# Optimizing the Diagnostic Strategy for Acute Musculoskeletal Infections in Children: Evaluating the Clinical Performance and Comparative Cost of a Noninvasive Diagnostic Technique > **NIH NIH K23** · UNIVERSITY OF COLORADO DENVER · 2024 · $186,210 ## Abstract PROJECT SUMMARY/ABSTRACT Pediatric musculoskeletal infections (MSKIs) are burdensome disorders that consume significant hospital re- sources and require prompt antimicrobial treatment to prevent systemic morbidity and life-altering disability. Identifying the causative bacterial culprit for MSKIs improves care by quickly targeting therapy. However, many children suffering from MSKIs never have their bacterial cause identified using existing microbiological tech- niques. Blood cultures are minimally invasive and inexpensive but only find the pathogen in 30-50% of MSKIs. Surgically-collected biopsies of infected musculoskeletal specimens (i.e., “source cultures”) increase diagnostic yield by 30% but require invasive and expensive diagnostic procedures with potential harm from sedation and surgery. Studies are needed to identify the optimal diagnostic strategy for MSKIs (i.e., routine use of invasive procedures versus blood culture alone). The Pediatric Health Information System (PHIS) database contains administrative data from millions of inpatient encounters and could be leveraged to efficiently study the diag- nostic variability for MSKIs at 52 pediatric hospitals in the United States. In addition, new diagnostic modalities have emerged that hold promise for pediatric MSKIs but need further study in these patients. Specifically, next- generation sequencing of microbial cell-free DNA (mcfDNA) from a peripheral blood specimen is a newly de- veloped non-invasive diagnostic test that uses a “liquid biopsy” to detect more than 1000 potential pathogens. Although mcfDNA testing is approved for clinical use, this test has not been validated in children with MSKIs specifically. The lack of evidence for how mcfDNA compares to invasive diagnostic procedures limits its clinical utility in this population. The Infectious Diseases Society of America (IDSA) recently called for new studies to determine whether mcfDNA testing could improve care for pediatric MSKIs. In addition, mcfDNA has an esti- mated cost of more than $2000, and cost analyses are needed to justify its use. This proposal aims to address the critical need for an optimized diagnostic strategy in pediatric MSKIs by (1) describing national variability in diagnostic testing and associated clinical outcomes for acute pediatric MSKIs; (2) determining the clinical performance of non-invasive mcfDNA testing for MSKIs compared to microbiological testing of surgically collected bone and joint specimens; (3) describe the cost of mcfDNA as compared to existing diagnostic options for pediatric MSKIs. This project is the culmination of this candidate’s dedication to improving clinical outcomes for children hospitalized with MSKIs. The objective of this award is for the candidate to develop the skills needed to meet his long-term goal of becoming an independent investigator studying diagnostic innovation for pediatric infections. The candidate will build on his research skillset through expert mentorship, dida... ## Key facts - **NIH application ID:** 10774323 - **Project number:** 5K23AI171084-02 - **Recipient organization:** UNIVERSITY OF COLORADO DENVER - **Principal Investigator:** Justin Benjamin Searns - **Activity code:** K23 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $186,210 - **Award type:** 5 - **Project period:** 2023-02-03 → 2027-01-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10774323 ## Citation > US National Institutes of Health, RePORTER application 10774323, Optimizing the Diagnostic Strategy for Acute Musculoskeletal Infections in Children: Evaluating the Clinical Performance and Comparative Cost of a Noninvasive Diagnostic Technique (5K23AI171084-02). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10774323. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*