The University of Iowa Stroke Preclinical Assessment Network to Support Translational Studies for Acute Cerebroprotection

项目摘要 爱荷华大学(UIowa)准备推进急性脑损伤患者的脑保护领域 保留作为美国国立卫生研究院卒中前临床评估网络(SPAN)的一个地点的缺血性卒中，S 翻译研究基础设施，高效地进行严谨和创新的比较研究 再灌流背景下的脑保护。UIowa-SPAN一贯遵循严格的、临床的 类似试验的方法，以避免过去脑保护研究的方法错误。具体来说，我们 使用随机化、盲目干预、独立结果判断和意向治疗分析 来解读和报道我们的动物研究。我们还解决了性和合并症的影响，以增加 我们研究的翻译价值。UIowa-SPAN汇集了一支由基础和翻译人员组成的团队 将技术专业知识与物流相结合的科学家。这导致了在 SPAN的第一次迭代，始终如一地引领网络的注册效率，同时产生 基于指标的最高质量数据。如果我们被选为 网站在新的网络迭代中。值得注意的是，UIowa-SPAN的目标与UIowa的目标一致 StrokeNet区域协调中心，NIH临床试验网络，使命是识别和 测试前景看好的中风疗法。我们还提出了跨度的多个方面的创新， 包括将总体数据变异性降至最低，血栓啮齿动物模型的技术改进，以及 改进当前成果衡量的内部有效性，使用人工智能 解释转角测试和网格行走测试的替代计算方法。我们的目标是严格地 并有效地确定哪些脑保护干预措施可能在临床试验中成功，以便 改善80万美国中风患者的预后，目前正在接受 效果有限的再灌注策略。

Project Summary The University of Iowa (UIowa) is poised to advance the field of cerebroprotection in patients with acute ischemic stroke by remaining as a site for the NIH Stroke Preclinical Assessment Network (SPAN)’s translational research infrastructure to efficiently conduct rigorous and innovative comparative studies of cerebroprotection in the context of reperfusion. UIowa-SPAN has consistently followed a rigorous, clinical trial-like approach to avoid the methodological mistakes of past cerebroprotection research. Specifically, we use randomization, blinded intervention, independent outcome adjudications, and intention-to-treat analyses to interpret and report our animal studies. We also address the effect of sex and comorbidities to increase the translational value of our research. UIowa-SPAN brings together a team of basic and translational scientists that integrates technical expertise with logistics. This has resulted in the top performance during the first iteration of SPAN, consistently leading the enrollment efficiency of the network while producing the highest quality data based on the metrics. We aim to maintain or exceed this performance if selected as a site in the new iteration of the network. Notably, the goals of UIowa-SPAN are aligned with those of UIowa’s regional coordinating center for StrokeNet, a NIH clinical trial network with the mission of identifying and testing promising stroke therapies. We are also proposing innovations to multiple aspects of the SPAN, including minimizing overall data variability, technical improvements in the embolic clot rodent model, and improvements to the internal validity of the current outcome measures, using artificial intelligence to interpret corner tests and alternative computation methods for the grid walk test. Our goal is to rigorously and efficiently identify which cerebroprotective interventions are likely to succeed in clinical trials in order to improve the outcomes of the 800,000 Americans who suffer a stroke and are currently treated with reperfusion strategies that have limited effectiveness.