Comparative Effectiveness of the Bivalent (Original/Omicron BA.4/BA.5) mRNA COVID-19 Vaccines mRNA-1273.222 and BNT162b2 Bivalent in Adults with Underlying Medical Conditions in the United States.

BACKGROUND/OBJECTIVES: This retrospective cohort study evaluated the relative vaccine effectiveness (rVE) of two bivalent (original/Omicron BA.4/BA.5) vaccines mRNA-1273.222 versus the BNT162b2 Bivalent in preventing COVID-19-related outcomes in adults with underlying medical conditions associated with increased risk for severe COVID-19. METHODS: In a linked electronic health record/claims dataset, US adults (≥18 years) with ≥1 underlying medical condition of interest who received either the bivalent vaccine between 31 August 2022 and 28 February 2023 were identified. The inverse probability of treatment weighting was used to adjust for cohort differences. Cohorts were followed up for COVID-19-related hospitalizations and outpatient encounters until 31 May 2023. Hazard ratios and rVEs were estimated using Cox regression. Subgroup analyses were performed on individuals with pre-specified comorbid conditions. RESULTS: 757,572 mRNA-1273.222 and 1,204,975 BNT162b2 Bivalent recipients were identified. The adjusted rVE over a median follow-up of 198 days was 10.9% (6.2%-15.2%) against COVID-19-related hospitalization and 3.2% (1.7%-4.7%) against COVID-19-related outpatient encounters. rVE estimates for COVID-19 hospitalizations among subgroups with comorbid conditions were as follows: diabetes 15.1% (8.7%-21.0%), cerebro- and cardiovascular disease 14.7% (9.0%-20.1%), chronic lung disease 11.9% (5.1%-18.2%), immunocompromised 15.0% (7.2%-22.2%), chronic kidney disease 8.4% (0.5%-15.7%). CONCLUSIONS: Overall, among adults with underlying medical conditions, mRNA-1273.222 was more effective than BNT162b2 Bivalent, especially in preventing COVID-19-related hospitalizations.

Obesity and metabolic syndrome in patients with heart failure with preserved ejection fraction: a cross-sectional analysis of the Veradigm Cardiology Registry.

BACKGROUND: The proportion of heart failure patients with preserved ejection fraction has been rising over the past decades and has coincided with increases in the prevalence of obesity and metabolic syndrome. The relationship between these interconnected comorbidities and heart failure with preserved ejection fraction (HFpEF) is still poorly understood. This study characterized obesity and metabolic syndrome among real-world patients with HFpEF. METHODS: We identified adults with heart failure in the Veradigm Cardiology Registry, previously the PINNACLE Registry, with a left ventricular ejection fraction measurement ≥ 50% between 01/01/2016 and 12/31/2019. Patients were stratified by obesity diagnosis and presence of metabolic syndrome (≥ 3 of the following: diabetes, hypertension, hyperlipidemia, and obesity). We captured baseline demographic and clinical characteristics and used multivariable logistic regression to examine the odds of having cardiac (atrial fibrillation, coronary artery disease, coronary artery bypass surgery, myocardial infarction, and stroke/transient ischemic attack) and non-cardiac (chronic kidney disease, chronic liver disease, and peripheral artery disease) comorbidities of interest. The models adjusted for age and sex, and the main covariates of interest were obesity and metabolic burden score (0-3 based on the presence of diabetes, hypertension, and hyperlipidemia). The models were run with and without an obesity*metabolic burden score interaction term. RESULTS: This study included 264,571 patients with HFpEF, of whom 55.7% had obesity, 52.5% had metabolic syndrome, 42.5% had both, and 34.3% had neither. After adjusting for age, sex, and burden of other metabolic syndrome-associated diagnoses, patients with HFpEF with obesity had lower odds of a diagnosis of other evaluated comorbidities relative to patients without obesity. The presence of metabolic syndrome in HFpEF appears to increase comorbidity burden as each additional metabolic syndrome-associated diagnosis was associated with higher odds of assessed comorbidities except atrial fibrillation. CONCLUSION: Obesity was common among patients with HFpEF and not always co-occurring with metabolic syndrome. Multivariable analysis suggested that patients with obesity may develop HFpEF in the absence of other driving factors such as cardiovascular disease or metabolic syndrome.

Comparison of COVID-19 and Influenza-Related Outcomes in the United States during Fall-Winter 2022-2023: A Cross-Sectional Retrospective Study.

Influenza and COVID-19 contribute significantly to the infectious disease burden during the respiratory season, but their relative burden remains unknown. This study characterizes the frequency and severity of medically attended COVID-19 and influenza during the peak of the 2022-2023 influenza season in the pediatric, adult, and older adult populations and characterizes the prevalence of underlying conditions among patients hospitalized with COVID-19. This cross-sectional analysis included individuals in the Veradigm EHR Database linked to Komodo claims data with a medical encounter between 1 October 2022 and 31 March 2023 (study period). Patients with medical encounters were identified with a diagnosis of COVID-19 or influenza during the study period and stratified based on the highest level of care received with that diagnosis. Among 23,526,196 individuals, there were more COVID-19-related medical encounters than influenza-related encounters, overall and by outcome. Hospitalizations with COVID-19 were more common than hospitalizations with influenza overall (incidence ratio = 4.6) and in all age groups. Nearly all adults hospitalized with COVID-19 had at least one underlying medical condition, but 37.1% of 0-5-year-olds and 25.0% of 6-17-year-olds had no underlying medical conditions. COVID-19 was associated greater burden than influenza during the peak of the 2022-2023 influenza season.

A global federated real-world data and analytics platform for research.

Objective: This article describes a scalable, performant, sustainable global network of electronic health record data for biomedical and clinical research. Materials and Methods: TriNetX has created a technology platform characterized by a conservative security and governance model that facilitates collaboration and cooperation between industry participants, such as pharmaceutical companies and contract research organizations, and academic and community-based healthcare organizations (HCOs). HCOs participate on the network in return for access to a suite of analytics capabilities, large networks of de-identified data, and more sponsored trial opportunities. Industry participants provide the financial resources to support, expand, and improve the technology platform in return for access to network data, which provides increased efficiencies in clinical trial design and deployment. Results: TriNetX is a growing global network, expanding from 55 HCOs and 7 countries in 2017 to over 220 HCOs and 30 countries in 2022. Over 19 000 sponsored clinical trial opportunities have been initiated through the TriNetX network. There have been over 350 peer-reviewed scientific publications based on the network's data. Conclusions: The continued growth of the TriNetX network and its yield of clinical trial collaborations and published studies indicates that this academic-industry structure is a safe, proven, sustainable path for building and maintaining research-centric data networks.

Federated Electronic Health Record Database via a Public-Private Partnership to Enhance Health Care Equity by Disparity Discovery and Equitable Clinical Trial Recruitment.

Despite increasingly stringent requirements from regulatory agencies, clinical trials often fail to recruit study populations representative of real-world demographics and disease prevalence and are often skewed away from racial/ethnic minorities. Consequently, data produced by such trials can result in treatment guidelines and outcome expectations that do not apply to racial/ethnic minorities, further widening health disparities. In this study, we describe a new tool, the TriNetX Diversity Lens ("Diversity Lens"), which augments the existing electronic health record querying functionality of TriNetX and allows clinical trial sponsors to rapidly evaluate the potential impact of inclusion and exclusion criteria on the eligibility rates of different racial and ethnic groups. We describe the development of Diversity Lens in collaboration with public and private stakeholders. Additionally, we feature examples of how Diversity Lens can bring to the surface insights into existing health disparities and prospectively explore the impact of study criteria on the eligibility of racial/ethnic minorities.

Circulating tumor cells: clinically relevant molecular access based on a novel CTC flow cell.

BACKGROUND: Contemporary cancer diagnostics are becoming increasing reliant upon sophisticated new molecular methods for analyzing genetic information. Limiting the scope of these new technologies is the lack of adequate solid tumor tissue samples. Patients may present with tumors that are not accessible to biopsy or adequate for longitudinal monitoring. One attractive alternate source is cancer cells in the peripheral blood. These rare circulating tumor cells (CTC) require enrichment and isolation before molecular analysis can be performed. Current CTC platforms lack either the throughput or reliability to use in a clinical setting or they provide CTC samples at purities that restrict molecular access by limiting the molecular tools available. METHODOLOGY/PRINCIPAL FINDINGS: Recent advances in magetophoresis and microfluidics have been employed to produce an automated platform called LiquidBiopsy®. This platform uses high throughput sheath flow microfluidics for the positive selection of CTC populations. Furthermore the platform quantitatively isolates cells useful for molecular methods such as detection of mutations. CTC recovery was characterized and validated with an accuracy (<20% error) and a precision (CV<25%) down to at least 9 CTC/ml. Using anti-EpCAM antibodies as the capture agent, the platform recovers 78% of MCF7 cells within the linear range. Non specific recovery of background cells is independent of target cell density and averages 55 cells/mL. 10% purity can be achieved with as low as 6 CTCs/mL and better than 1% purity can be achieved with 1 CTC/mL. CONCLUSIONS/SIGNIFICANCE: The LiquidBiopsy platform is an automated validated platform that provides high throughput molecular access to the CTC population. It can be validated and integrated into the lab flow enabling CTC enumeration as well as recovery of consistently high purity samples for molecular analysis such as quantitative PCR and Next Generation Sequencing. This tool opens the way for clinically relevant genetic profiling of CTCs.