BACKGROUND The SPAN trial (Stroke Preclinical Assessment Network) is the largest preclinical study testing acute stroke interventions in experimental focal cerebral ischemia using endovascular filament middle cerebral artery occlusion (MCAo). Besides testing interventions against controls, the prospective design captured numerous biological and procedural variables, highlighting the enormous heterogeneity introduced by the multicenter structure that might influence stroke outcomes. Here, we leveraged the unprecedented sample size achieved by the SPAN trial and the prospective design to identify the biological and procedural variables that affect experimental stroke outcomes in transient endovascular filament MCAo. METHODS The study cohort included all mice enrolled and randomized in the SPAN trial (N=1789). Mice were subjected to 60-minute MCAo and followed for a month. Thirteen biological and procedural independent variables and 4 functional (weight loss and 4-point neuroscore on days 1 and 2, corner test on days 7 and 28, and mortality) and 3 tissue (day 2, magnetic resonance imaging infarct volumes and swelling; day 30, magnetic resonance imaging tissue loss) outcome variables were prospectively captured. Multivariable regression with stepwise elimination was used to identify the predictors and their effect sizes. RESULTS Older age, active circadian stage at MCAo, and thinner and longer filament silicone tips predicted higher mortality. Older age, larger body weight, longer anesthesia duration, and longer filament tips predicted worse neuroscores, while high-fat diet and blood flow monitoring predicted milder neuroscores. Older age and a high-fat diet predicted worse corner test performance. While shorter filament tips predicted more ipsiversive turning, longer filament tips appeared to predict contraversive turning. Age, sex, and weight interacted when predicting the infarct volume. Older age was associated with smaller infarcts on day 2 magnetic resonance imaging, especially in animals with larger body weights; this association was most conspicuous in females. High-fat diet also predicted smaller infarcts. In contrast, the use of cerebral blood flow monitoring and more severe cerebral blood flow drop during MCAo, longer anesthesia, and longer filament tips all predicted larger infarcts. Bivariate analyses among the dependent variables highlighted a disconnect between tissue and functional outcomes. CONCLUSIONS Our analyses identified variables affecting endovascular filament MCAo outcome, an experimental stroke model used worldwide. Multiple regression refuted some commonly reported predictors and revealed previously unrecognized associations. Given the multicenter prospective design that represents a sampling of real-world conditions, the degree of heterogeneity mimicking clinical trials, the large number of predictors adjusted for in the multivariable model, and the large sample size, we think this is the most definitive analysis of the predictors of preclinical stroke outcome to date. Future multicenter experimental stroke trials should standardize or at least ensure a balanced representation of the biological and procedural variables identified herein as potential confounders.

中文翻译：

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中风临床前评估网络 （SPAN） 试验结果的生物学和程序预测因子。


背景 SPAN 试验（中风临床前评估网络）是最大的临床前研究，使用血管内细丝大脑中动脉闭塞 （MCAo） 测试急性中风干预实验性局灶性脑缺血。除了针对对照测试干预措施外，前瞻性设计还捕获了许多生物学和程序变量，突出了可能影响卒中结果的多中心结构引入的巨大异质性。在这里，我们利用 SPAN 试验和前瞻性设计实现的前所未有的样本量来确定影响瞬时血管内细丝 MCAo 实验性卒中结果的生物学和程序变量。方法 研究队列包括所有在 SPAN 试验中入组和随机分配的小鼠 （N=1789）。小鼠接受 60 分钟的 MCAo 并随访一个月。前瞻性捕获 13 个生物和程序自变量和 4 个功能变量 （第 1 天和第 2 天的体重减轻和 4 分神经评分，第 7 天和第 28 天的角落测试，以及死亡率）和 3 个组织 （第 2 天，磁共振成像梗死体积和肿胀;第 30 天，磁共振成像组织损失）结果变量。使用逐步消除的多变量回归来确定预测变量及其效应大小。结果 年龄较大、MCAo 的昼夜节律活跃阶段以及更细和更长的细丝硅胶尖端预示着更高的死亡率。年龄较大、体重较大、麻醉持续时间较长和细丝尖端较长预示着神经评分较差，而高脂肪饮食和血流监测预测神经评分较轻。年龄较大和高脂肪饮食预示着角测试表现较差。 虽然较短的细丝尖端预测了更多的逆向转弯，但较长的细丝尖端似乎预示着逆向转弯。年龄、性别和体重在预测梗死体积时相互作用。在第 2 天磁共振成像中，年龄较大与较小的梗死相关，尤其是在体重较大的动物中;这种关联在女性中最为明显。高脂肪饮食也预示着较小的梗死。相比之下，使用 脑血流监测 和 MCAo 期间更严重的脑血流下降、更长的麻醉时间和更长的细丝尖端都预示着更大的梗死。因变量之间的双变量分析突出了组织和功能结果之间的脱节。结论 我们的分析确定了影响血管内细丝 MCAo 结果的变量，这是一种在全球范围内使用的实验性卒中模型。多元回归反驳了一些常见的预测变量，并揭示了以前未被识别的关联。鉴于代表真实世界条件样本的多中心前瞻性设计、模拟临床试验的异质性程度、在多变量模型中调整的大量预测因子以及大样本量，我们认为这是迄今为止对临床前卒中结果预测因子的最权威分析。未来的多中心实验性卒中试验应标准化或至少确保此处确定为潜在混杂因素的生物学和程序变量的平衡表示。