Publications by authors named "James B Byrd"

Background: In this study, we investigated sleep quality, depression and stress symptoms as hypothesized factors affecting the association between HIV status and nocturnal blood pressure dipping status in rural Uganda.

Methods: Individuals living with HIV (PLHIV) and people without HIV (PwoHIV) underwent 24-hour ambulatory blood pressure monitoring (ABPM) and classified as extreme dippers, dippers and non-dippers based on a percentage nocturnal drop in mean systolic and diastolic blood pressure. Ordinal logistic regression models were used to assess the effect of different exposure variables (HIV status, sleep quality and other covariates) on the outcome (dipping status).

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This interdisciplinary review explores the intricate nexus between HIV infection, nutrition, adrenal gland function, and cardiovascular health, highlighting a critical aspect of HIV management often overlooked in current literature. With the advent of antiretroviral therapy, the life expectancy of people living with HIV has dramatically improved, transforming HIV into a manageable chronic condition. However, this success brings forth new challenges, notably an increased risk of cardiovascular diseases among people living with HIV.

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Background: AKI is associated with mortality in patients hospitalized with coronavirus disease 2019 (COVID-19); however, its incidence, geographic distribution, and temporal trends since the start of the pandemic are understudied.

Methods: Electronic health record data were obtained from 53 health systems in the United States in the National COVID Cohort Collaborative. We selected hospitalized adults diagnosed with COVID-19 between March 6, 2020, and January 6, 2022.

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Background: Acute kidney injury (AKI) is associated with mortality in patients hospitalized with COVID-19, however, its incidence, geographic distribution, and temporal trends since the start of the pandemic are understudied.

Methods: Electronic health record data were obtained from 53 health systems in the United States (US) in the National COVID Cohort Collaborative (N3C). We selected hospitalized adults diagnosed with COVID-19 between March 6th, 2020, and January 6th, 2022.

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Multiple methodologies have been developed to identify and predict adverse events (AEs); however, many of these methods do not consider how patient population characteristics, such as diseases, age, and gender, affect AEs seen. In this study, we evaluated the utility of collecting and analyzing AE data related to hydroxychloroquine (HCQ) and chloroquine (CQ) from US Prescribing Information (USPIs, also called drug product labels or package inserts), the FDA Adverse Event Reporting System (FAERS), and peer-reviewed literature from PubMed/EMBASE, followed by AE classification and modeling using the Ontology of Adverse Events (OAE). Our USPI analysis showed that CQ and HCQ AE profiles were similar, although HCQ was reported to be associated with fewer types of cardiovascular, nervous system, and musculoskeletal AEs.

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Background: Optimal management of androgen excess in 21-hydroxylase deficiency (21OHD) remains challenging. 11-oxygenated-C steroids (11-oxyandrogens) have emerged as promising biomarkers of disease control, but data regarding their response to treatment are lacking.

Objective: To compare the dynamic response of a broad set of steroids to both conventional oral glucocorticoids (OG) and circadian cortisol replacement continuous subcutaneous hydrocortisone infusion (CSHI) in patients with 21OHD based on 24-hour serial sampling.

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Article Synopsis
  • The text discusses the challenges in understanding long COVID (PASC) due to varied terminologies and inconsistent methods in studies, making it hard to compare findings.
  • It highlights the importance of using the Human Phenotype Ontology (HPO) to create standardized terminology for clinical manifestations associated with long COVID, facilitating better data integration across research studies.
  • The authors curated relevant studies and identified 287 unique clinical findings, noting that while fatigue was the most reported symptom, there was a wide range of reports and terminology used by different studies.
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After emerging in China in late 2019, the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread worldwide, and as of mid-2021, it remains a significant threat globally. Only a few coronaviruses are known to infect humans, and only two cause infections similar in severity to SARS-CoV-2: , a species closely related to SARS-CoV-2 that emerged in 2002, and , which emerged in 2012. Unlike the current pandemic, previous epidemics were controlled rapidly through public health measures, but the body of research investigating severe acute respiratory syndrome and Middle East respiratory syndrome has proven valuable for identifying approaches to treating and preventing novel coronavirus disease 2019 (COVID-19).

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The novel coronavirus SARS-CoV-2, which emerged in late 2019, has since spread around the world and infected hundreds of millions of people with coronavirus disease 2019 (COVID-19). While this viral species was unknown prior to January 2020, its similarity to other coronaviruses that infect humans has allowed for rapid insight into the mechanisms that it uses to infect human hosts, as well as the ways in which the human immune system can respond. Here, we contextualize SARS-CoV-2 among other coronaviruses and identify what is known and what can be inferred about its behavior once inside a human host.

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Since the beginning of the COVID-19 pandemic, pharmaceutical treatment hypotheses have abounded, each requiring careful evaluation. A randomized controlled trial generally provides the most credible evaluation of a treatment, but the efficiency and effectiveness of the trial depend on the existing evidence supporting the treatment. The researcher must therefore compile a body of evidence justifying the use of time and resources to further investigate a treatment hypothesis in a trial.

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Article Synopsis
  • - The National COVID Cohort Collaborative (N3C) is a massive electronic health record database that provides valuable insights into COVID-19, supporting the development of better diagnostic tools and clinical practices.
  • - This study analyzed data from nearly 2 million adults across 34 medical centers to evaluate the severity of COVID-19 and its risk factors over time, using advanced machine learning techniques to predict severe outcomes.
  • - Among the 174,568 adults infected with SARS-CoV-2, a significant portion experienced severe illness, highlighting the need for continuous monitoring and adjustment of treatment approaches based on demographic characteristics and disease severity.
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Urine is commonly used for clinical diagnosis and biomedical research. The discovery of extracellular vesicles (EV) in urine opened a new fast-growing scientific field. In the last decade urinary extracellular vesicles (uEVs) were shown to mirror molecular processes as well as physiological and pathological conditions in kidney, urothelial and prostate tissue.

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Article Synopsis
  • Extracellular vesicles (EVs) are tiny membrane-bound structures released by cells that play a key role in communication between cells and have potential as therapeutic agents and drug delivery systems.
  • EVs have shown promise in preclinical studies for delivering nucleic acids, proteins, and small molecules, and some have even entered early clinical trials targeting cancer and neurodegenerative diseases.
  • However, the advancement of EV-based drug delivery is challenged by variability in sample types and methods, lack of standardization, and ongoing concerns about their safety and effectiveness, though high-quality EV drugs might be developed through more systematic approaches.
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Since late 2019, the novel coronavirus SARS-CoV-2 has introduced a wide array of health challenges globally. In addition to a complex acute presentation that can affect multiple organ systems, increasing evidence points to long-term sequelae being common and impactful. The worldwide scientific community is forging ahead to characterize a wide range of outcomes associated with SARS-CoV-2 infection; however the underlying assumptions in these studies have varied so widely that the resulting data are difficult to compareFormal definitions are needed in order to design robust and consistent studies of Long COVID that consistently capture variation in long-term outcomes.

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After emerging in China in late 2019, the novel coronavirus SARS-CoV-2 spread worldwide and as of mid-2021 remains a significant threat globally. Only a few coronaviruses are known to infect humans, and only two cause infections similar in severity to SARS-CoV-2: , a closely related species of SARS-CoV-2 that emerged in 2002, and , which emerged in 2012. Unlike the current pandemic, previous epidemics were controlled rapidly through public health measures, but the body of research investigating severe acute respiratory syndrome and Middle East respiratory syndrome has proven valuable for identifying approaches to treating and preventing novel coronavirus disease 2019 (COVID-19).

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Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the now pandemic disease, coronavirus disease (COVID-19). A number of reports have emerged suggesting these patients may present with signs and symptoms consistent with ST-segment elevation myocardial infarction without coronary artery occlusion.

Case Summary: We report an international case series of patients with confirmed COVID-19 infection who presented with suspected ST-segment elevation myocardial infarction.

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The novel coronavirus SARS-CoV-2, which emerged in late 2019, has since spread around the world and infected hundreds of millions of people with coronavirus disease 2019 (COVID-19). While this viral species was unknown prior to January 2020, its similarity to other coronaviruses that infect humans has allowed for rapid insight into the mechanisms that it uses to infect human hosts, as well as the ways in which the human immune system can respond. Here, we contextualize SARS-CoV-2 among other coronaviruses and identify what is known and what can be inferred about its behavior once inside a human host.

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Article Synopsis
  • The National COVID Cohort Collaborative (N3C) is the largest U.S. COVID-19 patient database, created to provide a comprehensive analysis of clinical characteristics, disease progression, and treatment outcomes across multiple health centers, enhancing predictive and diagnostic tools for COVID-19.
  • A study involving over 1.9 million patients from 34 medical centers found significant clinical data, showing that certain factors like age, sex, and underlying conditions affect disease severity, with a notable decrease in mortality rates among hospitalized patients over time.
  • The N3C dataset was utilized in machine learning models to successfully predict severe outcomes in COVID-19 patients, achieving high accuracy rates and demonstrating the potential of using electronic health
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Background: Biological considerations suggest that renin-angiotensin system inhibitors might influence the severity of COVID-19. We aimed to evaluate whether continuing versus discontinuing renin-angiotensin system inhibitors (angiotensin-converting enzyme inhibitors or angiotensin receptor blockers) affects outcomes in patients admitted to hospital with COVID-19.

Methods: The REPLACE COVID trial was a prospective, randomised, open-label trial done at 20 large referral hospitals in seven countries worldwide.

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Background: Primary aldosteronism is a common cause of treatment-resistant hypertension. However, evidence from local health systems suggests low rates of testing for primary aldosteronism.

Objective: To evaluate testing rates for primary aldosteronism and evidence-based hypertension management in patients with treatment-resistant hypertension.

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