There are very few studies comparing epidemiology and outcomes of out-of-hospital cardiac arrest (OHCA) in different ethnic groups. Previous ethnicity studies have mostly determined OHCA differences between African American and Caucasian populations. The aim of this study was to compare epidemiology, clinical presentation, and outcomes of OHCA between the local Middle Eastern Gulf Cooperation Council (GCC) Arab and the migrant North African populations living in Qatar. This was a retrospective cohort study of Middle Eastern GCC Arabs and migrant North African patients with presumed cardiac origin OHCA resuscitated by Emergency Medical Services (EMS) in Qatar, between June 2012 and May 2015. There were 285 Middle Eastern GCC Arabs and 112 North African OHCA patients enrolled during the study period. Compared with the local GCC Arabs, univariate analysis showed that the migrant North African OHCA patients were younger and had higher odds of initial shockable rhythm, pre-hospital interventions (defibrillation and amioderone), pre-hospital scene time, and decreased odds of risk factors (hypertension, respiratory disease, and diabetes) and pre-hospital response time. The survival to hospital discharge had greater odds for North African OHCA patients which did not persist after adjustment. Multivariable logistic regression showed that North Africans were associated with lower odds of diabetes (OR 0.48, 95% CI 0.25-0.91, = 0.03), and higher odds of initial shockable rhythm (OR 2.86, 95% CI 1.30-6.33, = 0.01) and greater scene time (OR 1.02 95% CI 1.0-1.04, = 0.02). North African migrant OHCA patients were younger, had decreased risk factors and favourable OHCA rhythm and received greater ACLS interventions with shorter pre-hospital response times and longer scene times leading to better survival.
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http://dx.doi.org/10.1080/13557858.2018.1530736 | DOI Listing |
The degree of immunological compatibility between donors and recipients greatly impacts allograft survival. In the United States kidney allocation system, HLA antigen-level matching has been shown to cause ethnic disparities and thus, has been de-emphasised. However, priority points are still awarded for antigen-level zero-ABDR matching, zero-DR matching and one-DR matching.
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December 2024
Department of Nephrology and Mineral Metabolism, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
Objective: We performed a scoping review of randomised clinical trials (RCTs) assessing pharmacological therapies for the initial management of lupus nephritis (LN), focusing on study design, included populations and outcome definitions, to assess the generalisability of their results and identify gaps in the evidence.
Methods: RCTs evaluating pharmacological interventions for the initial therapy of LN published between 2000 and 2024 were evaluated. Extracted variables included study design, selection criteria, outcome definitions, populations recruited and clinical characteristics of participants.
PLoS One
December 2024
A.J. Drexel Autism Institute, Drexel University, Philadelphia, PA, United States of America.
The objective of this study was to identify utilization of housing support provided by the U.S. Department of Housing and Urban Development (HUD) among autistic people in the U.
View Article and Find Full Text PDFBMC Res Notes
December 2024
COPC Research Unit, Faculty of Health Sciences, University of Pretoria, Pretoria, 0002, South Africa.
Objective: Prior research has shown strong evidence of spatial clustering of tuberculosis across a range of contexts. Identifying the spatial patterning of infectious diseases such as tuberculosis is crucial as it allows for targeted intervention strategies, directing healthcare resources efficiently to areas where tuberculosis incidence is concentrated. This is especially true for low- and middle-income countries that typically experience greater resource constraints relative to their Global North counterparts.
View Article and Find Full Text PDFLancet Digit Health
December 2024
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK; Centre for Patient Reported Outcomes Research, School of Health Sciences, College of Medical and Dental Sciences, Birmingham, UK; University of Birmingham, Birmingham, UK. Electronic address:
Without careful dissection of the ways in which biases can be encoded into artificial intelligence (AI) health technologies, there is a risk of perpetuating existing health inequalities at scale. One major source of bias is the data that underpins such technologies. The STANDING Together recommendations aim to encourage transparency regarding limitations of health datasets and proactive evaluation of their effect across population groups.
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