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Sexual orientation and gender identity measures and viral suppression for people living with HIV: a protocol for a population-based cohort study

Por: Yang · X. · Olatosi · B. · Weissman · S. · Li · X. · Zhang · J.
Introduction

The measure of sexual orientation and gender identity (SOGI) data in electronic health records (EHR) has been critical for addressing health disparities and inequalities, especially for HIV care. Given that gender and sexual minorities (eg, transgender, men who have sex with men and intersex) are key groups in people living with HIV (PLWH), SOGI data can facilitate a more accurate understanding about the HIV outcomes (eg, viral suppression) among this key group and then lead to tailored therapeutic services. The two-step SOGI collection method as an emerging gender measurement can be used to measure SOGI status in medical settings. Using the statewide cohort of PLWH in South Carolina (SC), this project aims to: (1) integrate statewide PLWH cohort data with their birth certificate data to evaluate SOGI measurements from multiple EHR sources; and (2) examine differences in viral suppression based on SOGI measurements.

Methods and analysis

Our EHR database includes several HIV data sources with patients’ gender information, such as SC Department of Health and Environmental Control Centre (DHEC), Health Sciences South Carolina (HSSC) and Prisma as well as birth certificate data to retrieve the sex at birth. The SC Enhanced HIV/AIDS Reporting System (e-HARS) from DHEC will provide longitudinal viral load information to define a variety of viral suppression status. Datasources like the SC office of Revenue and Fiscal Affairs (RFA) will extract longitudinal EHR clinical data of all PLWH in SC from multiple health systems; obtain data from other state agencies and link the patient-level data with county-level data from multiple publicly available data sources.

Ethics and dissemination

The study was approved by the Institutional Review Board at the University of South Carolina (Pro00129906) as a Non-Human Subject study. The study’s findings will be published in peer-reviewed journals and disseminated at national and international conferences and through social media.

Patterns and predictors of racial/ethnic disparities in HIV care continuum in the Southern USA: protocol for a population-based cohort study

Por: Yang · X. · Zhang · J. · Olatosi · B. · Li · Z. · Weissman · S. · Li · X.
Introduction

Health disparities exist at every step of the HIV care continuum (HCC) among racial/ethnic minority population. Such racial/ethnic disparities may have significantly delayed the progress in HCC in the Southern US states that are strongly represented among geographic focus areas in the 2019 federal initiative titled ‘Ending the HIV Epidemic: A Plan for America’. However, limited efforts have been made to quantify the long-term spatiotemporal variations of HCC disparities and their contributing factors over time, particularly in the context of COVID-19 pandemic. This project aims to identify the spatiotemporal patterns of racial disparities of each HCC outcome and then determine the contribution of contextual features for temporal change of disparities in HCC.

Methods and analysis

This cohort study will use statewide HIV cohort data in South Carolina, including all people living with HIV (PLWH) who were diagnosed with HIV in 2005–2020. The healthcare encounter data will be extracted from longitudinal EHR from six state agencies and then linked to aggregated county-level community and social structural-level data (eg, structural racism, COVID-19 pandemic) from multiple publicly available data sources. The South Carolina Revenue of Fiscal and Affairs will serve as the honest broker to link the patient-level and county-level information. We will first quantify the HCC-related disparities by creating a county-level racial/ethnic disparity index (RDI) for each key HCC outcomes (eg, HIV testing, timely diagnosis), examine the temporal patterns of each RDI over time and then using geographical weighted lasso model examine which contextual factors have significant impacts on the change of county-level RDI from 2005 to 2020.

Ethics and dissemination

The study was approved by the Institutional Review Board at the University of South Carolina (Pro00121718) as a Non-Human Subject study. The study’s findings will be published in peer-reviewed journals and disseminated at national and international conferences and through social media.

Study of heavy metal resistance genes in <i>Escherichia coli</i> isolates from a marine ecosystem with a history of environmental pollution (arsenic, cadmium, copper, and mercury)

by Ashley S. Tseng, Marilyn C. Roberts, Scott J. Weissman, Peter M. Rabinowitz

We analyzed whole genome sequences of 308 Escherichia coli isolates from a marine ecosystem to determine the prevalence and relationships of heavy metal resistance genes (HMRGs) and antibiotic resistance genes (ARGs), as well as the presence of plasmid sequences. We screened all genomes for presence of 18 functional HMRGs conferring resistance to arsenic, cadmium, copper, or cadmium/mercury. In subset analyses, we examined geographic variations of HMRG carriage patterns in 224 isolates from water sources, and sought genetic linkages between HMRGs and ARGs in 25 genomes of isolates resistant to antibiotics. We found high carriage rates of HMRGs in all genomes, with 100% carrying at least one copy of 11 out of 18 HMRGs. A total of 173 (56%) of the isolates carried both HMRGs and plasmid sequences. In the 25 genomes of antibiotic-resistant isolates, 80% (n = 20) carried HMRGs, ARGs, and plasmid sequences, while 40% (n = 10) had linked HMRGs and ARGs on their assembled genomes. We found no evidence of geographic variation in HMRG frequency, nor any association between locational proximity to Superfund sites and co-carriage of HMRGs and ARGs. Our study findings indicate that HMRGs are common among E. coli in marine ecosystems, suggesting widespread heavy metal presence in water sources of a region with history of environmental pollution. Further research is needed to determine the role HMRGs play in driving antimicrobial resistance in human pathogens through genetic linkage and the value their detection in environmental bacterial genomes may offer as an indicator of environmental heavy metal pollution.
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