July 16, 2026

FDA Approves First Oral PCSK9 Inhibitor

Merck reported placebo-adjusted LDL-C reductions of 56% and 59% at week 24 in two phase 3 CORALreef trials supporting the approval.

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July 15, 2026

Serostatus May Modify RA Activity–CV Link

Combined rheumatoid factor and anticitrullinated protein antibody status appeared to modify the association between baseline rheumatoid arthritis disease activity and subsequent cardiovascular events in an international observational cohort.

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July 13, 2026

New CDC Report Tracks US Mortality Trends

The annual provisional report summarizes changes in mortality rates, demographic patterns, and leading causes of death during 2025.

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July 02, 2026

Hemodynamic Instability in Intubation May Be Predictable

Narrative review describes how physiologic stressors accumulate from induction through postintubation care and may contribute to cardiovascular deterioration during airway management.

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June 30, 2026

How Does Social Media Influence Health Decisions?

National survey findings suggest many US adults report making health decisions based on social media despite widespread concerns about the accuracy of health information shared to the platforms.

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June 26, 2026

ASE Plenary: Progress, Priorities, and What’s Next

Efforts to align, sustain, and engage drove a year of growth for ASE.

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June 26, 2026

Gout May Signal Higher Stroke Risk in AF

In a nationwide Finnish cohort, patients with atrial fibrillation and gout had higher ischemic stroke rates, while urate-lowering therapy was associated with lower stroke rates.

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June 23, 2026

Lactate Biomarker May Predict Outcomes in Cardiogenic Shock

A review of cardiogenic shock studies suggests serial lactate measurements provide more prognostic information than isolated values and may better reflect treatment response.

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June 22, 2026

FDA Cites Manufacturing Issues for Cytisinicline

Application supported by Phase 3 smoking-cessation data and long-term safety findings.

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June 22, 2026

Coronary Model Shows Limits in Cath-Referred Patients

An interpretable machine-learning model classified angiographic coronary artery disease in patients referred for coronary angiography, but high disease prevalence and unclear inflammatory signals limited clinical interpretation.

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