PSUN52 Patients with Left Ventricular Hypertrophy on Echocardiography are Frequently Evaluated with Renin and Aldosterone

Background

Increased left ventricular (LV) mass is an independent predictor of cardiovascular morbidity and mortality. Primary aldosteronism (PA) is associated with increased LV mass regardless of concomitant essential hypertension. Therefore, we hypothesize that the findings of increased LV mass approximated by left-ventricular hypertrophy (LVH) on echocardiogram relate to renin-independent hyperaldosteronism.

Methods

We performed a retrospective review of patients who underwent echocardiography at our institution between April of 2013 and September of 2017 (n=98,007 individuals). Of this population, we identified patients who underwent transthoracic echocardiography who met criteria for LVH based on current American Society of Echocardiography guidelines using the interventricular septal thickness in diastole (IVSd) and left ventricular posterior wall thickness in diastole (LVPWd). We excluded patients who underwent isolated transesophageal imaging as well as those who had significant structural cardiac abnormalities other than LVH. This cohort was analyzed with an internal self-service data tool to determine if patients had undergone biochemical evaluation with serum aldosterone and renin, which defined the final analytical cohort.

Results

We identified 19,664 patients with LVH of whom 5.8% (n = 1132) underwent biochemical evaluation with serum aldosterone and corresponding plasma renin activity (PRA) or direct renin concentration (DRC). In all patients with LVH, the mean IVSd was 11.7 ± 1.2mm in those who underwent biochemical testing and 11.5 ± 1.2 mm in those who did not (p <0.001); the mean LVPWd was 11.4 ± 1.1 mm mm in those who underwent biochemical testing and 11.3 ± 1.1 mm in those who did not (p <0.001). Of African American patients with LVH, 9.8% underwent biochemical testing; 5.0% of Caucasian patients with LVH underwent testing. The median PRA was 0.9 ng/mL/h with a median aldosterone to renin activty ratio (ARR) of 8.9 ng/dL-ng/mL/h. . The majority (54.4%) of individuals who underwent testing with plasma renin activity had a PRA ≤ 1.0 ng/mL/h.

Conclusion

Patients with LVH are being evaluated with renin and aldosterone at a higher frequency than patients with resistant hypertension and other guideline based indications for PA screening. Individuals evaluated with renin and aldosterone had increased IVSD and LVPWd, suggestive of more extensive LVH, compared with other individuals with LVH. LVH may be a sensitive screening criterion for PA. Additional prospective studies are necessary.

Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m.

COVID-19-associated AKI in hospitalized US patients: incidence, temporal trends, geographical distribution, risk factors and mortality

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. AKI was determined with serum creatinine (SCr) and diagnosis codes. Time were divided into 16-weeks (P1-6) periods and geographical regions into Northeast, Midwest, South, and West. Multivariable models were used to analyze the risk factors for AKI or mortality.

Results

Out of a total cohort of 306,061, 126,478 (41.0 %) patients had AKI. Among these, 17.9% lacked a diagnosis code but had AKI based on the change in SCr. Similar to patients coded for AKI, these patients had higher mortality compared to those without AKI. The incidence of AKI was highest in P1 (49.3%), reduced in P2 (40.6%), and relatively stable thereafter. Compared to the Midwest, the Northeast, South, and West had higher adjusted AKI incidence in P1, subsequently, the South and West regions continued to have the highest relative incidence. In multivariable models, AKI defined by either SCr or diagnostic code, and the severity of AKI was associated with mortality.

Conclusions

Uncoded cases of COVID-19-associated AKI are common and associated with mortality. The incidence and distribution of COVID-19-associated AKI have changed since the first wave of the pandemic in the US.

Abstract 040: Prevalence Of Dual Indications For Antihypertensive Medications And Statins In The National Health And Nutrition Survey

Introduction: Despite widespread indications for concomitant treatment of hypertension and hyperlipidemia, the proportion of the U. S population eligible for both remains unknown. Further, although fixed-dose combinations of these drugs are associated with better adherence, few are available.

Hypothesis: We hypothesized a significant proportion of the population would be eligible for antihypertensive medication and a statin.

Methods: Data from the National Health and Nutrition Examination Survey from 2011 to 2018 with survey weighting to represent the noninstitutionalized U.S. population ≥18 years were utilized. Prevalence of individuals with dual indications for antihypertensive and statin therapy was determined using the 2017 ACC/AHA guidelines for hypertension and the 2019 ACC/AHA guidelines for primary prevention of cardiovascular disease, respectively.

Results: Sociodemographic characteristics are shown in Table 1. Among those ≥18 years, there were 88 million (33.4%) individuals with an indication for antihypertensive medication and 88.5 million (33.9%) with an indication for a statin. 64.6 million adults or 24.8% (95% CI: 23.5 to 26.2) of the population had dual indications for antihypertensive medication and a statin. Notably, 73.4% of those indicated for antihypertensive medication were also indicated a statin.

Conclusions: Quarter of the U.S. adult population and nearly three-quarters of hypertensive patients are eligible for antihypertensive medication and a statin. Combining antihypertensive medications with a statin in fixed-dose combinations could reduce medication disutility and increase adherence to optimize lipid and blood pressure goals.

Ontology-Based Classification and Analysis of Adverse Events Associated With the Usage of Chloroquine and Hydroxychloroquine

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. According to EMBASE literature mining, CQ and HCQ were associated with QT prolongation (primarily when treating COVID-19), heart arrhythmias, development of Torsade des Pointes, and retinopathy (primarily when treating lupus). The FAERS data was analyzed by proportional ratio reporting, Chi-square test, and minimal case number filtering, followed by OAE classification. HCQ was associated with 63 significant AEs (including 21 cardiovascular AEs) for COVID-19 patients and 120 significant AEs (including 12 cardiovascular AEs) for lupus patients, supporting the hypothesis that the disease being treated affects the type and number of certain CQ/HCQ AEs that are manifested. Using an HCQ AE patient example reported in the literature, we also ontologically modeled how an AE occurs and what factors (e.g., age, biological sex, and medical history) are involved in the AE formation. The methodology developed in this study can be used for other drugs and indications to better identify patient populations that are particularly vulnerable to AEs.

Identification and Development of Therapeutics for COVID-19

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: Severe acute respiratory syndrome-related coronavirus, a species closely related to SARS-CoV-2 that emerged in 2002, and Middle East respiratory syndrome-related coronavirus, 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). Building on this research, the medical and scientific communities have responded rapidly to the COVID-19 crisis and identified many candidate therapeutics. The approaches used to identify candidates fall into four main categories: adaptation of clinical approaches to diseases with related pathologies, adaptation based on virological properties, adaptation based on host response, and data-driven identification (ID) of candidates based on physical properties or on pharmacological compendia. To date, a small number of therapeutics have already been authorized by regulatory agencies such as the Food and Drug Administration (FDA), while most remain under investigation. The scale of the COVID-19 crisis offers a rare opportunity to collect data on the effects of candidate therapeutics. This information provides insight not only into the management of coronavirus diseases but also into the relative success of different approaches to identifying candidate therapeutics against an emerging disease. IMPORTANCE The COVID-19 pandemic is a rapidly evolving crisis. With the worldwide scientific community shifting focus onto the SARS-CoV-2 virus and COVID-19, a large number of possible pharmaceutical approaches for treatment and prevention have been proposed. What was known about each of these potential interventions evolved rapidly throughout 2020 and 2021. This fast-paced area of research provides important insight into how the ongoing pandemic can be managed and also demonstrates the power of interdisciplinary collaboration to rapidly understand a virus and match its characteristics with existing or novel pharmaceuticals. As illustrated by the continued threat of viral epidemics during the current millennium, a rapid and strategic response to emerging viral threats can save lives. In this review, we explore how different modes of identifying candidate therapeutics have borne out during COVID-19.

Characterizing Long COVID: Deep Phenotype of a Complex Condition

BACKGROUND

Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies.

METHODS

The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19.

FUNDING

We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies.

INTERPRETATION

Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID.

FUNDING

U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411.

24-Hour Profiles of 11-Oxygenated C19 Steroids and Δ5-Steroid Sulfates during Oral and Continuous Subcutaneous Glucocorticoids in 21-Hydroxylase Deficiency

Background

Optimal management of androgen excess in 21-hydroxylase deficiency (21OHD) remains challenging. 11-oxygenated-C19 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 via continuous subcutaneous hydrocortisone infusion (CSHI) in patients with 21OHD based on 24-hour serial sampling.

Participants and Methods

We studied 8 adults (5 women), ages 19-43 years, with poorly controlled classic 21OHD who participated in a single-center open-label phase I-II study comparing OG with CSHI. We used mass spectrometry to measure 15 steroids (including 11-oxyandrogens and Δ5 steroid sulfates) in serum samples obtained every 2 h for 24 h after 3 months of stable OG, and 6 months into ongoing CSHI.

Results

In response to OG therapy, androstenedione, testosterone (T), and their four 11-oxyandrogen metabolites:11β-hydroxyandrostenedione, 11-ketoandrostenedione, 11β-hydroxytestosterone and 11-ketotestosterone (11KT) demonstrated a delayed decline in serum concentrations, and they achieved a nadir between 0100-0300. Unlike DHEAS, which had little diurnal variation, pregnenolone sulfate (PregS) and 17-hydoxypregnenolone sulfate peaked in early morning and declined progressively throughout the day. CSHI dampened the early ACTH and androgen rise, allowing the ACTH-driven adrenal steroids to return closer to baseline before mid-day. 11KT concentrations displayed the most consistent difference between OG and CSHI across all time segments. While T was lowered by CSHI as compared with OG in women, T increased in men, suggesting an improvement of the testicular function in parallel with 21OHD control in men.

Conclusion

11-oxyandrogens and PregS could serve as biomarkers of disease control in 21OHD. The development of normative data for these promising novel biomarkers must consider their diurnal variability.

Pathogenesis, Symptomatology, and Transmission of SARS-CoV-2 through Analysis of Viral Genomics and Structure

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. Because the genomic content of coronaviruses, which specifies the virus's structure, is highly conserved, early genomic analysis provided a significant head start in predicting viral pathogenesis and in understanding potential differences among variants. The pathogenesis of the virus offers insights into symptomatology, transmission, and individual susceptibility. Additionally, prior research into interactions between the human immune system and coronaviruses has identified how these viruses can evade the immune system's protective mechanisms. We also explore systems-level research into the regulatory and proteomic effects of SARS-CoV-2 infection and the immune response. Understanding the structure and behavior of the virus serves to contextualize the many facets of the COVID-19 pandemic and can influence efforts to control the virus and treat the disease. IMPORTANCE COVID-19 involves a number of organ systems and can present with a wide range of symptoms. From how the virus infects cells to how it spreads between people, the available research suggests that these patterns are very similar to those seen in the closely related viruses SARS-CoV-1 and possibly Middle East respiratory syndrome-related CoV (MERS-CoV). Understanding the pathogenesis of the SARS-CoV-2 virus also contextualizes how the different biological systems affected by COVID-19 connect. Exploring the structure, phylogeny, and pathogenesis of the virus therefore helps to guide interpretation of the broader impacts of the virus on the human body and on human populations. For this reason, an in-depth exploration of viral mechanisms is critical to a robust understanding of SARS-CoV-2 and, potentially, future emergent human CoVs (HCoVs).

Ten Rules for Conducting Retrospective Pharmacoepidemiological Analyses: Example COVID-19 Study

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. An observational study can provide this evidence, but the lack of randomized exposure and the researcher's inability to control treatment administration and data collection introduce significant challenges. A proper analysis of observational health care data thus requires contributions from experts in a diverse set of topics ranging from epidemiology and causal analysis to relevant medical specialties and data sources. Here we summarize these contributions as 10 rules that serve as an end-to-end introduction to retrospective pharmacoepidemiological analyses of observational health care data using a running example of a hypothetical COVID-19 study. A detailed supplement presents a practical how-to guide for following each rule. When carefully designed and properly executed, a retrospective pharmacoepidemiological analysis framed around these rules will inform the decisions of whether and how to investigate a treatment hypothesis in a randomized controlled trial. This work has important implications for any future pandemic by prescribing what we can and should do while the world waits for global vaccine distribution.

Separation, characterization, and standardization of extracellular vesicles for drug delivery applications

Extracellular vesicles (EVs) are membranous nanovesicles secreted from living cells, shuttling macromolecules in intercellular communication and potentially possessing intrinsic therapeutic activity. Due to their stability, low immunogenicity, and inherent interaction with recipient cells, EVs also hold great promise as drug delivery vehicles. Indeed, they have been used to deliver nucleic acids, proteins, and small molecules in preclinical investigations. Furthermore, EV-based drugs have entered early clinical trials for cancer or neurodegenerative diseases. Despite their appeal as delivery vectors, however, EV-based drug delivery progress has been hampered by heterogeneity of sample types and methods as well as a persistent lack of standardization, validation, and comprehensive reporting. This review highlights specific requirements for EVs in drug delivery and describes the most pertinent approaches for separation and characterization. Despite residual uncertainties related to pharmacodynamics, pharmacokinetics, and potential off-target effects, clinical-grade, high-potency EV drugs might be achievable through GMP-compliant workflows in a highly standardized environment.

Clinical Characterization and Prediction of Clinical Severity of SARS-CoV-2 Infection Among US Adults Using Data From the US National COVID Cohort Collaborative

Importance

The National COVID Cohort Collaborative (N3C) is a centralized, harmonized, high-granularity electronic health record repository that is the largest, most representative COVID-19 cohort to date. This multicenter data set can support robust evidence-based development of predictive and diagnostic tools and inform clinical care and policy.

Objectives

To evaluate COVID-19 severity and risk factors over time and assess the use of machine learning to predict clinical severity.

Design, Setting, and Participants

In a retrospective cohort study of 1 926 526 US adults with SARS-CoV-2 infection (polymerase chain reaction >99% or antigen <1%) and adult patients without SARS-CoV-2 infection who served as controls from 34 medical centers nationwide between January 1, 2020, and December 7, 2020, patients were stratified using a World Health Organization COVID-19 severity scale and demographic characteristics. Differences between groups over time were evaluated using multivariable logistic regression. Random forest and XGBoost models were used to predict severe clinical course (death, discharge to hospice, invasive ventilatory support, or extracorporeal membrane oxygenation).

Main Outcomes and Measures

Patient demographic characteristics and COVID-19 severity using the World Health Organization COVID-19 severity scale and differences between groups over time using multivariable logistic regression.

Results

The cohort included 174 568 adults who tested positive for SARS-CoV-2 (mean [SD] age, 44.4 [18.6] years; 53.2% female) and 1 133 848 adult controls who tested negative for SARS-CoV-2 (mean [SD] age, 49.5 [19.2] years; 57.1% female). Of the 174 568 adults with SARS-CoV-2, 32 472 (18.6%) were hospitalized, and 6565 (20.2%) of those had a severe clinical course (invasive ventilatory support, extracorporeal membrane oxygenation, death, or discharge to hospice). Of the hospitalized patients, mortality was 11.6% overall and decreased from 16.4% in March to April 2020 to 8.6% in September to October 2020 (P = .002 for monthly trend). Using 64 inputs available on the first hospital day, this study predicted a severe clinical course using random forest and XGBoost models (area under the receiver operating curve = 0.87 for both) that were stable over time. The factor most strongly associated with clinical severity was pH; this result was consistent across machine learning methods. In a separate multivariable logistic regression model built for inference, age (odds ratio [OR], 1.03 per year; 95% CI, 1.03-1.04), male sex (OR, 1.60; 95% CI, 1.51-1.69), liver disease (OR, 1.20; 95% CI, 1.08-1.34), dementia (OR, 1.26; 95% CI, 1.13-1.41), African American (OR, 1.12; 95% CI, 1.05-1.20) and Asian (OR, 1.33; 95% CI, 1.12-1.57) race, and obesity (OR, 1.36; 95% CI, 1.27-1.46) were independently associated with higher clinical severity.

Conclusions and Relevance

This cohort study found that COVID-19 mortality decreased over time during 2020 and that patient demographic characteristics and comorbidities were associated with higher clinical severity. The machine learning models accurately predicted ultimate clinical severity using commonly collected clinical data from the first 24 hours of a hospital admission.

Urinary extracellular vesicles: A position paper by the Urine Task Force of the International Society for Extracellular Vesicles

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. Therefore, several methods to isolate and characterize uEVs have been developed. However, methodological aspects of EV separation and analysis, including normalization of results, need further optimization and standardization to foster scientific advances in uEV research and a subsequent successful translation into clinical practice. This position paper is written by the Urine Task Force of the Rigor and Standardization Subcommittee of ISEV consisting of nephrologists, urologists, cardiologists and biologists with active experience in uEV research. Our aim is to present the state of the art and identify challenges and gaps in current uEV-based analyses for clinical applications. Finally, recommendations for improved rigor, reproducibility and interoperability in uEV research are provided in order to facilitate advances in the field.

Challenges in defining Long COVID: Striking differences across literature, Electronic Health Records, and patient-reported information

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. Even the condition itself goes by three terms, most widely "Long COVID", but also "COVID-19 syndrome (PACS)" or, "post-acute sequelae of SARS-CoV-2 infection (PASC)". In the present study, we investigate the definitions used in the literature published to date and compare them against data available from electronic health records and patient-reported information collected via surveys. Long COVID holds the potential to produce a second public health crisis on the heels of the pandemic itself. Proactive efforts to identify the characteristics of this heterogeneous condition are imperative for a rigorous scientific effort to investigate and mitigate this threat.

Identification and Development of Therapeutics for COVID-19

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: Severe acute respiratory syndrome-related coronavirus, a closely related species of SARS-CoV-2 that emerged in 2002, and Middle East respiratory syndrome-related coronavirus, 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). Building on this research, the medical and scientific communities have responded rapidly to the COVID-19 crisis to identify many candidate therapeutics. The approaches used to identify candidates fall into four main categories: adaptation of clinical approaches to diseases with related pathologies, adaptation based on virological properties, adaptation based on host response, and data-driven identification of candidates based on physical properties or on pharmacological compendia. To date, a small number of therapeutics have already been authorized by regulatory agencies such as the Food and Drug Administration (FDA), while most remain under investigation. The scale of the COVID-19 crisis offers a rare opportunity to collect data on the effects of candidate therapeutics. This information provides insight not only into the management of coronavirus diseases, but also into the relative success of different approaches to identifying candidate therapeutics against an emerging disease.

Testing for Primary Aldosteronism and Mineralocorticoid Receptor Antagonist Use Among U.S. Veterans : A Retrospective Cohort Study

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.

DESIGN

Retrospective cohort study.

SETTING

U.S. Veterans Health Administration.

PARTICIPANTS

Veterans with apparent treatment-resistant hypertension (n = 269 010) from 2000 to 2017, defined as either 2 blood pressures (BPs) of at least 140 mm Hg (systolic) or 90 mm Hg (diastolic) at least 1 month apart during use of 3 antihypertensive agents (including a diuretic), or hypertension requiring 4 antihypertensive classes.

MEASUREMENTS

Rates of primary aldosteronism testing (plasma aldosterone-renin) and the association of testing with evidence-based treatment using a mineralocorticoid receptor antagonist (MRA) and with longitudinal systolic BP.

RESULTS

4277 (1.6%) patients who were tested for primary aldosteronism were identified. An index visit with a nephrologist (hazard ratio [HR], 2.05 [95% CI, 1.66 to 2.52]) or an endocrinologist (HR, 2.48 [CI, 1.69 to 3.63]) was associated with a higher likelihood of testing compared with primary care. Testing was associated with a 4-fold higher likelihood of initiating MRA therapy (HR, 4.10 [CI, 3.68 to 4.55]) and with better BP control over time.

LIMITATIONS

Predominantly male cohort, retrospective design, susceptibility of office BPs to misclassification, and lack of confirmatory testing for primary aldosteronism.

CONCLUSION

In a nationally distributed cohort of veterans with apparent treatment-resistant hypertension, testing for primary aldosteronism was rare and was associated with higher rates of evidence-based treatment with MRAs and better longitudinal BP control. The findings reinforce prior observations of low adherence to guideline-recommended practices in smaller health systems and underscore the urgent need for improved management of patients with treatment-resistant hypertension.

PRIMARY FUNDING SOURCE

National Institutes of Health.

ST-segment elevation in patients presenting with COVID-19: case series

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. Three patients with confirmed COVID-19 presented with electrocardiogram criteria for ST-segment elevation myocardial infarction. No patient had obstructive coronary disease at coronary angiography. Post-mortem histology in one case demonstrated myocardial ischaemia in the absence of coronary atherothrombosis or myocarditis.

DISCUSSION

Patients with COVID-19 may present with features consistent with ST-segment elevation myocardial infarction and patent coronary arteries. The prevalence and clinical outcomes of this condition require systematic investigation in consecutive unselected patients.

Pathogenesis, Symptomatology, and Transmission of SARS-CoV-2 through Analysis of Viral Genomics and Structure

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. Because the genomic content of coronaviruses, which specifies the virus's structure, is highly conserved, early genomic analysis provided a significant head start in predicting viral pathogenesis and in understanding potential differences among variants. The pathogenesis of the virus offers insights into symptomatology, transmission, and individual susceptibility. Additionally, prior research into interactions between the human immune system and coronaviruses has identified how these viruses can evade the immune system's protective mechanisms. We also explore systems-level research into the regulatory and proteomic effects of SARS-CoV-2 infection and the immune response. Understanding the structure and behavior of the virus serves to contextualize the many facets of the COVID-19 pandemic and can influence efforts to control the virus and treat the disease.

The National COVID Cohort Collaborative: Clinical Characterization and Early Severity Prediction

Background:

The majority of U.S. reports of COVID-19 clinical characteristics, disease course, and treatments are from single health systems or focused on one domain. Here we report the creation of the National COVID Cohort Collaborative (N3C), a centralized, harmonized, high-granularity electronic health record repository that is the largest, most representative U.S. cohort of COVID-19 cases and controls to date. This multi-center dataset supports robust evidence-based development of predictive and diagnostic tools and informs critical care and policy.

Methods and Findings:

In a retrospective cohort study of 1,926,526 patients from 34 medical centers nationwide, we stratified patients using a World Health Organization COVID-19 severity scale and demographics; we then evaluated differences between groups over time using multivariable logistic regression. We established vital signs and laboratory values among COVID-19 patients with different severities, providing the foundation for predictive analytics. The cohort included 174,568 adults with severe acute respiratory syndrome associated with SARS-CoV-2 (PCR >99% or antigen <1%) as well as 1,133,848 adult patients that served as lab-negative controls. Among 32,472 hospitalized patients, mortality was 11.6% overall and decreased from 16.4% in March/April 2020 to 8.6% in September/October 2020 (p = 0.002 monthly trend). In a multivariable logistic regression model, age, male sex, liver disease, dementia, African-American and Asian race, and obesity were independently associated with higher clinical severity. To demonstrate the utility of the N3C cohort for analytics, we used machine learning (ML) to predict clinical severity and risk factors over time. Using 64 inputs available on the first hospital day, we predicted a severe clinical course (death, discharge to hospice, invasive ventilation, or extracorporeal membrane oxygenation) using random forest and XGBoost models (AUROC 0.86 and 0.87 respectively) that were stable over time. The most powerful predictors in these models are patient age and widely available vital sign and laboratory values. The established expected trajectories for many vital signs and laboratory values among patients with different clinical severities validates observations from smaller studies, and provides comprehensive insight into COVID-19 characterization in U.S. patients.

Conclusions:

This is the first description of an ongoing longitudinal observational study of patients seen in diverse clinical settings and geographical regions and is the largest COVID-19 cohort in the United States. Such data are the foundation for ML models that can be the basis for generalizable clinical decision support tools. The N3C Data Enclave is unique in providing transparent, reproducible, easily shared, versioned, and fully auditable data and analytic provenance for national-scale patient-level EHR data. The N3C is built for intensive ML analyses by academic, industry, and citizen scientists internationally. Many observational correlations can inform trial designs and care guidelines for this new disease.

Responsible, practical genomic data sharing that accelerates research

Data sharing anchors reproducible science, but expectations and best practices are often nebulous. Communities of funders, researchers and publishers continue to grapple with what should be required or encouraged. To illuminate the rationales for sharing data, the technical challenges and the social and cultural challenges, we consider the stakeholders in the scientific enterprise. In biomedical research, participants are key among those stakeholders. Ethical sharing requires considering both the value of research efforts and the privacy costs for participants. We discuss current best practices for various types of genomic data, as well as opportunities to promote ethical data sharing that accelerates science by aligning incentives.

Randomized elimination and prolongation of ACE inhibitors and ARBs in coronavirus 2019 (REPLACE COVID) Trial Protocol

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), is associated with high incidence of multiorgan dysfunction and death. Angiotensin-converting enzyme 2 (ACE2), which facilitates SARS-CoV-2 host cell entry, may be impacted by angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs), two commonly used antihypertensive classes. In a multicenter, international randomized controlled trial that began enrollment on March 31, 2020, participants are randomized to continuation vs withdrawal of their long-term outpatient ACEI or ARB upon hospitalization with COVID-19. The primary outcome is a hierarchical global rank score incorporating time to death, duration of mechanical ventilation, duration of renal replacement or vasopressor therapy, and multiorgan dysfunction severity. Approval for the study has been obtained from the Institutional Review Board of each participating institution, and all participants will provide informed consent. A data safety monitoring board has been assembled to provide independent oversight of the project.

Extracellular Vesicles in Essential Hypertension: Hidden Messengers

PURPOSE OF REVIEW

Hypertension affects about half of all Americans, yet in the vast majority of cases, the factors causing the hypertension cannot be clearly delineated. Developing a more precise understanding of the molecular pathogenesis of HTN and its various phenotypes is therefore a pressing priority. Circulating and urinary extracellular vesicles (EVs) are potential novel candidates as biomarkers and bioactivators in HTN. EVs are a heterogeneous population of small membrane fragments shed from various cell types into various body fluids. As EVs carry protein, RNA, and lipids, they also play a role as effectors and novel cell-to-cell communicators. In this review, we discuss the diagnostic, functional, and regenerative role of EVs in essential HTN and focus on EV protein and RNA cargo as the most extensively studied EV cargo.

RECENT FINDINGS

The field of EVs in HTN is still a young one and earlier studies have not used the novel EV detection tools currently available. More rigor and transparency in EV research are needed. Current data suggest that EVs represent potential novel biomarkers in HTN. EVs correlate with HTN severity and possibly end-organ damage. However, it has yet to be discerned which specific subtype(s) of EV reflects best HTN pathophysiology. Evolving studies are also showing that EVs might be novel regulators in vascular and renal tubular function and also be therapeutic. RNA in EVs has been studied in the context of hypertension, largely in the form of studies of miRNA, which are reviewed herein. Beyond miRNAs, mRNA in urinary EVs changed in response to sodium loading in humans. EVs represent promising novel biomarkers and bioactivators in essential HTN. Novel tools are being developed to apply more rigor in EV research including more in vivo models and translation to humans.

Blood pressure, heart rate, and mortality in chronic obstructive pulmonary disease: the SUMMIT trial

Aims

To characterize the relationship between blood pressure (BP) or heart rate and mortality and morbidity in chronic obstructive pulmonary disease (COPD).

Methods and results

We performed post hoc analysis of baseline BP or heart rate and all-cause mortality and cardiovascular events in the SUMMIT trial. SUMMIT was a randomized double-blind outcome trial of 16 485 participants (65 ± 8 years, 75% male, and 47% active smokers) enrolled at 1368 sites in 43 countries. Participants with moderate COPD with or at risk for cardiovascular disease (CVD) were randomized to placebo, long-acting beta agonist, inhaled corticosteroid, or their combination. All-cause mortality increased in relation to high systolic [≥140 mmHg; hazard ratio (HR) 1.27, 95% confidence interval (CI) 1.12-1.45] or diastolic (≥90 mmHg; HR 1.35, 95% CI 1.14-1.59) BP and low systolic (<120 mmHg; HR 1.36, 95% CI 1.13-1.63) or diastolic (<80 mmHg; HR 1.15, 95% CI 1.00-1.32) BP. Higher heart rates (≥80 per minute; HR 1.39, 95% CI 1.21-1.60) and pulse pressures (≥80 mmHg; HR 1.39, 95% CI 1.07-1.80) were more linearly related to increases in all-cause mortality. The risks of cardiovascular events followed similar patterns to all-cause mortality. Similar findings were observed in subgroups of patients without established CVD.

Conclusion

A 'U-shaped' relationship between BP and all-cause mortality and cardiovascular events exists in patients with COPD and heightened cardiovascular risk. A linear relationship exists between heart rate and all-cause mortality and cardiovascular events in this population. These findings extend the prognostic importance of BP to this growing group of patients and raise concerns that both high and low BP may pose health risks.

Medicare reimbursement policy for ambulatory blood pressure monitoring: A qualitative analysis of public comments to the Centers for Medicare and Medicaid Services

Ambulatory blood pressure monitoring (ABPM) is considered the best means of diagnosing hypertension. However, it is rarely used and is reimbursed only under narrow conditions. We sought to gain insight into the perceived value of ABPM among stakeholders who responded to the Centers for Medicare and Medicaid Services' (CMS) request for comments to inform the first revision of ABPM reimbursement policy in over 15 years. We found that most comments were classifiable in two main themes, current coverage and future coverage. Individuals and institutions representing multiple disciplines and specialties were highly supportive of expanding the current CMS coverage of ABPM, including for a wide range of clinical indications and populations. It is clear from the comments reviewed that there is wide support for expanding CMS coverage for ABPM. Broad support for a change in ABPM reimbursement policy may lead to changes in the way this technology is used in the United States.

Current Status of Angiotensin Receptor Blocker Recalls

Losartan was the ninth most prescribed drug in the United States in 2016, and several other angiotensin-II receptor blockers (ARBs) are widely prescribed. Since July 2018, >2 dozen specific ARB products have been recalled owing to the presence of potentially carcinogenic nitrosamine impurities in selected lots. As is the case with all U.S. drug recalls, the ARB recalls have been voluntary on the part of the companies involved. In April 2019, the Food and Drug Administration categorized marketed ARB products with respect to nitrosamine impurities: (1) not present, (2) to be determined with no prior lots removed from the market (TBD), or (3) to be determined in the context of prior lots having been removed from the market (TBD*). The data were structured as hundreds of rows of products. Owing to the complexity of these data, more than a year into the recalls, it remains difficult for clinicians to understand which ARB products are free of impurities.

Primary Aldosteronism: Practical Approach to Diagnosis and Management

Primary aldosteronism (PA) is the most common form of secondary hypertension. In many cases, somatic mutations in ion channels and pumps within adrenal cells initiate the pathogenesis of PA, and this mechanism might explain why PA is so common and suggests that milder and evolving forms of PA must exist. Compared with primary hypertension, PA causes more end-organ damage and is associated with excess cardiovascular morbidity, including heart failure, stroke, nonfatal myocardial infarction, and atrial fibrillation. Screening is simple and readily available, and targeted therapy improves blood pressure control and mitigates cardiovascular morbidity. Despite these imperatives, screening rates for PA are low, and mineralocorticoid-receptor antagonists are underused for hypertension treatment. After the evidence for the prevalence of PA and its associated cardiovascular morbidity is summarized, a practical approach to PA screening, referral, and management is described. All physicians who treat hypertension should routinely screen appropriate patients for PA.

Human Urinary mRNA as a Biomarker of Cardiovascular Disease

Supplemental Digital Content is available in the text.

Background

mRNA in urine supernatant (US-mRNA) might encode information about renal and cardiorenal pathophysiology, including hypertension. H, whether the US-mRNA transcriptome reflects that of renal tissues and whether changes in renal physiology are detectable using US-mRNA is unknown.

Methods

We compared transcriptomes of human urinary extracellular vesicles and human renal cortex. To avoid similarities attributable to ubiquitously expressed genes, we separately analyzed ubiquitously expressed and highly kidney-enriched genes. To determine whether US-mRNA reflects changes in renal gene expression, we assayed cell-depleted urine for transcription factor activity of mineralocorticoid receptors (MR) using probe-based quantitative polymerase chain reaction. The urine was collected from prehypertensive individuals (n=18) after 4 days on low-sodium diet to stimulate MR activity and again after suppression of MR activity via sodium infusion.

Results

In comparing this US-mRNA and human kidney cortex, expression of 55 highly kidney-enriched genes correlated strongly (r_s=0.82) while 8457 ubiquitously expressed genes correlated moderately (r_s=0.63). Standard renin-angiotensin-aldosterone system phenotyping confirmed the expected response to sodium loading. Cycle threshold values for MR-regulated targets (SCNN1A, SCNN1G, TSC22D3) changed after sodium loading, and MR-regulated targets (SCNN1A, SCNN1G, SGK1, and TSC22D3) correlated significantly with serum aldosterone and inversely with urinary sodium excretion.

Conclusions

RNA-sequencing of urinary extracellular vesicles shows concordance with human kidney. Perturbation in human endocrine signaling (MR activation) was accompanied by changes in mRNA in urine supernatant. Our findings could be useful for individualizing pharmacological therapy in patients with disorders of mineralocorticoid signaling, such as resistant hypertension. More generally, these insights could be used to noninvasively identify putative biomarkers of disordered renal and cardiorenal physiology.

Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing

Supplemental Digital Content is available in the text.

Background:

Data sharing accelerates scientific progress but sharing individual-level data while preserving patient privacy presents a barrier.

Methods and Results:

Using pairs of deep neural networks, we generated simulated, synthetic participants that closely resemble participants of the SPRINT trial (Systolic Blood Pressure Trial). We showed that such paired networks can be trained with differential privacy, a formal privacy framework that limits the likelihood that queries of the synthetic participants’ data could identify a real a participant in the trial. Machine learning predictors built on the synthetic population generalize to the original data set. This finding suggests that the synthetic data can be shared with others, enabling them to perform hypothesis-generating analyses as though they had the original trial data.

Conclusions:

Deep neural networks that generate synthetic participants facilitate secondary analyses and reproducible investigation of clinical data sets by enhancing data sharing while preserving participant privacy.

Hypertension

Recent guidelines on diagnosis and management of high blood pressure (BP) include substantial changes and several new concepts compared with previous guidelines. These are reviewed and their clinical implications are discussed in this article. The goal is to provide a practical reference to assist clinicians with up-to-date management of patients with high BP. Important issues include new diagnostic thresholds, out-of-office BP monitoring, intensified treatment goals, and a different approach to resistant hypertension. Finally, differences among guidelines, the persistent controversies that have led to them, and their implications for clinical practice are discussed.

Personalized Medicine and the Treatment of Hypertension

PURPOSE OF REVIEW

The purpose of this review is to discuss the implications of personalized medicine for the treatment of hypertension, including resistant hypertension.

RECENT FINDINGS

We suggest a framework for the personalized treatment of hypertension based on the concept of a trade-off between simplicity and personalization. This framework is based on treatment strategies classified as low, medium, or high information burden personalization approaches. The extent to which a higher information burden is justified depends on the clinical scenario, particularly the ease with which the blood pressure can be controlled. A one-size-fits-many treatment strategy for hypertension is efficacious for most people; however, a more personalized approach could be useful in patients with subtypes of hypertension that do not respond as expected to treatment. Clinicians seeing patients with unusual hypertension phenotypes should be familiar with emerging trends in personalized treatment of hypertension.

Clinical research using extracellular vesicles: insights from the International Society for Extracellular Vesicles 2018 Annual Meeting

The abstracts presented at the 2018 International Society for Extracellular Vesicles Annual Meeting offer unique insight into the newest discoveries related to the biology and applied use of extracellular vesicles (EVs). As an extension of a recent "Clinical-Wrap Up" discussion at the International Society for Extracellular Vesicles 2018 Annual Meeting, a systematic review of each abstract was performed to determine which abstracts could be considered clinical research. Once the clinical research abstracts were identified, systematic data extraction included: the major focus of each clinical research abstract; the countries in which the work was done; and the sample size, if provided in the abstract. Each abstract was reviewed by two independent authors, with a third author resolving discrepancies in cases of disagreement. 174 out of 656 (27%) unique abstracts were determined to be clinical research. Oncology was a principal research focus (51 of the 174 clinical research abstracts, 29%). Many other clinical research abstracts presented at the International Society for Extracellular Vesicles 2018 Annual Meeting focused on the use of human samples for development of methods for potential application in the clinic. Beyond oncology and methods development, a wide range of topics was represented, including cardiovascular disease, neurodegenerative disease, genetics, and many others. Current research involving EVs highlights the common, but false dichotomy of science into curiosity-driven basic science or application-driven clinical research, when in fact both quest for understanding and intent to apply the findings appeared to drive much of the work at the International Society for Extracellular Vesicles 2018 Annual Meeting. Using Pasteur's Quadrant as a framework, we discuss where the field of EV research is heading and how we may gain insight into the biological function of EVs in tandem with how they may benefit individual health.

Use of physician-recommended non-pharmacological strategies for hypertension control among hypertensive patients

This study aims to evaluate the 4 non-pharmacological strategies adopted by patients for hypertension control and patient characteristics that affect the choice of strategies. Four thousand hypertensive patients aged ≥18 years were selected from the National Health and Nutrition Examination Survey. Odds ratios of the choice of strategies were analyzed using weighted logistic models. Clinical recommendations of non-pharmacological strategies for hypertension control were relatively low. More exercise was the least frequent strategy used for hypertension control. More patients reported using ≥3 strategies than using ≤2 strategies (79.1% vs 20.9%, P < .0001). Non-Hispanic blacks were more likely to use each individual strategy and to use ≥3 strategies simultaneously. Patients with obesity and diabetes were less likely to attempt weight control or more exercise, but more likely to use ≥3 strategies than peers. Educational programs should be developed to enhance physician's advice for lifestyle modifications and to increase patient's acceptance of physical activity.

Reach Out Churches: A Community-Based Participatory Research Pilot Trial to Assess the Feasibility of a Mobile Health Technology Intervention to Reduce Blood Pressure Among African Americans

Innovative strategies are needed to reduce the hypertension epidemic among African Americans. Reach Out was a faith-collaborative, mobile health, randomized, pilot intervention trial of four mobile health components to reduce high blood pressure (BP) compared to usual care. It was designed and tested within a community-based participatory research framework among African Americans recruited and randomized from churches in Flint, Michigan. The purpose of this pilot study was to assess the feasibility of the Reach Out processes. Feasibility was assessed by willingness to consent (acceptance of randomization), proportion of weeks participants texted their BP readings (intervention use), number lost to follow-up (retention), and responses to postintervention surveys and focus groups (acceptance of intervention). Of the 425 church members who underwent BP screening, 94 enrolled in the study and 73 (78%) completed the 6-month outcome assessment. Median age was 58 years, and 79% were women. Participants responded with their BPs on an average of 13.7 (SD = 10.7) weeks out of 26 weeks that the BP prompts were sent. All participants reported satisfaction with the intervention. Reach Out, a faith-collaborative, mobile health intervention was feasible. Further study of the efficacy of the intervention and additional mobile health strategies should be considered.

Cigarette Smoking and Subtypes of Uncontrolled Blood Pressure Among Diagnosed Hypertensive Patients: Paradoxical Associations and Implications

BACKGROUND

Isolated uncontrolled systolic blood pressure (SBP), uncontrolled systolic-diastolic blood pressure (BP), and isolated uncontrolled diastolic blood pressure (DBP) are subtypes of uncontrolled BP. The associations of smoking with uncontrolled BP subtypes among diagnosed hypertensive patients are unknown.

METHODS

Seven thousand eight hundred twenty-nine subjects aged 18 years or over with diagnosed hypertension were selected from the National Health and Nutrition Examination Survey with stratified multistage clustered sampling design. Weighted logistic regressions were conducted to estimate odds ratios (ORs) with 95% confidence intervals (CIs) of uncontrolled BP subtypes related to smoking status. Weighted multiple regression models were used to examine the association of smoking with levels of SBP, DBP, and pulse pressure.

RESULTS

The average age of the study sample was 60.3 ± 0.3 years. 54.2% ± 0.7% were females. Compared to nonsmokers, current smokers were 22% less likely to have uncontrolled BP (OR: 0.78, 95% CI: 0.64-0.94, P = 0.01), and 21% less likely to have isolated uncontrolled SBP (OR: 0.79, 95% CI: 0.64-0.97, P = 0.02). Average DBP was 1.5 mm Hg lower (95% CI: -2.8 to -0.2 mm Hg, P = 0.02) in current smokers than in nonsmokers. Average DBP was 0.9 mm Hg lower (95% CI: -1.7 to -0.03 mm Hg, P = 0.04) in former smokers than in nonsmokers. Current smoking and former smoking were not associated with risk of uncontrolled systolic-diastolic BP and isolated uncontrolled DBP.

CONCLUSIONS

Paradoxical associations between current smoking and SBP, uncontrolled BP and isolated uncontrolled SBP were shown among hypertensive patients. The explanation for these associations is currently unknown. No cause-effect relationships should be assumed.

Personalized medicine and treatment approaches in hypertension: current perspectives

In the US, hypertension affects one in three adults. Current guideline-based treatment of hypertension involves little diagnostic testing. A more personalized approach to the treatment of hypertension might be of use. Several methods of personalized treatment have been proposed and vetted to varying degrees. The purpose of this narrative review is to discuss the rationale for personalized therapy in hypertension, barriers to its development and implementation, some influential examples of proposed personalization measures, and a view of future efforts.

Anxiety in the "age of hypertension"

In the USA, hypertension affects one in three adults, and anxiety disorders are the most commonly diagnosed mental health disorders. Both hypertension and anxiety have been studied extensively. Yet, a full understanding of anxiety's relationship to hypertension has been elusive. In this review, we discuss the spectrum of anxiety disorders. In addition, we consider the evidence for acute and long-term effects of anxiety on blood pressure. We review the effect on blood pressure of several "real-world" stressors, such as natural disasters. In addition, we review the effect of anxiety treatments on blood pressure. We explain the American Heart Association's recent recommendations regarding meditation and other relaxation methods in the management of hypertension. We conclude that novel research methods are needed in order to better elucidate many aspects of how anxiety relates to hypertension.