Effects of rare kidney diseases on kidney failure: a longitudinal analysis of the UK National Registry of Rare Kidney Diseases (RaDaR) cohort

\ua9 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Individuals with rare kidney diseases account for 5–10% of people with chronic kidney disease, but constitute more than 25% of patients receiving kidney replacement therapy. The National Registry of Rare Kidney Diseases (RaDaR) gathers longitudinal data from patients with these conditions, which we used to study disease progression and outcomes of death and kidney failure. Methods: People aged 0–96 years living with 28 types of rare kidney diseases were recruited from 108 UK renal care facilities. The primary outcomes were cumulative incidence of mortality and kidney failure in individuals with rare kidney diseases, which were calculated and compared with that of unselected patients with chronic kidney disease. Cumulative incidence and Kaplan–Meier survival estimates were calculated for the following outcomes: median age at kidney failure; median age at death; time from start of dialysis to death; and time from diagnosis to estimated glomerular filtration rate (eGFR) thresholds, allowing calculation of time from last eGFR of 75 mL/min per 1\ub773 m2 or more to first eGFR of less than 30 mL/min per 1\ub773 m2 (the therapeutic trial window). Findings: Between Jan 18, 2010, and July 25, 2022, 27 285 participants were recruited to RaDaR. Median follow-up time from diagnosis was 9\ub76 years (IQR 5\ub79–16\ub77). RaDaR participants had significantly higher 5-year cumulative incidence of kidney failure than 2\ub781 million UK patients with all-cause chronic kidney disease (28% vs 1%; p<0\ub70001), but better survival rates (standardised mortality ratio 0\ub742 [95% CI 0\ub732–0\ub752]; p<0\ub70001). Median age at kidney failure, median age at death, time from start of dialysis to death, time from diagnosis to eGFR thresholds, and therapeutic trial window all varied substantially between rare diseases. Interpretation: Patients with rare kidney diseases differ from the general population of individuals with chronic kidney disease: they have higher 5-year rates of kidney failure but higher survival than other patients with chronic kidney disease stages 3–5, and so are over-represented in the cohort of patients requiring kidney replacement therapy. Addressing unmet therapeutic need for patients with rare kidney diseases could have a large beneficial effect on long-term kidney replacement therapy demand. Funding: RaDaR is funded by the Medical Research Council, Kidney Research UK, Kidney Care UK, and the Polycystic Kidney Disease Charity

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Stratospheric and mesospheric data assimilation: the role of middle atmospheric dynamics

The middle atmosphere refers to the stratosphere and mesosphere and features dynamics and circulationsthat are fundamentally different from those of the troposphere. The large-scale meridional circulations inthe middle atmosphere operate on seasonal and longer time scales and are largely forced by the breakingof upward propagating waves. The winter stratosphere is dominated by large-scale waves and a polarvortex which confines constituents and which is sometimes punctuated by stratospheric sudden warmings.In contrast, the summer stratosphere is quiescent. Meanwhile, the meridional circulation in themesosphere is mainly driven by the breaking of a broad spectrum of gravity waves that have propagatedupward from the troposphere. These facets of middle atmosphere dynamics have implications for, andpose unique challenges to, data assimilation systems whose models encompass this region of theatmosphere. In this work, we provide an overview of middle atmosphere data assimilation in the contextof the dynamics of this region. The purpose is to demonstrate how the dynamics can be used to explainthe behavior of data assimilation systems in the middle atmosphere, and also to identify challenges inassimilating measurements from this region of the atmosphere. There are two overarching themes.Firstly, we consider the vertical propagation of information through waves, resolved and parameterized,and background error covariances. Secondly, we delve into the dynamical sources of model errors andtechniques for their estimation.Fil: Polavarapu, Saroja. Environment and Climate Change Canada; CanadáFil: Pulido, Manuel Arturo. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas y Naturales y Agrimensura. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Modelado e Innovación Tecnológica. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Modelado e Innovación Tecnológica; Argentin

Innovative Technologies for Sustainable Textile Coloration, Patterning, and Surface Effects

The environmental impact of textile dyeing and finishing is of paramount concern in the textile industry. Enzyme and laser processing technologies present attractive alternatives to conventional textile coloration and surface patterning methods. Both technologies have the capability to reduce the impact of manufacturing on the environment by reducing the consumption of chemicals, water and energy, and the subsequent generation of waste. Two emerging textile processing technologies, laser processing and enzyme biotechnology, were investigated as a means of applying surface design and color to materials with a focus on improving the efficiency and sustainability of existing textile design and finishing methods. Through industrial stakeholder engagement and interdisciplinary research involving textile design, fiber and dye chemistry, biotechnology and optical engineering, this design-led project brought together design practice and science with a commercial focus. Each technology was used to modify targeted material properties, finding and exploiting opportunities for the design and finishing of textiles. The work resulted in a catalog of new coloration and design techniques for both technologies making it possible to achieve: selective surface pattern by differential dyeing, combined three-dimensional and color finishing and novel coloration of textile materials. The chapter provides a literature review mapping the use of enzyme biotechnology and laser processing technology within textile design and manufacturing to date, identifying current and future opportunities to reduce environmental impacts through their application. The methodological approach, which was interdisciplinary and design-led, will be introduced and the specific design and scientific methods applied will be detailed. Each of the techniques developed will be discussed and examples of the design effects achieved will be presented. And, an indication of the reductions in chemical effluent, efficiencies in resource use, and design-flexibility in comparison with traditional textile coloration and surface patterning techniques will be given