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从原则到实践:缩小患者分析的差距。

From principle to practice: bridging the gap in patient profiling.

机构信息

Department of Biochemistry, University of Vermont, Burlington, Vermont, United States of America.

出版信息

PLoS One. 2013;8(1):e54728. doi: 10.1371/journal.pone.0054728. Epub 2013 Jan 25.

Abstract

The standard clinical coagulation assays, activated partial thromboplastin time (aPTT) and prothrombin time (PT) cannot predict thrombotic or bleeding risk. Since thrombin generation is central to haemorrhage control and when unregulated, is the likely cause of thrombosis, thrombin generation assays (TGA) have gained acceptance as "global assays" of haemostasis. These assays generate an enormous amount of data including four key thrombin parameters (lag time, maximum rate, peak and total thrombin) that may change to varying degrees over time in longitudinal studies. Currently, each thrombin parameter is averaged and presented individually in a table, bar graph or box plot; no method exists to visualize comprehensive thrombin generation data over time. To address this need, we have created a method that visualizes all four thrombin parameters simultaneously and can be animated to evaluate how thrombin generation changes over time. This method uses all thrombin parameters to intrinsically rank individuals based on their haemostatic status. The thrombin generation parameters can be derived empirically using TGA or simulated using computational models (CM). To establish the utility and diverse applicability of our method we demonstrate how warfarin therapy (CM), factor VIII prophylaxis for haemophilia A (CM), and pregnancy (TGA) affects thrombin generation over time. The method is especially suited to evaluate an individual's thrombotic and bleeding risk during "normal" processes (e.g pregnancy or aging) or during therapeutic challenges to the haemostatic system. Ultimately, our method is designed to visualize individualized patient profiles which are becoming evermore important as personalized medicine strategies become routine clinical practice.

摘要

标准的临床凝血检测,如活化部分凝血活酶时间(aPTT)和凝血酶原时间(PT),无法预测血栓形成或出血风险。由于凝血酶生成是止血的核心,当不受调节时,可能是血栓形成的原因,凝血酶生成检测(TGA)已作为止血的“整体检测”得到认可。这些检测会产生大量数据,包括四个关键的凝血酶参数(lag time、最大速率、峰值和总凝血酶),这些参数在纵向研究中可能随时间发生不同程度的变化。目前,每个凝血酶参数都进行平均处理,并在表格、柱状图或箱线图中单独呈现;没有方法可以可视化随时间变化的综合凝血酶生成数据。为了解决这个需求,我们创建了一种同时可视化所有四个凝血酶参数的方法,并可以进行动画处理,以评估凝血酶生成随时间的变化。这种方法使用所有凝血酶参数来根据个体的止血状态进行内在排序。凝血酶生成参数可以使用 TGA 经验性地得出,也可以使用计算模型(CM)进行模拟。为了证明我们方法的实用性和广泛适用性,我们展示了华法林治疗(CM)、血友病 A 因子 VIII 预防(CM)和妊娠(TGA)如何随时间影响凝血酶生成。该方法特别适合评估个体在“正常”过程(如妊娠或衰老)或在对止血系统进行治疗性挑战期间的血栓形成和出血风险。最终,我们的方法旨在可视化个体化患者的概况,随着个性化医疗策略成为常规临床实践,这些概况变得越来越重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af32/3556038/3c902932721e/pone.0054728.g001.jpg

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