Toward Individual Treatment in Cervical Artery Dissection: Subgroup Analysis of the TREAT-CAD Randomized Trial.

Annals of neurology(2024)

引用 0|浏览6
暂无评分
摘要
OBJECTIVE:Uncertainty remains regarding antithrombotic treatment in cervical artery dissection. This analysis aimed to explore whether certain patient profiles influence the effects of different types of antithrombotic treatment. METHODS:This was a post hoc exploratory analysis based on the per-protocol dataset from TREAT-CAD (NCT02046460), a randomized controlled trial comparing aspirin to anticoagulation in patients with cervical artery dissection. We explored the potential effects of distinct patient profiles on outcomes in participants treated with either aspirin or anticoagulation. Profiles included (1) presenting with ischemia (no/yes), (2) occlusion of the dissected artery (no/yes), (3) early versus delayed treatment start (median), and (4) intracranial extension of the dissection (no/yes). Outcomes included clinical (stroke, major hemorrhage, death) and magnetic resonance imaging outcomes (new ischemic or hemorrhagic brain lesions) and were assessed for each subgroup in separate logistic models without adjustment for multiple testing. RESULTS:All 173 (100%) per-protocol participants were eligible for the analyses. Participants without occlusion had decreased odds of events when treated with anticoagulation (odds ratio [OR] = 0.28, 95% confidence interval [CI] = 0.07-0.86). This effect was more pronounced in participants presenting with cerebral ischemia (n = 118; OR = 0.16, 95% CI = 0.04-0.55). In the latter, those with early treatment (OR = 0.26, 95% CI = 0.07-0.85) or without intracranial extension of the dissection (OR = 0.34, 95% CI = 0.11-0.97) had decreased odds of events when treated with anticoagulation. INTERPRETATION:Anticoagulation might be preferable in patients with cervical artery dissection presenting with ischemia and no occlusion or no intracranial extension of the dissection. These findings need confirmation. ANN NEUROL 2024.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要