color communities
Recent Approaches to Design and Analysis of Electrical Impedance Systems for Single Cells using Machine Learning
Get PDFIndividual cells have many unique properties that can be quantified to develop a holistic understanding of a population. This can include understanding population characteristics, identifying subpopulations, or elucidating outlier characteristics that may be indicators of disease. Electrical impedance measurements are rapid and label-free for the monitoring of single cells and generate large datasets of many cells at single or multiple frequencies. To increase the accuracy and sensitivity of measurements and define the relationships between impedance and biological features, many electrical measurement systems have incorporated machine learning (ML) paradigms for control and analysis. Considering the difficulty capturing complex relationships using traditional modelling and statistical methods due to population heterogeneity, ML offers an exciting approach to the systemic collection and analysis of electrical properties in a data-driven way. In this work, we discuss incorporation of ML to improve the field of electrical single cell analysis by addressing the design challenges to manipulate single cells and sophisticated analysis of electrical properties that distinguish cellular changes. Looking forward, we emphasize the opportunity to build on integrated systems to address common challenges in data quality and generalizability to save time and resources at every step in electrical measurement of single cells.</p
