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New time-saving predictor algorithm for multiple breath washout in adolescents.

Jonathan Grønbæk1, Henrik Wegener Hallas1, Lambang Arianto1

  • 1COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark.

Pediatric Research
|March 23, 2016
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Summary

A new algorithm can shorten the multiple breath washout (MBW) test time in adolescents. However, using earlier prediction points increases test uncertainty, requiring cautious application, especially in individuals with normal lung clearance index (LCI) values.

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Area of Science:

  • Pediatric Pulmonology
  • Respiratory Physiology
  • Clinical Diagnostics

Background:

  • Multiple breath washout (MBW) is a valuable diagnostic tool for assessing lung function.
  • The standard MBW test is often lengthy, posing challenges for pediatric populations.
  • Developing time-efficient methods for MBW is crucial for clinical applicability.

Purpose of the Study:

  • To evaluate the accuracy and uncertainty of a novel, time-saving predictor algorithm for MBW in adolescents.
  • To determine optimal prediction points for reducing test duration while minimizing introduced variability.

Main Methods:

  • Adolescents from the COPSAC2000 birth cohort underwent MBW testing at age 13 using sulfur hexafluoride (SF6).
  • Measurements were analyzed using a mixed model, focusing on prediction points at 5% (t5%) and 10% (t10%) of the standard endpoint (t2.5%).
  • Washout time (WoT) and lung clearance index (LCI) uncertainty were calculated for each prediction point.

Main Results:

  • Analysis included 172 MBW trials from 78 adolescents.
  • At t10%, WoT was reduced by 41% with an LCI uncertainty of ±0.159 units.
  • At t5%, WoT was reduced by 25% with an LCI uncertainty of ±0.083 units, identified as the optimal point.

Conclusions:

  • The predictor algorithm effectively shortens MBW test duration in adolescents.
  • Earlier prediction points result in greater uncertainty in LCI measurements.
  • This algorithm shows promise for pediatric MBW but requires careful use in subjects with normal LCI values.