Transfusion and Organ Dysfunction in Pediatric Septic Shock (TROPICS) study

小儿败血性休克 (TROPICS) 研究中的输血和器官功能障碍

• 批准号: 10367133
• 负责人: Jennifer Muszynski
• 金额: $ 86.57万
• 依托单位: RESEARCH INST NATIONWIDE CHILDREN'S HOSP
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-20 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10367133
• 关键词: Algorithms; Biological Markers; Blood Banks; Blood specimen; Cells; Characteristics; Child; Clinical; Clinical Trials; Collection; Complex; Computerized Medical Record; Critical Illness; Critically ill children; Data; Decision Making; Decision Modeling; Diagnostic Reagent Kits; Erythrocyte Transfusion; Erythrocytes; Evaluation; Face; Fostering; Functional disorder; Future; Goals; Guidelines; Harm Reduction; Health; Heme; Hemoglobin; Immune; Immunologic Tests; Immunology; Immunosuppression; Infant; Inflammation; Inflammatory; Intervention Trial; Learning; Machine Learning; Measures; Mediator of activation protein; Methods; Mission; Modeling; Morbidity - disease rate; Multi-Institutional Clinical Trial; Multi-site clinical study; Multiple Organ Failure; Observational Study; Organ; Outcome; Oxygen; Patients; Phenotype; Physiological; Physiology; Plasma; Precision medicine trial; Recommendation; Research; Risk; Sepsis; Septic Shock; Shock; Statistical Models; Techniques; Testing; Time; Transfusion; United States National Institutes of Health; adverse outcome; base; blood product; cohort; design; electronic data; extracellular vesicles; hemodynamics; immune function; improved; improved outcome; indexing; innovation; machine learning method; mortality; mortality risk; pediatric sepsis; personalized medicine; precision medicine; prevent; programs; prospective; response; septic; support tools; therapy design; transfusion medicine

Abstract Worldwide, nearly 3 million children die each year from sepsis. Red blood cells (RBC) are transfused in ~50% of children with septic shock, with the intent to enhance oxygen delivery, help resolve shock, and prevent organ dysfunction. However, RBC transfusion has repeatedly been associated with adverse outcomes in critical illness, suggesting harm. For most children with septic shock we lack data to identify who should or should not be transfused. Interventional trials and RBC transfusion guidelines have used hemoglobin concentration alone to inform RBC transfusion decisions. However, this is likely not the best way to decide when to transfuse RBCs to a patient with shock. Our preliminary data in septic children suggest that hemodynamic measures better identify children who might benefit from RBC transfusion and that children with severe immune suppression may be at greater risks of transfusion-related harm. Lastly, our data show that RBC transfusion effects likely differ based on RBC unit collection, storage, and processing methods, and resultant quantities of soluble mediators. Together, these data support our hypothesis that physiologic and blood product factors will predict when children with septic shock will benefit from, or be harmed by, RBC transfusion. The overall goal of our research program is to develop a personalized-medicine approach to RBC transfusion in children with septic shock. Our objective for this proposal is to build decision support tools that can be used in future clinical trials to identify when children with septic shock should or should not be transfused with RBCs. Our proposal uses robust machine learning techniques that are designed to use a very large number of dynamic variables to define personalized treatment decisions that maximize clinical outcomes. With these methods, and an agnostic, data-driven approach, the resultant decision rules will be free of clinician bias and can consider a much wider array of clinical parameters than have traditionally been used in transfusion trials. We will conduct a multicenter prospective observational study of 660 children with septic shock to accomplish the following specific aims: Aim 1: Determine which clinical, hemodynamic, and blood product-specific factors should drive RBC transfusion decision-making in children with septic shock. Using data from the electronic medical record, we will use outcome-weighted learning to build dynamic transfusion algorithms to minimize predicted daily organ dysfunction (PELOD2 scores). Aim 2: Identify immune phenotypes that predict differential response to RBC transfusion in children with septic shock. We will collect serial blood samples from subjects to measure a validated panel of inflammatory and immune function biomarkers and test the hypothesis that outcomes related to RBC transfusion will differ based on pre-transfusion levels of biomarkers of inflammation and/or immune suppression. We expect our data to transform the design of interventional trials of data-driven RBC transfusion algorithms to shift the transfusion paradigm away from hemoglobin-based strategies and improve outcomes for critically ill septic children.

抽象的 在全球范围内，每年将近300万儿童死于败血症。红细胞（RBC）以〜50％的身份输血 患有败血性休克的儿童，目的是增强氧气递送，有助于解决冲击并防止 器官功能障碍。但是，RBC输血与不良后果有关 重症疾病，暗示伤害。对于大多数患有败血性休克的孩子，我们缺乏数据来确定谁应该或 不应输了。介入的试验和RBC输血指南使用了血红蛋白 仅集中精力就可以告知RBC输血决策。但是，这可能不是决定的最佳方法 何时将RBC输送给有冲击的患者。我们在化粪池儿童中的初步数据表明 血流动力学措施更好地识别可能从加拿大皇家骑警输血中受益的儿童 严重的免疫抑制可能面临与输血相关的危害的更大风险。最后，我们的数据表明 RBC输血效应可能会根据RBC单元收集，存储和处理方法而有所不同，并且 最终数量的可溶性介体。这些数据共同支持我们的假设，即生理学和 血液产品因素将预测脓毒症儿童何时受益于RBC或受到损害 输血。我们的研究计划的总体目标是开发一种个性化的中等医学方法 败血性休克儿童的RBC输血。我们对该建议的目标是建立决策支持工具 可以在以后的临床试验中使用，以确定何时应有或不应 用RBCs输出。我们的建议使用强大的机器学习技术，这些技术旨在使用非常 大量的动态变量来定义最大化临床结果的个性化治疗决策。 通过这些方法以及不可知论，数据驱动的方法，由此产生的决策规则将不含临床医生 偏见，可以考虑比传统上使用的临床参数更广泛 输血试验。我们将对660名化粪池儿童进行多中心前瞻性观察研究 震惊完成以下特定目的：目标1：确定哪种临床，血液动力学和血液 特定于产品的因素应推动败血性休克儿童的RBC输血决策。 使用电子病历中的数据，我们将使用成果加权学习来构建动态 输血算法以最大程度地减少预测的每日器官功能障碍（PELOD2分数）。目标2：识别 免疫表型预测化粪池儿童对RBC输血的差异反应 震惊。我们将从受试者那里收集连续血样，以测量经过验证的炎症和 免疫功能生物标志物并检验以下假设：与RBC输血相关的结果将有所不同 关于炎症和/或免疫抑制的生物标志物的转移前灌注水平。我们希望我们的数据能够 转换数据驱动的RBC输血算法的介入的介入的设计，以转移输血 范式远离基于血红蛋白的策略，改善了重症化脓性儿童的结果。