Recovery of dialysis patients with COVID-19 : health outcomes 3 months after diagnosis in ERACODA

Background. Coronavirus disease 2019 (COVID-19)-related short-term mortality is high in dialysis patients, but longer-term outcomes are largely unknown. We therefore assessed patient recovery in a large cohort of dialysis patients 3 months after their COVID-19 diagnosis. Methods. We analyzed data on dialysis patients diagnosed with COVID-19 from 1 February 2020 to 31 March 2021 from the European Renal Association COVID-19 Database (ERACODA). The outcomes studied were patient survival, residence and functional and mental health status (estimated by their treating physician) 3 months after COVID-19 diagnosis. Complete follow-up data were available for 854 surviving patients. Patient characteristics associated with recovery were analyzed using logistic regression. Results. In 2449 hemodialysis patients (mean ± SD age 67.5 ± 14.4 years, 62% male), survival probabilities at 3 months after COVID-19 diagnosis were 90% for nonhospitalized patients (n = 1087), 73% for patients admitted to the hospital but not to an intensive care unit (ICU) (n = 1165) and 40% for those admitted to an ICU (n = 197). Patient survival hardly decreased between 28 days and 3 months after COVID-19 diagnosis. At 3 months, 87% functioned at their pre-existent functional and 94% at their pre-existent mental level. Only few of the surviving patients were still admitted to the hospital (0.8-6.3%) or a nursing home (∼5%). A higher age and frailty score at presentation and ICU admission were associated with worse functional outcome. Conclusions. Mortality between 28 days and 3 months after COVID-19 diagnosis was low and the majority of patients who survived COVID-19 recovered to their pre-existent functional and mental health level at 3 months after diagnosis

UNITY : a low-field magnetic resonance neuroimaging initiative to characterize neurodevelopment in low and middle-income settings

DATA AVAILABILITY : Data collected as part of the UNITY network will be made available to researchers from the academic communities at varying levels of granularity depending on site-specific IRB approvals. For some sites, full access to individual raw and processed data will be provided, whilst for others, owing to national policies (e.g., those located in India) may only be able to provide de-identified composite values (e.g., regional volumes, mean relaxometry measures, etc.). The Bill & Melinda Gates Foundation is committed to open access and broad data availability as permitted.Measures of physical growth, such as weight and height have long been the predominant outcomes for monitoring child health and evaluating interventional outcomes in public health studies, including those that may impact neurodevelopment. While physical growth generally reflects overall health and nutritional status, it lacks sensitivity and specificity to brain growth and developing cognitive skills and abilities. Psychometric tools, e.g., the Bayley Scales of Infant and Toddler Development, may afford more direct assessment of cognitive development but they require language translation, cultural adaptation, and population norming. Further, they are not always reliable predictors of future outcomes when assessed within the first 12–18 months of a child’s life. Neuroimaging may provide more objective, sensitive, and predictive measures of neurodevelopment but tools such as magnetic resonance (MR) imaging are not readily available in many low and middle-income countries (LMICs). MRI systems that operate at lower magnetic fields (< 100mT) may offer increased accessibility, but their use for global health studies remains nascent. The UNITY project is envisaged as a global partnership to advance neuroimaging in global health studies. Here we describe the UNITY project, its goals, methods, operating procedures, and expected outcomes in characterizing neurodevelopment in sub-Saharan Africa and South Asia.The Bill & Melinda Gates Foundation, the NIHR Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, and through a Wellcome Trust Investigator Award and a Wellcome Trust Strategic Award.https://www.elsevier.com/locate/dcnhj2024Biochemistry, Genetics and Microbiology (BGM)ImmunologyPaediatrics and Child HealthRadiologySDG-03:Good heatlh and well-beingSDG-17:Partnerships for the goal

Social-ecological and regional adaption of agrobiodiversity management across a global set of research regions

To examine management options for biodiversity in agricultural landscapes, eight research regions were classified into social-ecological domains, using a dataset of indicators of livelihood resources, i.e., capital assets. Potential interventions for biodiversity-based agriculture were then compared among landscapes and domains. The approach combined literature review with expert judgment by researchers working in each landscape. Each landscape was described for land use, rural livelihoods and attitudes of social actors toward biodiversity and intensification of agriculture. Principal components analysis of 40 indicators of natural, human, social, financial and physical capital for the eight landscapes showed a loss of biodiversity associated with high-input agricultural intensification. High levels of natural capital (e.g. indicators of wildland biodiversity conservation and agrobiodiversity for human needs) were positively associated with indicators of human capital, including knowledge of the flora and fauna and knowledge sharing among farmers. Three social-ecological domains were identified across the eight landscapes (Tropical Agriculture-Forest Matrix, Tropical Degrading Agroecosystem, and Temperate High-Input Commodity Agriculture) using hierarchical clustering of the indicator values. Each domain shared a set of interventions for biodiversity-based agriculture and ecological intensification that could also increase food security in the impoverished landscapes. Implementation of interventions differed greatly among the landscapes, e.g. financial capital for new farming practices in the Intensive Agriculture domain vs. developing market value chains in the other domains. This exploratory study suggests that indicators of knowledge systems should receive greater emphasis in the monitoring of biodiversity and ecosystem services, and that inventories of assets at the landscape level can inform adaptive management of agrobiodiversity-based intervention