Leveraging Molecular Technologies to Improve Diagnosis and Management of Pediatric Acute Respiratory Illness in Resource-Constrained Settings

利用分子技术改善资源有限环境中儿科急性呼吸系统疾病的诊断和管理

• 批准号: 10739603
• 负责人: Emily Jane Ciccone
• 金额: $ 20.38万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-27 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10739603
• 关键词: Acceleration; Acute; Acute respiratory infection; Affect; Africa South of the Sahara; Age; Algorithms; Antibiotic Therapy; Antibiotics; Antimicrobial Resistance; Applications Grants; Bacterial Infections; Biological Markers; Biometry; Biostatistical Methods; Blood; Blood specimen; C-reactive protein; Categories; Child; Childhood; Clinical; Cohort Studies; Data; Derivation procedure; Detection; Development; Diagnosis; Diagnostic; Diagnostic tests; Enrollment; Etiology; Evaluation; Fever; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Goals; Growth; Hospitalization; Immune Response Genes; Immune response; Infection; Knowledge; Laboratories; Malaria; Malnutrition; Measurement; Measures; Mentored Patient-Oriented Research Career Development Award; Mentors; Mentorship; Metagenomics; Methodology; Modeling; Molecular; Molecular Profiling; Nasopharynx; Nature; North Carolina; Participant; Performance; Physicians; Polymerase Chain Reaction; Population; Positioning Attribute; Probability; Process; Quality of Care; Reference Standards; Research Personnel; Resource-limited setting; Respiratory Signs and Symptoms; Role; Sampling; Scientist; Seasons; Site; Streptococcus pneumoniae; Symptoms; Syndrome; Technology; Test Result; Testing; Time; Training; Transcript; Uganda; Uncertainty; Universities; Validation; Viral; Virus; Virus Diseases; Work; acceptability and feasibility; adjudication; antimicrobial; clinical biomarkers; clinical predictive model; co-infection; cohort; communicable disease diagnosis; comorbidity; design; diagnostic tool; differential expression; disease diagnostic; evaluation/testing; experience; global health; improved; influenza pneumonia; next generation sequencing; novel; novel diagnostics; pathogen; pediatrician; performance tests; point of care; predictive modeling; procalcitonin; prospective; respiratory; tool; training opportunity

PROJECT SUMMARY/ABSTRACT Antimicrobial resistance (AMR) is a rapidly growing threat to global health that is primarily driven by the overuse and misuse of antimicrobials. The applicant’s preliminary work in Uganda confirmed what has been noted in other resource-limited settings - children who present with febrile illnesses, particularly those with associated respiratory symptoms, are frequently treated with antibiotic therapy despite most of them likely having self-limited viral infections that do not require such treatment. This inappropriate dispensation of antibiotics is in part due to the diagnostic uncertainty inherent in the reliance on clinical symptoms for diagnosis and management of acute respiratory infections (ARI). Therefore, there is an urgent need for novel diagnostic tools that can distinguish children with bacterial ARI from those with non-bacterial infections, thus reducing antibiotic overuse for children presenting with this clinical syndrome. The objective of the scientific aims proposed in this K23 application is to develop a diagnostic model that accurately predicts bacterial infection in children with febrile ARI in Uganda. This work will facilitate the long-term goal of the applicant, which is to become an independent investigator with expertise in diagnostic evaluation and implementation working to improve quality of care and antimicrobial stewardship in both domestic and global contexts. Specifically, under the mentorship of experts in the fields of emerging molecular technologies, diagnostic evaluation, and prediction modeling at the University of North Carolina at Chapel Hill, she will (1) determine the etiology of febrile ARI in a cohort of previously and prospectively enrolled children, enhancing the diagnostic assessment with PCR-based and metagenomic next generation sequencing tools, (2) validate a host immune response gene expression assay, incorporating genes previously identified to be differentially expressed in viral and bacterial ARI, that minimizes the number of genes included to maximize feasibility in resource-constrained settings, and (3) develop novel clinical algorithms that combine host-based classifiers with other clinical and laboratory data to accurately predict bacterial ARI. Through pursuit of the scientific aims, the associated experiential and hands-on laboratory and biostatistical training, and focused didactic coursework, the applicant will address the following gaps in her knowledge: (1) molecular technologies and their role in infectious disease diagnosis and diagnostic development, (2) clinical prediction modeling, and (3) diagnostic tool evaluation and implementation. By the conclusion of the K23 award period, the applicant will have generated key results to inform a competitive R01 application. She will also be well-positioned to transition into an independent physician scientist and leading expert in diagnostic evaluation and antimicrobial stewardship in resource- constrained settings.

项目摘要/摘要 抗菌耐药性（AMR）是对全球健康的迅速增长的威胁，主要由 过度使用和错过了抗菌剂。申请人在乌干达的初步工作确认了 在其他资源有限的环境中指出 - 出现高热疾病的孩子，尤其是那些 相关的呼吸道症状经常接受抗生素治疗目的地治疗，其中大多数可能 具有不需要这种治疗的自限病毒感染。这种不适当的分配 抗生素部分是由于诊断临床症状固有的诊断不确定性 和急性呼吸道感染（ARI）的管理。因此，迫切需要新颖的诊断 可以将细菌ARI与非细菌感染的儿童区分开的工具，从而减少 抗生素过度使用该临床综合征的儿童。科学目的的目的 在此K23应用中提出的是开发一种准确预测细菌感染的诊断模型 乌干达有高温ARI的孩子。这项工作将促进申请人的长期目标，即 成为具有诊断评估和实施专业知识的独立研究者 提高在国内和全球环境中的护理质量和抗菌管理的质量。具体来说，下 专家在新兴分子技术，诊断评估和 她将在北卡罗来纳大学教堂山的大学进行预测，她将（1）确定 在以前和前瞻性儿童的队列中，发热的ARI，增强了诊断评估 使用基于PCR和元基因组的下一代测序工具，（2）验证宿主免疫反应 基因表达测定，结合先前鉴定为在病毒和 细菌ARI，可以最大程度地减少为最大化资源受限的可行性所包含的基因数量 设置以及（3）开发新型临床算法，这些临床算法将基于宿主的分类器与其他临床和 实验室数据准确预测细菌ARI。通过追求科学目标，相关的 体验和动手实验室和生物统计学培训，以及申请人的重点教学课程 将在她的知识中解决以下差距：（1）分子技术及其在传染病中的作用 诊断和诊断发展，（2）临床预测建模，以及（3）诊断工具评估和 执行。根据K23颁奖期结束，申请人将产生关键结果 通知有竞争力的R01申请。她还将有充分的位置过渡到独立的 医师科学家兼诊断评估和抗菌管理的主要专家 受限的设置。