Fever Etiology and Prognostic Point-of-Care Biomarkers in African Children with Severe Febrile Illness

摘要 严重的小儿发热性疾病具有很高的全球死亡率，并不成比例地影响儿童的资源， 撒哈拉以南非洲（SSA）的有限环境。虽然快速，适当的治疗可以改善结果， 严重的发热性疾病，我们缺乏对如何快速识别需要紧急和 具体管理。我的主要假设是，下一代测序可以提高对一种病毒的检测。 与培养相比，生物标志物即时检测可以预测严重的细菌感染， 细菌感染和临床恶化的儿童表现为严重发热性疾病。与儿科 严重感染合作（UCSF，坦桑尼亚的Muhimbili医院和Chan Zuckerberg Biohub） 旧金山弗朗西斯科），该提案利用专业知识，使用临床数据，尖端病原体检测 方法，创新的生物信息学平台（Global IDSeq）和生物标志物来开发治疗方法 非洲严重发热性疾病的算法。在这项对坦桑尼亚儿童进行的前瞻性队列研究中， 发热性疾病，我们将确定与不良临床结局相关的风险因素（目标1）， 本地可用的诊断技术（目标1）和最先进的下一代测序，以确定 严重发热性疾病的病因学（目的2）。使用目标1和2的数据，我们将确定哪些POCT用于 宿主血清生物标志物（降钙素原、C反应蛋白、铁蛋白、乳酸盐、血糖和血红蛋白）最好 预测严重细菌感染和临床恶化（目标3），并制定治疗方案 纳入临床体征和生物标志物，指导管理和资源分配。 我的长期职业目标是通过以下方式改善患有严重发热疾病的儿童的临床结果 制定和实施适当的、与具体情况相关的循证干预措施， 资源有限的环境。这个指导以患者为导向的研究职业发展奖为我提供了 机会：（1）发展成为独立的物理学家，科学家所需的技能和专业知识， 儿科严重发热性疾病领域;（2）整合人群特异性临床数据，当地可用的诊断 数据，尖端的下一代测序科学和宿主生物标志物，以更好地识别严重的细菌 感染和高危儿童;（3）在坦桑尼亚建立进一步的临床研究基础设施和程序， 未来的临床研究;和（4）学习和应用下一代测序数据分析使用生物信息学 方法和先进的生物统计分析复杂的观测数据。我召集了一个导师， 我们的团队拥有不同的专业知识，致力于帮助我实现这些目标。后 完成这项建议，采用当地的临床数据，一种高度敏感的病原体检测方法， 创新的生物信息学平台，以及使用即时生物标志物进行风险分层的独特方法， 我们将处于独特的地位，创造一个以证据为基础的，具体的治疗算法，以改善 SSA中严重发热性疾病儿童的预后，这将在R 01资助的研究中进行测试。

ABSTRACT Severe pediatric febrile illness has high global mortality and disproportionately affects children in resource- limited settings in sub-Saharan Africa (SSA). Though rapid, appropriate treatment can improve outcomes in severe febrile illness, we lack a robust understanding of how to rapidly identify children in need of urgent and specific management. My central hypotheses are that next generation sequencing can improve detection of a serious bacterial infection compared to culture and that biomarker point-of-care tests can predict a serious bacterial infection and clinical deterioration in children presenting with severe febrile illness. With the Pediatric Severe Infection Collaboration (UCSF, Muhimbili Hospital in Tanzania, and the Chan Zuckerberg Biohub in San Francisco), this proposal leverages expertise that uses clinical data, cutting-edge pathogen detection methods, an innovative bioinformatics platform (Global IDSeq), and biomarkers to develop a treatment algorithm for severe febrile illness in Africa. In this prospective cohort study of Tanzanian children with severe febrile illness, we will determine risk factors associated with poor clinical outcomes (Aim 1) and employ both locally available diagnostic techniques (Aim 1) and state-of-the-art next generation sequencing to determine the etiology of severe febrile illness (Aim 2). Using data from Aims 1 & 2, we will determine which POCTs for host serum biomarkers (procalcitonin, C-reactive protein, ferritin, lactate, blood sugar, and hemoglobin) best predict serious bacterial infection and clinical deterioration (Aim 3) and develop a treatment algorithm incorporating clinical signs and biomarkers that will guide management and resource allocation. My long-term career objective is to improve clinical outcomes for children with severe febrile illness through the development and implementation of evidence-based interventions that are appropriate and context-relevant for resource-limited settings. This Mentored Patient-Oriented Research Career Development Award offers me the opportunity to: (1) develop skills and expertise necessary to become an independent physician-scientist in the field of pediatric severe febrile illness; (2) integrate population-specific clinical data, locally available diagnostic data, cutting-edge next generation sequencing science, and host biomarkers to better identify serious bacterial infections and high-risk children; (3) build further clinical research infrastructure and processes in Tanzania for future clinical studies; and (4) learn and apply next-generation sequencing data analysis using a bioinformatics approach and advanced biostatistical analyses of complex observational data. I have assembled a mentoring, collaborative team with diverse expertise who are committed to helping me achieve these goals. After completion of this proposal that employs local clinical data, a highly sensitive method of pathogen detection, an innovative bioinformatics platform, and a unique approach to risk stratification with point-of-care biomarkers, we will be uniquely positioned to create an evidence-based, context–specific treatment algorithm to improve outcomes in children with severe febrile illness in SSA, which will be tested in an R01-funded study.