The utility of a standardised breath sampler in school age children within a real-world prospective study

K K Bhavra1, M Wilde2,3, M Richardson4

  • 1Department of Respiratory Sciences, Leicester NIHR Biomedical Research Centre (Respiratory Theme), University of Leicester, Leicester, LE1 7RH, United Kingdom.

Journal of Breath Research
|February 15, 2022
PubMed

Insights

The ReCIVA breath sampler shows promise for collecting exhaled volatile organic compounds (VOCs) in children with asthma. While some technical issues like mask leaks and sampling synchronization occurred, the device reliably monitored pediatric breath profiles.

Area of Science:

  • Biomarkers and diagnostics
  • Respiratory medicine
  • Analytical chemistry

Background:

  • Clinical assessment of pediatric asthma requires non-invasive biomarkers.
  • Monitoring exhaled volatile organic compounds (VOCs) offers a promising alternative to invasive methods.
  • Standardized breath sampling is crucial for reliable VOC analysis.

Purpose of the Study:

  • To evaluate the efficacy of the ReCIVA breath sampler for collecting breath samples from children (5-15 years).
  • To assess the suitability of the ReCIVA for pediatric use in asthma research.

Main Methods:

  • Collected 90 breath samples from 64 children (with and without asthma) using two ReCIVA units.
  • Analyzed sample volume, sampling time, and operational faults (mask seal, communication errors).
  • Investigated the impact of sampling variability on VOC profiles using multivariate modeling.

Main Results:

  • 77.8% of samples met the target volume; sampling times differed between acute and stable asthma.
  • Operational faults, primarily mask leaks (15/21), were identified.
  • Synchronization issues affected 66.7% of samples, impacting breath phase accuracy.
  • Multivariate modeling confirmed no significant batch effects for eight operational variables.

Conclusions:

  • The ReCIVA device is suitable for pediatric breath sampling in asthma research.
  • Post-processing of sample metadata is recommended for quality assessment.
  • Future work should address synchronization faults and optimize mask fit for comfort and data quality.