Triple Therapy for Atrial Fibrillation and Percutaneous Coronary Intervention : A Contemporary Review

Chronic oral anticoagulant therapy is recommended (class I) in patients with mechanical heart valves and in patients with atrial fibrillation with a CHA₂DS₂-VASc (Congestive heart failure, Hypertension, Age ≥75 years, Diabetes mellitus, prior Stroke or transient ischemic attack or thromboembolism, Vascular disease, Age 65 to 74 years, Sex category) score ≥1. When these patients undergo percutaneous coronary intervention with stenting, treatment with aspirin and a P2Y₁₂ receptor inhibitor also becomes indicated. Before 2014, guidelines recommended the use of triple therapy (vitamin K antagonists, aspirin, and clopidogrel) for these patients. However, major bleeding is increasingly recognized as the Achilles’ heel of the triple therapy regimen. Lately, various studies have investigated this topic, including a prospective randomized trial, and the evidence for adding aspirin to the regimen of vitamin K antagonists and clopidogrel seems to be weakened. In this group of patients, the challenge is finding the optimal equilibrium to prevent thromboembolic events, such as stent thrombosis and thromboembolic stroke, without increasing bleeding risk.     

On instabilities of deep learning in image reconstruction and the potential costs of AI

Deep learning, due to its unprecedented success in tasks such as image classification, has emerged as a new tool in image reconstruction with potential to change the field. In this paper, we demonstrate a crucial phenomenon: Deep learning typically yields unstable methods for image reconstruction. The instabilities usually occur in several forms: 1) Certain tiny, almost undetectable perturbations, both in the image and sampling domain, may result in severe artefacts in the reconstruction; 2) a small structural change, for example, a tumor, may not be captured in the reconstructed image; and 3) (a counterintuitive type of instability) more samples may yield poorer performance. Our stability test with algorithms and easy-to-use software detects the instability phenomena. The test is aimed at researchers, to test their networks for instabilities, and for government agencies, such as the Food and Drug Administration (FDA), to secure safe use of deep learning methods.     

Biological variability of cell-free DNA in healthy females at rest within a short time course

International Journal of Legal Medicine - Alterations in cell-free DNA concentration (cfDNA) over time have been studied in diseased or injured patients or analyzed in athletes during exhaustive...