Integrated Coagulation Sensing to Predict Hemorrhage and Guide Transfusions

集成凝血传感来预测出血并指导输血

基本信息

批准号：
9765379
负责人：
Seemantini K Nadkarni
金额：
$ 78.04万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-15 至 2022-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9765379
关键词：
Acute Lung Injury Address Algorithms Allogenic Award Blood Blood Coagulation Disorders Blood Coagulation Factor Blood Component Transfusion Blood Platelets Blood Transfusion Blood specimen Cardiac Cardiac Surgery procedures Clinical Coagulation Process Complex Complication Critical Illness Defect Development Devices Dose Drops Event Fibrin Fibrinolysis Generations Goals Hand Health Care Costs Healthcare Hematocrit procedure Hemoglobin Hemorrhage Hemostatic function Hospitals Hour Iatrogenesis Impairment Individual Intelligence Intensive Care Units Kidney Failure Laboratories Lasers Laser Speckle Imaging Lead Life Measures Microprocessor Modeling Modulus Monitor Motion Operative Surgical Procedures Optics Organ failure Outcome Pathway interactions Patient-Focused Outcomes Patients Pattern Phase Plasma Platelet Count measurement Procedures Property Prothrombin time assay Recommendation Repeat Surgery Reporting Resources Rheology Risk Sampling Savings Severities Societies Source System Techniques Testing Thoracic Surgeon Thrombin Time Tissues Touch sensation Transfusion Unit of Measure Vascular blood supply Whole Blood Work base blood product cardiac intensive care unit cohort cost crosslink improved indexing individual patient infection risk innovation instrument light scattering meter mortality novel novel strategies operation particle platelet function point of care polymerization predictive modeling tool validation studies viscoelasticity wasting

项目摘要

ABSTRACT The goal of this project is to develop an integrated coagulation instrument approach for use at the point-of-care to predict bleeding events and tailor blood component transfusion after cardiac surgery. Severe bleeding, frequently a result of impaired coagulation or coagulopathy, occurs in over 50% of patients after complex cardiac surgeries. Multiple factors including the depletion of clotting factors, impaired platelet function and the systemic activation of fibrinolytic pathways contribute to the development of coagulopathy. To manage defective coagulation, blood components are transfused to correct bleeding abnormalities. Inadequate or delayed transfusion can lead to life-threatening blood loss and organ failure, while overuse of allogenic blood may cause acute lung injury, renal failure and increased mortality after cardiac surgery. In order to achieve optimal outcome and save lives, clinical tools that can rapidly predict major bleeding following cardiac surgery are essential. Unfortunately, laboratory tests are ineffective in the context of rapidly changing coagulation conditions in critically-ill cardiac patients, resulting in transfusion triggers that are often imprecise, inadequate and in many cases, clinically unnecessary. Together, these factors pose detrimental complications for patients, and place a large burden on healthcare costs by wasting a scarce resource leading to blood product shortage for patients in need. This dire situation has prompted a Class I recommendation by the Society of Thoracic Surgeons for tailoring transfusion decisions via point-of-care coagulation tests that are supplemented with integrated transfusion algorithms. Our proposal directly addresses this recommendation. Here, we propose a novel approach termed iCoagLab that measures multiple coagulation parameters within less than 10 minutes at the bedside to identify patients at an elevated risk of bleeding after cardiac surgery, tailor transfusion requirements and monitor hemostasis during treatment. The technique involves placing a few drops of whole blood in a small cartridge. A laser source illuminates the blood sample and a camera images laser speckle patterns reflected from the sample over time. By analyzing laser speckle intensity fluctuations during coagulation, we can simultaneously quantify multiple coagulation metrics including prothrombin time, activated clotting time, thrombin generation rate, fibrin polymerization, fibrinolysis, and platelet function. The optical device will be supplemented by an algorithm that combines information from multiplexed coagulation parameters to predict bleeding severity and identify transfusion strategies tailored to the individual patient. In the final phase of our work, we will conduct studies to evaluate the accuracy and utility of the new iCoagLab approach to predict bleeding risk and transfusion requirements in patients admitted to the cardiac ICU following surgery.

抽象的该项目的目的是开发一种集成的凝结仪器方法，以便在心脏手术后预测出血事件和量身定制血液成分输血的临时点。严重的出血，经常是凝血或凝血病受损的结果，发生在超过50％的患者中经过复杂的心脏手术。多种因素，包括凝血因子的耗竭，血小板受损纤溶途径的功能和全身激活有助于凝血病的发展。到控制缺陷的凝血，血液成分被输血以纠正出血异常。不足或延迟输血会导致威胁生命的失血和器官衰竭，而过度使用血液可能导致急性肺损伤，肾衰竭和心脏手术后死亡率增加。为了获得最佳结果并挽救生命，临床工具可以快速预测心脏后重大出血手术至关重要。不幸的是，实验室测试在迅速变化的背景下无效批判性心脏患者的凝结条件，导致输血触发通常不精确，在许多情况下，在临床上不必要。这些因素在一起构成有害并发症对于患者，通过浪费稀缺资源导致血液来承担医疗保健费用的巨大负担有需要的患者的产品短缺。这种可怕的情况促使我建议胸外科医生协会通过护理点凝血测试来调整输血决策补充综合输血算法。我们的建议直接解决了这一建议。在这里，我们提出了一种称为Icoaglab的新方法，该方法测量了多个凝血参数在床边不到10分钟，可以识别患者心脏手术后出血风险较高的患者，量身定制输血需求并监测治疗过程中的止血。该技术涉及放置一些在一个小弹药筒中滴全血。激光源照亮了血液样本和相机图像随着时间的流逝，样品反射的激光斑点图案。通过分析激光斑点强度波动在凝血过程中，我们可以同时量化多个凝血指标，包括凝血酶原时间，激活的凝血时间，凝血酶生成率，纤维蛋白聚合，纤维蛋白溶解和血小板功能。这光学设备将通过一种算法补充，该算法结合了多重凝结的信息预测严重程度出血并确定针对单个患者量身定制的输血策略的参数。在我们工作的最后阶段，我们将进行研究以评估新Icoaglab的准确性和实用性预测进入心脏ICU的患者的出血风险和输血要求的方法外科手术。