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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.

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.

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.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 (

Abstract 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.