Effective Reserve: A Latent Variable to Improve Outcome Prediction in Stroke.
Effective Reserve: A Latent Variable to Improve Outcome Prediction in Stroke.
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有效储备：改善中风结果预测的潜在变量。
DOI：
10.1016/j.jstrokecerebrovasdis.2018.09.003
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
RostMdMphFaan,NataliaS
中科院分区：
文献类型：
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作者：
Schirmer,MarkusD;EthertonMdPhD,MarkR;DalcaPhD,AdrianV;GieseMd,Anne-Katrin;CloonanMSc,Lisa;WuPhD,Ona;GollandPhD,Polina;RostMdMphFaan,NataliaS
根据最初的表现预测卒中后的功能结果仍然是一个开放的挑战，这表明这些预测模型中缺少一个重要的方面。存在一种被称为大脑储备的保护机制的概念，它可能被用来理解疾病结局的变化。在这项工作中，我们扩展了脑储备(有效储备)的概念，以改进急性缺血性中风(AIS)后功能预后的预测模型。连续接受急性脑磁共振成像(48小时)的AIS患者符合这项研究的条件。分别在T2液体衰减反转恢复像和弥散加权像上测量脑白质高信号和急性脑梗塞体积。于卒中后90d行改良Rankin量表评分。使用结构方程模型将有效储备定义为潜在变量，包括年龄、收缩压和颅内容量测量。在453例AIS患者(平均年龄66.6±14.7岁)中，36%为男性，311例为高血压。有效储备与90天改良朗金量表评分呈负相关(路径系数−为0.18±0.01，P<；0.01)。与没有有效储备的模型相比，在基于有效储备的模型中，预测和观察的修正兰金量表得分之间的相关性得到改善(Spearman‘sρ为0.29±0.18vs.0.15±0.17，P<；.001)。此外，高血压患者的有效储备较低(P<；10−6)。在卒中结局预测模型中使用有效储备是可行的，并导致更好的模型性能。此外，更高的有效储备与更有利的卒中后功能性结局相关，并可能与总体上更好的血管健康状况相对应。
Prediction of functional outcome after stroke based on initial presentation remains an open challenge, suggesting that an important aspect is missing from these prediction models. There exists the notion of a protective mechanism called brain reserve, which may be utilized to understand variations in disease outcome. In this work, we expand the concept of brain reserve (effective reserve) to improve prediction models of functional outcome after acute ischemic stroke (AIS). Consecutive AIS patients with acute brain magnetic resonance imaging (<48 hours) were eligible for this study. White matter hyperintensity and acute infarct volume were determined on T2 fluid attenuated inversion recovery and diffusion weighted images, respectively. Modified Rankin Scale scores were obtained at 90days poststroke. Effective reserve was defined as a latent variable using structural equation modeling by including age, systolic blood pressure, and intracranial volume measurements. Of 453 AIS patients (mean age 66.6 ± 14.7 years), 36% were male and 311 hypertensive. There was inverse association between effective reserve and 90-day modified Rankin Scale scores (path coefficient −0.18 ± 0.01,P< .01). Compared to a model without effective reserve, correlation between predicted and observed modified Rankin Scale scores improved in the effective-reserve-based model (Spearman's ρ 0.29 ± 0.18 versus 0.15 ± 0.17,P< .001). Furthermore, hypertensive patients exhibited lower effective reserve (P< 10−6). Using effective reserve in prediction models of stroke outcome is feasible and leads to better model performance. Furthermore, higher effective reserve is associated with more favorable functional poststoke outcome and might correspond to an overall better vascular health.