Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz

Logo MUG-Forschungsportal

Gewählte Publikation:

SHR Neuro Krebs Kardio Lipid Stoffw Microb

John, T; Kovacs, G; Douschan, P; Foris, V; Gumpoldsberger, M; John, N; Zeder, K; Zirlik, A; Olschewski, H; Pienn, M.
Detection of structural pulmonary changes with real-time high-fidelity analysis of expiratory CO2.
J Breath Res. 2025; Doi: 10.1088/1752-7163/adf253
PubMed FullText FullText_MUG

 

Führende Autor*innen der Med Uni Graz
John Teresa
Co-Autor*innen der Med Uni Graz
Douschan Philipp
Foris Vasile
John Nikolaus
Kovacs Gabor
Olschewski Horst
Pienn Michael
Zeder Katarina Eleonora
Zirlik Andreas
Altmetrics:

Dimensions Citations:

Plum Analytics:

Scite (citation analytics):

Abstract:
There is an unmet need for breath-based markers for pulmonary vascular disease (PVD). We developed a fully-automatic algorithm to analyse expiratory CO2 flow from resting ventilation and evaluated the clinical associations of our readouts. We enrolled patients with chronic obstructive pulmonary disease (COPD), interstitial lung disease (ILD), pulmonary arterial hypertension (PAH) and healthy controls and evaluated fractionated volumes for dead space, mixed space (MSV) and alveolar space, their respective CO2 volumes and ventilatory equivalents for CO2 (EqCO2) and the maximum slope of the first derivative of the cumulative expiratory CO2 volume over expired volume (MSV-slope) as primary readouts. Differences between groups were analysed using non-parametric tests. Associations were analysed by Spearman correlation. The discriminatory power was determined with receiver operating characteristic (ROC) analysis. Eleven COPD (median (IQR) age 64 (63-69) years), 10 ILD (61 (54-77) years), 10 PAH (64 (61-73) years) and 21 healthy controls (56 (52-61) years) were investigated. Patients vs. healthy controls showed increased MSV and mixed space CO2 (221 (164-270) mL vs. 144 (131-167) mL, and 3.9 (3.2-4.9) mL vs. 3.0 (2.7-3.4) mL, p<0.001 and p=0.002) and EqCO2 (38 (34-42) vs. 30 (29-35), p<0.001), and decreased MSV-slopes (0.16 (0.12-0.21) vs. 0.27 (0.23-0.32) L CO2/L2, p<0.001). Area under the curve (AUC) for MSV and MSV-slope for disease prediction was 0.81 (95% CI 0.69-0.93) and 0.84 (0.73-0.95), respectively. MSV and mixed space CO2 were only strongly increased in COPD and ILD but not PAH, resulting in a significant difference between PAH and COPD&ILD (AUC 0.74 (95% CI: 0.56-0.92). MSV and MSV-slope were significantly correlated with DLCO (ρ=-0.69 and ρ=0.72, respectively; both p<0.001). Fully-automatic high-fidelity expiratory CO2 flow analysis is technically feasible, easy and safe to perform, and may represent a novel approach to detect PVD with or without structural changes of the airways and lung parenchyma. Prospective studies with larger sample size are needed to validate these findings. .

© Med Uni Graz • Impressum