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Association between automatic AI-based quantification of airway-occlusive mucus plugs and all-cause mortality in patients with COPD

Tjeerd van der Veer, Eleni‐Rosalina Andrinopoulou, Gert‐Jan Braunstahl, Jean Paul Charbonnier, Victor Kim, Rudolfs Latisenko, David A. Lynch, Harm A.W.M. Tiddens

2024Thorax29 citationsDOIOpen Access PDF

Abstract

In this cohort study involving 9399 current and former smokers from the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease study, we assessed the relationship between artificial intelligence-quantified mucus plugs on chest CTs and all-cause mortality. Our results revealed a significant positive association, particularly for those with COPD GOLD stages 1-4, with HRs of 1.18 for 1-2 mucus-obstructed bronchial segments and 1.27 for ≥3 obstructed segments. This corroborates previous visual mucus plug counting research and demonstrates the relevance of mucus plugs in COPD pathology and as a marker for risk assessment. Automated mucus plug quantification methods may provide an efficient tool for both clinical evaluations and research.

Topics & Concepts

MedicineCOPDMucusPulmonary diseasePathologyAirwayCohortCohort studyInternal medicineSurgeryEcologyBiologyChronic Obstructive Pulmonary Disease (COPD) ResearchAsthma and respiratory diseasesLung Cancer Diagnosis and Treatment
Association between automatic AI-based quantification of airway-occlusive mucus plugs and all-cause mortality in patients with COPD | Litcius