Completed Lungs & Breathing NIHR-supported project Digestion, Kidneys & Other Organs

A pilot study to assess the feasibility of analysing expired breath in ventilated paediatric patients to diagnose infection

In plain English

AI plain-English summary

Every year, around 6,000 to 7,000 children in UK paediatric intensive care units are put on ventilators for lower respiratory tract infections (LRTI). The BRANCH study is testing whether the chemicals in a child’s breath can reveal not only the presence of an infection but also the specific microbe causing it. Currently, diagnosing LRTI in ventilated children often requires invasive procedures or broad-spectrum antibiotics while waiting for lab results. This pilot study aims to recruit 25 ventilated children with LRTI and 10 ventilated for other reasons, collecting breath samples from the ventilator’s expiratory circuit for about 30 minutes. The samples are sent for molecular analysis to detect volatile organic compounds (VOCs)—chemical by-products of normal lung metabolism that change when infection is present. Previous work has shown unique breath chemical profiles in adults and children with tuberculosis. If the approach proves feasible, it could lead to a rapid, non-invasive diagnostic tool that identifies infections and their causes from breath alone. This would reduce unnecessary antibiotic use, speed up targeted treatment, and avoid invasive sampling in critically ill children. The team at Imperial College, with world-leading expertise in these techniques, plans to follow this pilot with a larger multi-centre study in West London.

View original technical description
Each year, nearly 6000-7000 children are ventilated in UK paediatric intensive care units (PICU) for lower respiratory tract infections (LRTI). In the BRANCH study, we want to test whether the breath from children with LRTI contains a different profile of chemicals compared to children without LRTI and whether the profile can be used to identify the bug causing the LRTI. In adults and children with tuberculosis unique breath chemical profiles have been identified previously.As part of the study, we aim to recruit 25 ventilated children with a LRTI to serve as cases and 10 children ventilated for reasons other than LRTI (post-operative cases, for example) to serve as controls in a pilot study to check the feasibility of collecting and performing molecular analysis on expired ventilated air. The study would involve collecting breath samples from the expiratory (breathing out) part of the ventilator circuit for a short period of time (approximately 30 mins). This expired air would otherwise be wasted. The sample collected would be dispatched to a special laboratory for molecular analysis to look for volatile organic compounds (VOC). VOCs are a range of compounds produced by the lungs during normal metabolism as by-products which are breathed out. In the presence of a LRTI, the microorganisms in the lungs add to or change the composition and proportion of the VOCs exhaled out. This change in the VOC profile can be identified by molecular analysis.Imperial College have world-leading expertise in the techniques we are piloting in this vulnerable population, and once this project has gathered important preliminary data, we have the unique capability of advancing this research forward in a multi-centre prospective study in West London.

Researchers

Toranj Wadia (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

Breath Analysis in Intensive Care: Proof of Concept for Non-Invasive Diagnosis of Ventilator Associated Pneumonia
Host immune response point-of-care testing for children and adults presenting to primary care with acute upper respiratory tract infection: a mixed-methods feasibility study
A miniaturised laser isotope ratiometer for early diagnosis of sepsis by exhaled breath analysis
Comparison of Lower Airway Sampling Strategies In Children with PBB (CLASSIC PBB)
Measurement of novel indices of lung function in respiratory disease

Original classification

Infection & AMR

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.