Mentoring patient-oriented researchers in pediatric diarrhea

指导以患者为中心的小儿腹泻研究人员

• 批准号: 10591728
• 负责人: Daniel Ted Leung
• 金额: $ 17.19万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-11 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10591728
• 关键词: Address; Advanced Development; Antibiotics; Area; Award; Bangladesh; Big Data Methods; Bioinformatics; Biological Markers; Biometry; Cause of Death; Cessation of life; Child; Childhood; Cholera; Clinical; Clinical Management; Collaborations; Communicable Diseases; Complement; Country; Data; Data Science; Data Sources; Detection; Diagnosis; Diagnostic; Diagnostic tests; Diarrhea; Enrollment; Epidemiology; Etiology; Foundations; Frequencies; Funding; Future; Goals; Immunology; Income; Individual; Infection; Infrastructure; Knowledge; Mentors; Mentorship; Methods; Microbiology; Morbidity - disease rate; Pathogen detection; Physicians; Planet Earth; Population; Probability; Prognosis; Public Health; Qualitative Methods; Research; Research Design; Research Personnel; Resource-limited setting; Role; Scientist; Serology; Statistical Methods; Testing; Time; Training; Triage; United States National Institutes of Health; Universities; Utah; Viral; Work; antimicrobial; biomarker discovery; biomarker identification; candidate identification; candidate marker; care seeking; clinical care; clinical decision support; clinical decision-making; clinical predictive model; clinical predictors; cohort; cost; diagnostic panel; diarrheal disease; enteric infection; epidemiologic data; experience; improved; low and middle-income countries; metabolomics; microbial; molecular diagnostics; pathogen; patient oriented; patient oriented research; point of care; predictive tools; programs; remote sensing; serosurveillance; spatial integration; statistics; support tools; tool; transcriptomics

Project Summary Diarrheal illness is the second most common cause of non-neonatal death among young children worldwide, and is a major cause of morbidity. Current etiologic diagnosis of diarrhea relies on microbial detection, and decisions for antibiotics commonly empiric. However, the majority of cases of diarrhea do not benefit from antibiotic use, and testing for all potential pathogens is neither financially nor logistically feasible. Thus, methods to improve the clinical management of pediatric diarrheal illness, including strategies for antimicrobial and diagnostic stewardship, are needed. Clinical prediction rules are potential tools to address this need, and in this K24 application, our overall goal is to explore strategies to improve clinical decision-making for diarrhea management, through use of spatial-temporal data and biomarkers. Dr. Leung, the PI, is a physician-scientist with training in clinical infectious diseases, immunology, microbiology, and epidemiology, with a focus on enteric infections, especially those that cause diarrheal illness in children in limited-resource settings. He has mentored over 40 patient-oriented researchers (PORs) since the start of his independent research program in 2014; additionally, he has co-mentored numerous PORs in collaboration with scientists and clinicians working in low- and middle-income countries. Leveraging infrastructure already in place from three ongoing NIH-funded awards (R01AI130378, R01AI135114, R01AI135115), as well as Gates Foundation-funded studies, he proposes to augment his current POR by addressing the following aims: 1) To examine the use of spatial- temporal data for individual-level clinical prediction of pediatric diarrhea, where the use of A) serosurveillance, B) molecular diagnostic, and C) earth observation-derived data will be explored, and 2) To identify clinical use- cases, and potential candidates, of fecal biomarkers that complement clinical decision support tools for management of pediatric diarrhea, using both qualitative methods to examine end-user perspectives and identify use-cases, and metabolomics and transcriptomics methods to identify candidate biomarkers. To accomplish these aims, he has established a co-mentoring team of experienced investigators with diverse expertise in statistical methods, biomarker discovery, and mentoring of POR investigators. This award will provide protected time for Dr. Leung to improve and increase his mentoring capacity of POR trainees, expand his expertise and experience in bioinformatics, and generate data for future projects to improve the management and knowledge of pediatric diarrheal infections.

项目摘要 腹泻病是全球幼儿中非肿瘤死亡的第二大最常见原因， 是发病率的主要原因。腹泻的当前病因学诊断依赖于微生物检测，并且 抗生素的决定通常是经验性的。但是，大多数腹泻病例并不能从中受益 抗生素的使用以及对所有潜在病原体的测试在财务上也不是可行的。因此， 改善小儿腹泻病的临床管理的方法，包括抗菌策略 需要诊断管理。临床预测规则是解决这一需求的潜在工具，并且 在此K24应用程序中，我们的总体目标是探索策略以改善腹泻的临床决策 通过使用时空数据和生物标志物，管理。 PI Leung博士是医师科学家 通过临床传染病，免疫学，微生物学和流行病学的培训，重点是 肠道感染，尤其是那些在限量资源环境中儿童引起腹泻病的感染。他有 自从他的独立研究计划开始以来，指导了40多名以患者为导向的研究人员 2014;此外，他还与科学家和临床医生合作，共同掌握了许多鲍尔 在低收入和中等收入国家。利用基础设施已经从三个正在进行的NIH资助的 奖项（R01AI130378，R01AI135114，R01AI135115），以及盖茨基金会资助的研究 提议通过解决以下目的来增加他当前的POR：1）检查空间的使用 小儿腹泻的个体临床预测的时间数据，其中使用a）血清监视， b）分子诊断，c）将探索地球观测衍生的数据，以及2）确定临床使用 - 粪便生物标志物的病例和潜在候选者，这些疾病补充了临床决策支持工具 小儿腹泻的管理，使用两种定性方法来检查最终用户的观点和 识别用例，代谢组学和转录组学方法来识别候选生物标志物。到 完成这些目标，他建立了一个由经验丰富的调查员组成的团队 POR研究人员的统计方法，生物标志物发现和指导方面的专业知识。这个奖项将 为Leung博士提供受保护的时间，以提高和提高其POR学员的指导能力，扩大 他在生物信息学方面的专业知识和经验，并为未来项目生成数据以改善 小儿腹泻感染的管理和知识。