在COVID-19患者中与PCR诊断相关的纵向实验室测试揭示了独特凝血病特征的时间演变
Longitudinal laboratory testing tied to PCR diagnostics in COVID-19 patients reveals temporal evolution of distinctive coagulopathy signatures
摘要：
从实验室检测结果及其与临床结果的三角测量中进行时间推断，如电子健康记录（EHR）中提供者注释的相关非结构化文本中所述，是推进精准医学不可或缺的一部分。在这里，我们研究了181名COVID阳性患者和7，775名COVID阴性患者，在为期两个月的观察期内，他们在194次检测中接受了130万次实验室检测，观察期以SARS-CoV-2 PCR检测日期为中心。我们发现，与临床表现和诊断测试时的COVID阴性患者相比，COVID阳性患者往往具有较高的血浆纤维蛋白原水平和类似的低血小板计数，两个队列中约25%的患者显示完全血小板减少症。然而，随着感染的发展，这些指标显示出相反的纵向趋势，与COVID阴性队列相比，纤维蛋白原下降，血小板计数增加，分别达到更低和更高的水平。我们的EHR增强治疗工作表明，少数患者在PCR检测日期后发生血栓栓塞事件，包括罕见的弥漫性血管内凝血病（DIC）病例，大多数患者缺乏通常在消耗性凝血病中观察到的血小板减少。这些时间趋势首次通过数字框架呈现了COVID-19相关凝血病（CAC）的细粒度分辨率，该框架将纵向实验室测量与结构化药物数据和神经网络驱动的非结构化EHR结果提取相结合。这项研究证明了精准医学平台如何帮助每个患者随着时间的推移了解特定的凝血特征，以实现更好地个性化血栓预防方案的目标。
英文摘要：
Temporal inference from laboratory testing results and their triangulation with clinical outcomes as described in the associated unstructured text from the providers notes in the Electronic Health Record (EHR) is integral to advancing precision medicine. Here, we studied 181 COVIDpos and 7,775 COVIDneg patients subjected to 1.3 million laboratory tests across 194 assays during a two-month observation period centered around their SARS-CoV-2 PCR testing dates. We found that compared to COVIDneg at the time of clinical presentation and diagnostic testing, COVIDpos patients tended to have higher plasma fibrinogen levels and similarly low platelet counts, with approximately 25% of patients in both cohorts showing outright thrombocytopenia. However, these measures show opposite longitudinal trends as the infection evolves, with declining fibrinogen and increasing platelet counts to levels that are lower and higher compared to the COVIDneg cohort, respectively. Our EHR augmented curation efforts suggest a minority of patients develop thromboembolic events after the PCR testing date, including rare cases with disseminated intravascular coagulopathy (DIC), with most patients lacking the platelet reductions typically observed in consumptive coagulopathies. These temporal trends present, for the first time, fine-grained resolution of COVID-19 associated coagulopathy (CAC), via a digital framework that synthesizes longitudinal lab measurements with structured medication data and neural network-powered extraction of outcomes from the unstructured EHR. This study demonstrates how a precision medicine platform can help contextualize each patients specific coagulation profile over time, towards the goal of informing better personalization of thromboprophylaxis regimen.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
