Informing the Emergency Care of Septic Shock Patients: A Novel Application of Data-Driven Analytics

通知感染性休克患者的紧急护理：数据驱动分析的新应用

• 批准号: 10491283
• 负责人: Lauren Page Black
• 金额: $ 18.01万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-20 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10491283
• 关键词: ADRB2 gene; Accident and Emergency department; Address; Area; Black race; Blood Pressure; Blood specimen; Characteristics; Classification; Clinical; Clinical Data; Clinical Research; Conflict (Psychology); Critical Care; Critical Illness; Data; Data Science; Data Set; Electronic Health Record; Emergency Care; Emergency Department patient; Emergency Medicine; Emergency Situation; Enrollment; Funding; Genes; Genetic; Genetic Polymorphism; Genetic Variation; Genotype; Goals; Heritability; Heterogeneity; Hospitals; Hour; Human; Hypotension; IV Fluid; Intervention; K-Series Research Career Programs; Knowledge; Lead; Liquid substance; Medical Genetics; Mentored Patient-Oriented Research Career Development Award; Mentors; Mentorship; Methods; Modeling; National Institute of General Medical Sciences; Outcome; Patients; Performance; Persons; Pharmaceutical Preparations; Pharmacogenetics; Pharmacogenomics; Phenotype; Population; Public Health; Race; Refractory; Research; Research Personnel; Resuscitation; Sampling; Scientist; Sepsis; Septic Shock; Shock; Single Nucleotide Polymorphism; Socioeconomic Status; Subgroup; Supervision; Systemic infection; Time; Training; Training and Education; Underrepresented Populations; Undifferentiated; Variant; Vasoconstrictor Agents; Work; advanced analytics; analytical method; base; beta-adrenergic receptor; biobank; biomedical informatics; black patient; blood pressure elevation; career; career development; clinical decision support; clinically relevant; cohort; cost; deep learning model; design; experience; implementation science; improved; innovation; insight; mortality; multidisciplinary; novel; patient population; patient response; premature; prospective; racial disparity; research study; response; risk variant; safety net; septic patients; skills; social factors; social health determinants; supervised learning; translational physician; treatment response; unsupervised learning

PROJECT SUMMARY Background: Septic shock is a commonly, costly, and deadly condition. There is increasing recognition that septic shock patients vary significantly in terms of (1) clinical presentation, (2) response to treatments, and (3) clinical outcomes. This patient-level heterogeneity may explain why optimal early septic shock management remains poorly understood. Patients with septic shock are four times more likely to die than septic patients without shock. Our preliminary data shows that Black patients have higher odds of mortality from septic shock compared to White patients. Current studies do not characterize patient heterogeneity among septic shock patients and do not explicate pharmacogenetic factors that may influence disparities in outcomes. Objective: Insights from synergistic data types are necessary to provide a more complete understanding of septic shock heterogeneity and hereditable factors that may influence vasopressor response and disparities in outcomes. The overall objective of the proposed research is to characterize both phenotypic and genetic aspects of heterogeneity in septic shock. This work is organized into two aims: (1) Identify Septic Shock Phenotypes Using Advanced Analytic Methods and (2) Quantify Vasopressor Pharmacogenetic Polymorphisms by Race and Vasopressor Response. Our overall hypothesis is that advanced analytic methods applied to clinical and genetic data can identify defining features of septic shock heterogeneity that are relevant to early septic shock management in the Emergency Department and disparities in outcomes. Methods: (Aim 1) We will use a national dataset of septic patients with hypotension refractory to initial Emergency Department fluid resuscitation and apply unsupervised machine learning clustering methods to define clinically relevant phenotypes of early septic shock patients. We will analyze phenotypic variation in clinical characteristics and outcomes. Then, we will develop a supervised model for phenotype classification. (Aim 2) We will perform targeted pharmacogenomics of 100 samples balanced for race, 73 of which are part of an existing research biobank of septic shock patients from our urban, safety-net hospital. We will enroll an additional 27 patients to complete the sample. We will examine the presence of risk alleles of single nucleotide polymorphisms for vasopressor-relevant genes by race. We will also examine the association between the targeted genetic polymorphisms and shock reversal. Career Development: During the proposed Career Development Award, I will work with my mentorship team to build the skills necessary to achieve independence as a clinical researcher. Specifically, I will 1) receive hands-on experience in the design and conduct of translational clinical research studies, 2) take didactic coursework in data science, biomedical informatics, and implementation science, 3) receive training and education in translational data science, clinical decision support, pharmacogenomics, and precision public health, and 4) become a leader and an effective mentor in academic emergency medicine.

项目概要 背景：感染性休克是一种常见、昂贵且致命的疾病。人们越来越认识到 感染性休克患者在以下方面存在显着差异：(1) 临床表现、(2) 对治疗的反应，以及 (3) 临床结果。这种患者水平的异质性可以解释为什么最佳的早期感染性休克管理 仍然知之甚少。脓毒性休克患者的死亡可能性是脓毒性患者的四倍 没有震惊。我们的初步数据显示，黑人患者死于感染性休克的几率更高 与白人患者相比。目前的研究并未描述感染性休克患者的异质性 患者，并且没有解释可能影响结果差异的药物遗传学因素。 目标：从协同数据类型中获得的见解对于提供更全面的理解是必要的 感染性休克的异质性和可能影响升压药反应的遗传因素和差异 结果。拟议研究的总体目标是表征表型和遗传 感染性休克的异质性方面。这项工作有两个目标：(1) 识别感染性休克 使用先进分析方法的表型和 (2) 量化血管升压药物遗传学 种族多态性和血管加压反应。我们的总体假设是高级分析 应用于临床和遗传数据的方法可以识别感染性休克异质性的定义特征 与急诊科的早期感染性休克管理和结果差异有关。 方法：（目标 1）我们将使用初始难治性低血压脓毒症患者的国家数据集 急诊科液体复苏并应用无监督机器学习聚类方法 定义早期感染性休克患者的临床相关表型。我们将分析表型变异 临床特征和结果。然后，我们将开发一个用于表型分类的监督模型。 （目标 2）我们将对 100 个种族平衡样本进行有针对性的药物基因组学研究，其中 73 个属于 来自我们城市安全网医院的败血性休克患者的现有研究生物库。我们将报名一个 另外 27 名患者完成了样本。我们将检查单核苷酸风险等位基因的存在 不同种族的血管加压药相关基因的多态性。我们还将检查之间的关联 有针对性的基因多态性和休克逆转。 职业发展：在拟议的职业发展奖期间，我将与我的导师团队合作 培养作为临床研究人员实现独立所需的技能。具体来说，我将1）收到 设计和进行转化临床研究的实践经验，2）接受教学 数据科学、生物医学信息学和实施科学方面的课程，3) 接受培训并 转化数据科学、临床决策支持、药物基因组学和精准公众教育 健康，4) 成为学术急诊医学领域的领导者和有效导师。