Endotypes of thrombocytopenia in the critically ill

危重症患者血小板减少症的内型

基本信息

批准号：
9307982
负责人：
Gilles Clermont
金额：
$ 18.02万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-07-01 至 2020-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9307982
关键词：
Acute Acute Lung Injury Acute Renal Failure with Renal Papillary Necrosis Admission activity Animals Attention Basic Science Biological Assay Blood Blood Coagulation Factor Blood Platelets Blood Vessels Breathing Caring Cell Communication Cells Chronic Disease Clinical Coagulation Process Collection Complex Computer Simulation Critical Illness Data Data Sources Databases Diagnosis Disease Disease Outcome Effector Cell Electronic Health Record Endothelium Etiology Event Evolution Formulation Four-dimensional Hemorrhage Hemostatic Agents Hemostatic function Hospitals Immune Immune response Inflammation Inflammatory Inflammatory Response Injury Intensive Care Intensive Care Units Intervention Knowledge Leukocytes Ligands Link Machine Learning Maps Mediator of activation protein Medical center Modeling Morbidity - disease rate Neoplasm Metastasis Operative Surgical Procedures Organ Outcome Participant Pathway interactions Patients Pattern Phenotype Physiology Plant Roots Platelet Activation Platelet Count measurement Platelet aggregation Play Population Process Prothrombin time assay Reaction Recruitment Activity Research Role Sentinel Sepsis Series Severity of illness Signal Transduction Site Solid Source Statistical Models Structure Surface System Therapeutic Thrombocytopenia Thromboembolism Thrombosis Thrombus Time Tissues Trauma Trauma patient Traumatic injury Uncertainty Universities Venous attenuation base burden of illness cell type cohort demographics density design individual patient mortality prevent response tool

项目摘要

Thrombocytopenia is extremely frequent in critically ill patients. However, the role of acute platelet responses in critically ill patients is not well studied, and the multifactorial etiology of thrombocytopenia in the ICU makes it difficult to understand, or understand whether or not to treat it. In several situations such as traumatic injury or sepsis, very low platelet counts have been to bleeding, thrombosis and end-organ injury. Platelets have been extensively studied as a key component of hemostasis, but a rapidly emerging concept is that platelets are also key effector cells in systemic inflammatory processes as both instigators of local and systemic inflammatory reactions and also participants in the inflammation that contributes to tissue injury. The link between platelets and inflammation is complex and bidirectional, as inflammatory ligands have been shown to regulate platelet function and activated platelets induce inflammatory responses in other cell types. The overarching theme of this proposal is to study platelet dynamics in critically ill patients, construct clinical endotypes of thrombocytopenia in this population, and to relate these endotypes to underlying mesoscale mechanisms through computational modeling. We will use a large electronic health record-based database and a tri-state trauma database as source data to construct these endotypes. We define endotype as clinical patterns defined along four dimensions: (1) baseline information (demographic, chronic disease burden, severity of illness and admitting diagnosis), (2) features of the platelet count time series (rate of decrease, nadir, etc.), (3) concurrent interventions, and (4) outcome. The computational approach will attempt to root clinical endotypes in mechanistic interpretations (or collections of alternative interpretations), contributing to focus basic science investiagtions, and to close key knowledge gaps preventing the design and use of targeted anti-platelet-inflammatory therapies in the critically ill. Computational models will be developed at different levels of complexity, with a specific attention to tie underlying mechanisms to functional assays routinely performed in thrombocytopenic patients, such as prothrombin time, activated coagulation time, and thromboelastogram.

在重症患者中，血小板减少症极为常见。但是，急性血小板反应在重症患者的研究尚未得到很好的研究，ICU中血小板减少症的多因素病因使其很难了解或了解是否对待它。在几种情况下，例如创伤性损伤或败血症，非常低血小板计数一直是出血，血栓形成和最终器官损伤。血小板已被广泛研究为钥匙止血的成分，但一个快速新兴的概念是血小板也是全身性效应细胞炎症过程是局部和系统性炎症反应的煽动者，也是参与者炎症会导致组织损伤。血小板与炎症之间的联系是复杂且双向的，由于已显示炎症配体可以调节血小板功能，并激活血小板会诱发炎症其他细胞类型的响应。该提案的总体主题是研究重病的血小板动力学患者，在该人群中构建血小板减少症的临床内型，并将这些内型与通过计算建模来实现介质机制。我们将使用大型电子健康记录数据库和三态创伤数据库作为来源数据，以构建这些内型。我们将内型定义为临床沿着四个维度定义的模式：（1）基线信息（人口统计学，慢性病负担，严重程度疾病和诊断），（2）血小板计数时间序列的特征（减少率，Nadir等），（3）并发干预措施和（4）结果。计算方法将尝试在机械解释（或替代解释的集合），有助于集中基础科学 Investiagtions，并填补关键知识差距，以防止针对性的抗植物炎症设计和使用重病的治疗。计算模型将以不同的复杂性开发，具体注意与在血小板减少患者中通常执行的功能测定的基本机制，例如凝血酶蛋白时间，激活的凝结时间和血栓图像造影。