Screening Technology and Outcomes Project in Stroke

描述（申请后）：拟议的研究是一项为期4年的研究，涉及600例缺血性卒中患者，旨在评估新的神经影像学技术在急性环境中的效用，以改善卒中结局的预测。目前，来自标准成像研究的数据，即大脑的非对比计算机断层扫描（CT）扫描，几乎没有增加 中风严重程度的临床测量。在大多数缺血性卒中病例中，研究正常。相比之下，功能性卒中的结局在患者之间差异很大，并受卒中的大小、部位和亚型的影响。预后通常是确定后，诊断测试，包括脑成像，是在病人的过程中进行？的住院时间。 然而，关于急性治疗选择和资源分配的风险/受益特征的决定发生在卒中后的最初几个小时。如果早期诊断研究能够预测结果并直接影响急性管理，则卒中对患者以及医疗保健系统的成本可能是可以改变的。 在一项仅需几分钟的研究中，新型超快速多通道CT（MDCT）扫描仪结合非造影剂脑计算机断层扫描（CT）、头颈部计算机断层扫描血管造影（CTA）和计算机断层扫描脑组织灌注（CTP），可对中风患者进行紧急评估。再加上仔细的临床评估，这一“下一个 新一代的成像技术有可能识别中风的血管原因和处于危险中的精确大脑区域，在患者发病后一小时内确定预后。他到达了急诊室。拟议的研究旨在更好地定义影响中风特定亚型临床和经济成本的特征，并对此进行测试 新的成像技术在紧急情况下的能力，以预测长期病人的结果。为此，申请人制定了三个具体目标。首先，研究者将确定急性缺血性卒中的测试性能特征（灵敏度、特异性） 使用基于众所周知的吐司（Organon 10172急性卒中治疗试验）标准的最终临床诊断作为金标准，使用MDCT神经成像预测那些最可能具有不良结局的患者。其次，研究人员将确定MDCT在预测脑梗死方面是否上级传统的非对比剂脑计算机断层扫描。 中风的功能结果。第三，将根据中风亚型、治疗、合并症、中风大小和位置的贡献开发中风成本的预测模型。经济模型将建立一种方法来衡量创新的中风管理，诊断测试和治疗的成本效益。 这项研究将允许开发基于不同亚型中风的成本和结果的经济模型。它将使功能结果的早期诊断，改善临床医生？在中风发作后的几个小时内做出困难的治疗决定的能力，并作为卫生保健资源分配的指导。

DESCRIPTION (after the Application): The proposed research is a four-year study of 600 ischemic stroke patients which is designed to evaluate the utility of new neuroimaging technology in the acute setting to improve prediction of stroke outcome. Currently, data from the standard imaging study, a non-contrast computed tomography (CT) scan of the brain, add little to clinical measures of stroke severity. In the majority of ischemic stroke cases, the study is normal. In contrast, functional stroke outcome varies dramatically among patients and is affected by the size, location and subtype of stroke. Prognosis is usually determined after diagnostic tests, including brain imaging, are performed over the course of the patient?s hospital stay. However, decisions regarding the risk/benefit profile of acute treatment options and resource allocation occur in the first hours after stroke. The costs of stroke, to the patient as well as to the healthcare system, are potentially modifiable if early diagnostic studies are able to predict outcome and directly impact on acute management. In a study that takes only minutes, new, ultra-fast multidector CT (MDCT) scanners enable the emergency evaluation of stroke patients, combining non-contrast brain computerized tomography (CT), computed tomographic angiography of the head and neck (CTA), and computed tomographic brain tissue perfusion (CTP). Coupled with careful clinical assessment, this "next generation" imaging technology has the potential to identify both the vascular cause of the stroke and the precise brain regions at risk, establishing the prognosis within an hour of the patient?s arrival in the emergency ward. The proposed research seeks to better define the characteristics affecting the clinical and financial costs of specific subtypes of strokes and to test this new imaging technology in the emergency setting for its ability to predict long term patient outcome. To this end, the applicant has developed three specific aims. First, investigators will determine the test performance characteristics (sensitivity, specificity) of acute ischemic stroke neuroimaging with MDCT in predicting those patients most likely to have poor outcome using the final clinical diagnosis based on the well known TOAST (Trial of Organon 10172 in Acute Stroke Treatment) criteria as the gold standard. Second, investigators will determine whether MDCT is superior to conventional non-contrast brain computerized tomography alone in predicting functional outcome from stroke. Third, a predictive model will be developed of stroke cost based on the contributions of subtype of strokes, treatments, co-morbidities, stroke size and location. The economic model will establish a means to measure the cost effectiveness of innovative stroke management, diagnostic testing, and therapies. This research will allow develop of economic models based on the costs and outcomes of different subtype of strokes. It will enable early prognostication of functional outcome, improving the clinician?s ability to make difficult treatment decisions in the hours after stroke onset, and serve as a guide for the allocation of health care resources.