Noninvasive Diagnostic Markers of Lower Respiratory Tract Infection in Mechanically Ventilated Patients

项目总结/文摘

Project Summary/Abstract Lower respiratory tract infection (LRTI) is the most common infectious cause of death. LRTI affects patients more often in ICUs, especially patients with mechanical ventilators. Early initiation of short-course antibiotic therapy is the cornerstone in managing mechanically ventilated patients with LRTI. However, using the current clinical criteria, a diagnosis of LRTI is typically not made until an infection in the lower respiratory tract is well established. To address the current limitations, molecular diagnostic technologies such as polymerase chain reaction (PCR)-based multiplex assays have been developed. However, they cannot distinguish between colonization and infection. Therefore, a more sophisticated diagnostic methodology is needed for LRTI diagnosis and management. Human exhaled air has great potential to address the current limitations in diagnosing LRTI. However, the lack of a suitable collection system for clinical use put a major barrier to exploring the medical potential of using human exhaled air. To address these limitations, Zeteo Tech renovated the capture mechanism and developed a novel collection system, BreathBiomicsTM, for biomolecules for human breath analysis. Specifically, we demonstrated that BreathBiomicsTM could be configured into mechanical ventilators for collecting biomolecules in the exhaled air from intubated patients in intensive care units. Most importantly, by characterizing these biomolecules using mass spectrometry, we identified truncated proteoforms, which are the products of activated proteases, and demonstrated that truncated proteoforms had the diagnostic potential for LRTI in a pilot study. Considering this evidence, we propose to determine whether truncated proteoforms in human exhaled air can be used as a noninvasive method for LRTI diagnosis and early prediction of LRTI in mechanically ventilated patients. Our work would largely assist decision-making for clinicians regarding antibiotic treatment and dramatically improve patients' clinical outcomes by limiting antibiotic requirements and minimizing harmful exposure to unnecessary antibiotic treatment.