A practical LRTI diagnostic-and-treatment algorithm for low-resource settings
Official title: A randomized controlled trial of a novel, evidence-based algorithm for managing lower respiratory tract infection in a resource-limited setting
Funded at Duke University · NIH-11590699 · Data updated 2026-11-12
Aims to improve how doctors diagnose and treat lower respiratory infections in settings with limited resources to reduce unnecessary antibiotic use.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Duke University NIH-funded |
| Lab location | 1 site (Durham, United States) |
| Project start | August 25, 2022 |
| Project end | July 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $54,648 |
| NIH project number | 3R01AI168420-05S1 |
| Project ID | NIH-11590699 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are individuals with suspected lower respiratory tract infection presenting in LMIC clinic settings, including both children and adults.
✕Less likely to help
Patients with complex, non-infectious respiratory conditions or those not meeting algorithm criteria may not benefit.
What this research studies
This project tests an easy-to-use, low-cost decision algorithm that combines simple diagnostic tools and real-time data to guide antibiotic decisions for people with lower respiratory infections in Sri Lanka. It focuses on both children and adults and seeks to tailor care to what is realistically available in LMICs. The study builds on existing patient samples and data from Sri Lankan clinics to refine the algorithm and then evaluate its impact on treatment choices and outcomes. If successful, the approach could be adapted to other low-resource settings to improve antimicrobial stewardship.
Why it matters
Potential benefit: If successful, patients could receive more accurate diagnoses and more appropriate antibiotic use, reducing unnecessary antibiotics and improving recovery.
How similar studies have gone: Related work in LMICs has shown that diagnostic algorithms can reduce unnecessary antibiotic use, but this study tests a refined, real-time version.
Where this research is happening
-
Duke University
Durham, United States Active
Researchers
- Principal investigator: Tillekeratne, Gayani — Duke University
- Study coordinator: Tillekeratne, Gayani
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.