Abstract
Background: Analysis of the respiratory pattern is currently reduced to simplified biomarkers, such as rate or phase timing. However, respiratory waveforms are complex and generally sampled with high fidelity. Our novel mathematical method, Symmetric Projection Attractor Reconstruction (SPAR) analyses waveforms without discarding any of this numerical data.
Aims and objectives: To identify new respiratory biomarkers by quantifying waveform morphology and variability using SPAR.
Methods: Retrospective respiratory flow data was analysed in 1-minute windows, from 8 volunteers exposed to normoxia and hypercapnia (5% Co2), while resting in a 50-degree head-up tilt position.
Results: As ventilation adapts from normoxia to steady-state hypercapnia (column 1 vs column 6), attractors become larger (reflecting amplitude changes of the signal, ROC AUC = 1.000), rounder (changes in the shape of inspiratory/expiratory phases, ROC AUC = 0.7969) and less diffuse (decreased wave-to-wave shape variability, ROC AUC = 0.7813) (Fig 1).
Conclusions: SPAR replots high fidelity waveform data generating corresponding “at-a-glance” quantifiable images. In this pilot, we identified new measures of morphology and variability following CO2 challenge. We predict that a combination of SPAR plus conventional measures may more sensitively discriminate changes in underlying respiratory physiology.
Aims and objectives: To identify new respiratory biomarkers by quantifying waveform morphology and variability using SPAR.
Methods: Retrospective respiratory flow data was analysed in 1-minute windows, from 8 volunteers exposed to normoxia and hypercapnia (5% Co2), while resting in a 50-degree head-up tilt position.
Results: As ventilation adapts from normoxia to steady-state hypercapnia (column 1 vs column 6), attractors become larger (reflecting amplitude changes of the signal, ROC AUC = 1.000), rounder (changes in the shape of inspiratory/expiratory phases, ROC AUC = 0.7969) and less diffuse (decreased wave-to-wave shape variability, ROC AUC = 0.7813) (Fig 1).
Conclusions: SPAR replots high fidelity waveform data generating corresponding “at-a-glance” quantifiable images. In this pilot, we identified new measures of morphology and variability following CO2 challenge. We predict that a combination of SPAR plus conventional measures may more sensitively discriminate changes in underlying respiratory physiology.
| Original language | English |
|---|---|
| Title of host publication | European Respiratory Journal |
| DOIs | |
| Publication status | Published - 2021 |