Current guidelines on antiplatelet agents for secondary prevention of noncardiogenic stroke: an evidence-based review
Abstract
Antiplatelet therapy is a mainstay of secondary prevention of ischemic strokes. Recent studies, such as Prevention Regimen for Effectively Avoiding Second Strokes (PRoFESS), the Clopidogrel for High Atherothrombotic Risk and Ischemic Stabilization, Management, and Avoidance (CHARISMA) trial, and the European/Australasian Stroke Prevention in Reversible Ischaemia Trial (ESPRIT), have added much to our understanding about how best to utilize the various antiplatelet agents available. Aspirin has been shown to reduce the risk of recurrent strokes, and the combination of aspirin and dipyridamole has repeatedly been shown to outperform aspirin alone. Recently, clopidogrel was demonstrated to be "noninferior" to an aspirin/dipyridamole combination, and can be considered as a first-line agent. The American Stroke Association and American Heart Association have clear recommendations on how to utilize these agents.
Read the paper
Related studies
- Combining in silico and in vitro approaches to identification of potent inhibitor against phospholipase A2 (PLA2)
- In silico and in vitro studies: investigating the chemical composition, DFT, molecular docking, and dynamic simulation of Satureja candidissima (Munby) Briq essential oil as a potential antibacterial agent
- Quercetin combined with ciprofloxacin and gentamicin inhibits biofilm formation and virulence in Staphylococcus aureus
- In silico study of the mechanism of action, pharmacokinetic and toxicological properties of some N-methylanthranilates and their analogs
- Anticonvulsant Effects of Citronellal, Daidzin, and Phytol, Possibly Through GABAA Receptor and Voltage-Gated Sodium Channel Interaction Pathways: In Vivo and In Silico Studies
- 2-Phenylcyclopropylmethylamine (PCPMA) Derivatives as D3R-Selective Ligands for 3D-QSAR, Docking and Molecular Dynamics Simulation Studies
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.