Saturday, May 18, 2024
5/18/2024
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.
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