Targeted treatment for acute stroke: development of prognostic models and decision support tools

中风是世界第二大杀手，最常见的原因是血液凝块堵塞了脑血管。溶解或防止血栓形成的药物提高了中风后康复的机会，但也增加了出血的机会；当出血进入大脑时，出血尤其严重。大多数中风患者需要在疾病的某个时候服用影响血液凝结的药物，从强效的抗血栓药物到风险较低的药物，如阿司匹林。如果医生能够可靠地选择哪些患者得到了帮助，而不是受到这些药物的伤害，这将是一大进步。我希望开发一种方法来预测哪些中风患者更有可能受到(出血)的伤害，而不是从影响凝血的药物中受益(通过避免形成血栓)。我将使用统计方法进行预测，然后探索医生和患者使用它们的最佳方式。这将为每个患者带来更好的决定，以及更好的治疗政策。这项研究将使用现有方法以及新技术(例如血液测试和脑成像)的最佳信息，以确保为每个中风患者做出有效和个性化的决定

Stroke, the world‘s second biggest killer, is most often due to a blockage of a brain blood vessel by blood clot. Drugs that dissolve clots or prevent them from forming improve the chance of recovery after stroke, but they also increase the chance of bleeding; when bleeds occur into the brain they are particularly severe. Most stroke patients need to take drugs that affect blood clotting at some point in their illness, ranging from potent ‘clot busting‘ drugs to less risky drugs like aspirin.If a doctor could reliably select which patients were helped rather than harmed by these drugs, this would be a big step forward. I hope to develop a method to predict which stroke patients are more likely to be harmed (by bleeding) than benefit (by avoiding forming blood clots) from medicines that affect clotting. I will use statistical methods to make predictions, and then explore the best way for doctors and patients to use them. This will lead to better decisions for each individual patient, and better treatment policies. This study will use the best information from existing methods as well as from newer technologies (e.g. blood tests and brain imaging) to ensure effective and personalised decisions for each stroke patient