Sepsis Characterization in Kilimanjaro

乞力马扎罗山败血症特征

基本信息

批准号：
10687389
负责人：
Matthew P Rubach
金额：
$ 14.73万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-23 至 2025-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10687389
关键词：
Admission activity Adolescent Adoption Adult Africa South of the Sahara African American Automobile Driving Award Bayesian Analysis Bayesian Modeling Bioinformatics Biological Blood Circulation Blood specimen Caring Cessation of life Characteristics Classification Clinical Clinical Data Clinical Research Cluster Analysis Country Cryptococcosis Data Data Collection Derivation procedure Detection Disease District Hospitals Epidemiology Etiology Europe European Evaluation Fever Foundations Functional disorder Future Gene Expression Profile Genetic Genetic Transcription Goals HIV Infections Health Health system High Prevalence Hospital Mortality Hospitals Immune response Immunologics Income Infection Infectious Disease Epidemiology Infrastructure Institutes Intervention Investigation Knowledge Lead Mathematics Methods Mission Modeling Molecular Morbidity - disease rate North America Observational Study Outcome Pathway interactions Patients Population Positioning Attribute Process Protocols documentation RNA analysis Research Research Personnel Resource-limited setting Sampling Sepsis Sepsis Syndrome Septic Shock Severities Site Stratification Structure Syndrome Tanzania Triage Tuberculosis United States National Institutes of Health Universities Validation Virus Diseases Whole Blood Work base burden of illness classifier algorithm clinical investigation clinical phenotype clinical research site clinically relevant cohort disability improved low income country mortality mortality risk patient population point of care precision genomic medicine precision medicine prospective randomized trial risk stratification sample collection septic patients therapy design transcriptomics

Admission activity Adolescent Adoption Adult Africa South of the Sahara African American Automobile Driving Award Bayesian Analysis Bayesian Modeling Bioinformatics Biological Blood Circulation Blood specimen Caring Cessation of life Characteristics Classification Clinical Clinical Data Clinical Research Cluster Analysis Country Cryptococcosis Data Data Collection Derivation procedure Detection Disease District Hospitals Epidemiology Etiology Europe European Evaluation Fever Foundations Functional disorder Future Gene Expression Profile Genetic Genetic Transcription Goals HIV Infections Health Health system High Prevalence Hospital Mortality Hospitals Immune response Immunologics Income Infection Infectious Disease Epidemiology Infrastructure Institutes Intervention Investigation Knowledge Lead Mathematics Methods Mission Modeling Molecular Morbidity - disease rate North America Observational Study Outcome Pathway interactions Patients Population Positioning Attribute Process Protocols documentation RNA analysis Research Research Personnel Resource-limited setting Sampling Sepsis Sepsis Syndrome Septic Shock Severities Site Stratification Structure Syndrome Tanzania Triage Tuberculosis United States National Institutes of Health Universities Validation Virus Diseases Whole Blood Work base burden of illness classifier algorithm clinical investigation clinical phenotype clinical research site clinically relevant cohort disability improved low income country mortality mortality risk patient population point of care precision genomic medicine precision medicine prospective randomized trial risk stratification sample collection septic patients therapy design transcriptomics

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项目摘要

PROJECT SUMMARY Sepsis is a leading cause of in-hospital death in high-income countries, and it likewise causes a formidable burden of disease in low-income countries, where in-hospital mortality for severe sepsis can exceed 60%. Building upon Duke University’s strong collaborative clinical research platform in Kilimanjaro, Tanzania, these studies will use data-driven clustering methods and Bayesian latent class models to define clinically meaningful subtypes of sepsis that are specific to the infectious disease epidemiology and population sub-structures of sub- Saharan Africa (sSA). In doing so, we seek to advance the long-term goal of improving detection, risk stratification and, eventually, tailored interventions for sepsis among adults in resource-limited settings. The rationale driving this project is that sepsis subtype characterization holds great promise for improving the evaluation, management and clinical investigation of sepsis in sSA. To perform our characterizations of adult sepsis subtypes, we will leverage existing samples and data from our research platform’s 2016-2019 severe febrile illness cohort to inform a two-year prospective observational study of sepsis admissions at district hospitals in Kilimanjaro. By developing a precision medicine-based approach to classify the key pathophysiologic subtypes of sepsis in sSA, this project promotes the US National Institutes of Health’s mission to uncover new knowledge that will lead to better health for everyone—in this case, better health for the most severely ill in the region with the highest burden of sepsis in the world. To achieve this, the project has set out SPECIFIC AIMS that will develop clinical phenotype clusters of adult sepsis derived from clinical bioinformatics using Bayesian statistics (Aim 1) as well as immunologic sepsis clusters based upon the molecular characterization of the host immune response to infection (Aim 2). We will integrate the approaches in Aim 1 and Aim 2 in order to identify robust and clinically meaningful subtypes of sepsis in Kilimanjaro (Aim 3). In Year 1, we will use the existing samples and data collected 2016-2019 to develop and refine the statistical and analytical models for our Aims. This will inform the analytical framework for the prospective sepsis patient cohort in Years 2-3, which will be the basis for both derivation and validation of the clinical and molecular sepsis subtype classifications. The clinical clusters and molecular characterizations discovered in Aim 1 and Aim 2 will also be compared to findings from clinical bioinformatic and gene expression signature analyses that have described sepsis subtypes in Europe and North America. The disease epidemiology of sepsis in sSA—high prevalence of advanced HIV infection and more diverse sepsis etiologies—as well as potential host genetic differences compared to European and North American sepsis patients necessitate that subtype identification be specifically derived and validated for application in sSA. Not only will this project identify subtypes that improve triage and tailored intervention design for sepsis in sSA—it will also establish a framework for sepsis research in a setting where the greatest gains are needed and where the greatest improvements in sepsis outcomes can indeed be made.

项目摘要败血症是高收入国家院内死亡的主要原因，它同样会引起强大的低收入国家的疾病负担，严重败血症的住院死亡率可能超过60％。在杜克大学在坦桑尼亚乞力马扎罗的强大合作临床研究平台的基础上，这些研究将使用数据驱动的聚类方法和贝叶斯潜在类模型来定义临床上有意义的败血症的亚型，特有的，特定于传染病流行病学和亚属性子类型撒哈拉非洲（SSA）。为此，我们试图促进改善检测，风险的长期目标分层，并最终在资源有限的环境中针对成年人的败血症量身定制干预措施。这驱动该项目的理由是，败血症亚型的特征有很大的希望 SSA中败血症的评估，管理和临床研究。表演我们的成人角色败血症亚型，我们将利用我们研究平台2016 - 2019年严重的现有样本和数据发热的疾病队列，以告知两年的败血症入院的前瞻性观察性研究乞力马扎罗的医院。通过开发一种基于精确医学的方法来分类关键病理生理学 SSA败血症的亚型，该项目促进了美国国立卫生研究院的任务知识将为所有人带来更好的健康 - 在这种情况下，对最严重病人的健康状况更好世界上败血症燃烧最高的地区。为了实现这一目标，该项目已设定了特定的目标这将发展使用贝叶斯的临床生物信息学衍生的成年败血症的临床表型簇统计（目标1）以及基于宿主的分子表征的免疫败血症簇对感染的免疫反应（AIM 2）。我们将将方法整合到AIM 1和AIM 2中，以确定乞力马扎罗中败血症的强大和临床有意义的亚型（AIM 3）。在第一年，我们将使用现有的采集的样品和数据收集了2016 - 2019年，以开发和完善我们目标的统计和分析模型。这将为2 - 3年的前瞻性败血症患者队列的分析框架提供信息，这将是该临床是基于临床和分子败血症亚型分类的推导和验证。在AIM 1和AIM 2中发现的集群和分子字符也将与来自描述欧洲败血症亚型的临床生物信息学和基因表达签名分析和北美。 SSA中败血症的疾病流行病学 - 晚期HIV感染的高度患病率和与欧洲和北部相比美国败血症患者需要特异性地得出亚型识别和验证在SSA中的应用。这个项目不仅可以识别可改善分类和量身定制干预设计的亚型对于SSA的败血症，它还将在最大的环境中建立败血症研究的框架确实需要增益，以及确实可以取得最大的改善。