Impairment and restrictions in possibly benign multiple sclerosis

Objective The aim was to describe a broad range of health dimensions in possibly benign multiple sclerosis (MS) hypothesizing that despite some limitations there is a high adaptation to the disease. Methods All patients from an outpatient university clinic data registry with an Expanded Disability Status Scale (EDSS) ≤3.5 and disease duration ≥15 years were addressed in a cross-sectional study. Physical impairment, neuropsychological functioning but also influence on activities and patient reported outcome measures including coping were studied. Results One hundred and twenty-five patients could be included (mean EDSS: 2.8; mean disease duration: 24 years). Cognitive impairment was minor (8%) but fatigue (73%) and depression (46%) were prevalent. Nevertheless, QOL and daily activities seemed to be less affected. Patients showed high social support, coping abilities, and sense of coherence, which was predictive for their perceived benignity of the disease. Based on the EDSS alone, we estimated the rate of benign MS after 15 years of MS as high as 23% decreasing to 16% if cognition was included in the definition. However, cognitive performance was not relevantly associated with other outcomes. Conclusion Common benign MS definitions seem to simplify a complex disease picture where different impairments and personal resources lead to more or less impact on people’s lives

The National Early Warning Score and its subcomponents recorded within ±24 hours of emergency medical admission are poor predictors of hospital-acquired acute kidney injury

YesBackground: Hospital-acquired Acute Kidney Injury (H-AKI) is a common cause of avoidable morbidity and mortality. Aim: To determine if the patients’ vital signs data as defined by a National Early Warning Score (NEWS), can predict H-AKI following emergency admission to hospital. Methods: Analyses of emergency admissions to York hospital over 24-months with NEWS data. We report the area under the curve (AUC) for logistic regression models that used the index NEWS (model A0), plus age and sex (A1), plus subcomponents of NEWS (A2) and two-way interactions (A3). Likewise for maximum NEWS (models B0,B1,B2,B3). Results: 4.05% (1361/33608) of emergency admissions had H-AKI. Models using the index NEWS had the lower AUCs (0.59 to 0.68) than models using the maximum NEWS AUCs (0.75 to 0.77). The maximum NEWS model (B3) was more sensitivity than the index NEWS model (A0) (67.60% vs 19.84%) but identified twice as many cases as being at risk of H-AKI (9581 vs 4099) at a NEWS of 5. Conclusions: The index NEWS is a poor predictor of H-AKI. The maximum NEWS is a better predictor but seems unfeasible because it is only knowable in retrospect and is associated with a substantial increase in workload albeit with improved sensitivity.The Health Foundatio

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Coastal greening of grey infrastructure: an update on the state-of-the-art

In the marine environment, greening of grey infrastructure (GGI) is a rapidly growing field that attempts to encourage native marine life to colonise marine artificial structures to enhance biodiversity, thereby promoting ecosystem functioning and hence service provision. By designing multifunctional sea defences, breakwaters, port complexes and offshore renewable energy installations, these structures can yield myriad environmental benefits, in particular, addressing UN SDG 14: Life below water. Although GGI has shown great promise and there is a growing evidence base, there remain many criticisms and knowledge gaps, and some feel that there is scope for GGI to be abused by developers to facilitate harmful development. Given the surge of research in this field in recent years, it is timely to review the literature to provide an update on the state of the art of the field in relation to the many criticisms and identify remaining knowledge gaps. Despite the rapid and significant advances made in this field, there is currently a lack of science and practice outside of academic sectors in the developed world, and there is a collective need for schemes that encourage intersectoral and trans-sectoral research, knowledge exchange and capacity building to optimise GGI in the pursuit of contributing to sustainable development

Coastal greening of grey infrastructure: An update on the state-of-the-art

In the marine environment, greening of grey infrastructure (GGI) is a rapidly growing field that attempts to encourage native marine life to colonize marine artificial structures to enhance biodiversity, thereby promoting ecosystem functioning and hence service provision. By designing multifunctional sea defences, breakwaters, port complexes and off-shore renewable energy installations, these structures can yield myriad environmental benefits, in particular, addressing UN SDG 14: Life below water. Whilst GGI has shown great promise and there is a growing evidence base, there remain many criticisms and knowledge gaps, and some feel that there is scope for GGI to be abused by developers to facilitate harmful development. Given the surge of research in this field in recent years, it is timely to review the literature to provide an update update on the state-of-the-art of the field in relation to the many criticisms and identify remaining knowledge gaps. Despite the rapid and significant advances made in this field, there is currently a lack of science and practice outside of academic sectors in the developed world, and there is a collective need for schemes that encourage intersectoral and transsectoral research, knowledge exchange, and capacity building to optimize GGI in the pursuit of contributing to sustainable development

Non-natives: 141 scientists object [Letter]

Peer reviewe

Environmental and societal factors associated with COVID-19-related death in people with rheumatic disease: an observational study

Published by Elsevier Ltd.Background: Differences in the distribution of individual-level clinical risk factors across regions do not fully explain the observed global disparities in COVID-19 outcomes. We aimed to investigate the associations between environmental and societal factors and country-level variations in mortality attributed to COVID-19 among people with rheumatic disease globally. Methods: In this observational study, we derived individual-level data on adults (aged 18-99 years) with rheumatic disease and a confirmed status of their highest COVID-19 severity level from the COVID-19 Global Rheumatology Alliance (GRA) registry, collected between March 12, 2020, and Aug 27, 2021. Environmental and societal factors were obtained from publicly available sources. The primary endpoint was mortality attributed to COVID-19. We used a multivariable logistic regression to evaluate independent associations between environmental and societal factors and death, after controlling for individual-level risk factors. We used a series of nested mixed-effects models to establish whether environmental and societal factors sufficiently explained country-level variations in death. Findings: 14 044 patients from 23 countries were included in the analyses. 10 178 (72·5%) individuals were female and 3866 (27·5%) were male, with a mean age of 54·4 years (SD 15·6). Air pollution (odds ratio 1·10 per 10 μg/m3 [95% CI 1·01-1·17]; p=0·0105), proportion of the population aged 65 years or older (1·19 per 1% increase [1·10-1·30]; p<0·0001), and population mobility (1·03 per 1% increase in number of visits to grocery and pharmacy stores [1·02-1·05]; p<0·0001 and 1·02 per 1% increase in number of visits to workplaces [1·00-1·03]; p=0·032) were independently associated with higher odds of mortality. Number of hospital beds (0·94 per 1-unit increase per 1000 people [0·88-1·00]; p=0·046), human development index (0·65 per 0·1-unit increase [0·44-0·96]; p=0·032), government response stringency (0·83 per 10-unit increase in containment index [0·74-0·93]; p=0·0018), as well as follow-up time (0·78 per month [0·69-0·88]; p<0·0001) were independently associated with lower odds of mortality. These factors sufficiently explained country-level variations in death attributable to COVID-19 (intraclass correlation coefficient 1·2% [0·1-9·5]; p=0·14). Interpretation: Our findings highlight the importance of environmental and societal factors as potential explanations of the observed regional disparities in COVID-19 outcomes among people with rheumatic disease and lay foundation for a new research agenda to address these disparities.MAG is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant numbers K01 AR070585 and K24 AR074534 [JY]). KDW is supported by the Department of Veterans Affairs and the Rheumatology Research Foundation Scientist Development award. JAS is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant numbers K23 AR069688, R03 AR075886, L30 AR066953, P30 AR070253, and P30 AR072577), the Rheumatology Research Foundation (K Supplement Award and R Bridge Award), the Brigham Research Institute, and the R. Bruce and Joan M. Mickey Research Scholar Fund. NJP is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (T32-AR-007258). AD-G is supported by grants from the Centers for Disease Control and Prevention and the Rheumatology Research Foundation. RH was supported by the Justus-Liebig University Giessen Clinician Scientist Program in Biomedical Research to work on this registry. JY is supported by grants from the National Institutes of Health (K24 AR074534 and P30 AR070155).info:eu-repo/semantics/publishedVersio