Tjeerd van der Veer, Eleni-Rosalina Andrinopoulou, Gert-Jan Braunstahl, Jean Paul Charbonnier, Victor Kim, Rudolfs Latisenko, David A Lynch, Harm Tiddens
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Association between automatic AI-based quantification of airway-occlusive mucus plugs and all-cause mortality in patients with COPD
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.
期刊介绍:
Thorax stands as one of the premier respiratory medicine journals globally, featuring clinical and experimental research articles spanning respiratory medicine, pediatrics, immunology, pharmacology, pathology, and surgery. The journal's mission is to publish noteworthy advancements in scientific understanding that are poised to influence clinical practice significantly. This encompasses articles delving into basic and translational mechanisms applicable to clinical material, covering areas such as cell and molecular biology, genetics, epidemiology, and immunology.