van der Veer Tjeerd, Andrinopoulou Eleni-Rosalina, Braunstahl Gert-Jan, Charbonnier Jean Paul, Kim Victor, Latisenko Rudolfs, Lynch David A, Tiddens Harm
Respiratory Medicine, Erasmus MC, Rotterdam, Netherlands
Respiratory Medicine, Leiden University Medical Center, Leiden, Netherlands.
Thorax. 2025 Jan 17;80(2):105-108. doi: 10.1136/thorax-2024-221928.
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.
在这项队列研究中,我们纳入了来自慢性阻塞性肺疾病遗传流行病学研究的9399名当前和既往吸烟者,评估了胸部CT上人工智能量化的黏液栓与全因死亡率之间的关系。我们的结果显示存在显著的正相关,特别是对于慢性阻塞性肺疾病全球倡议(GOLD)1-4级的患者,1-2个黏液阻塞支气管节段的风险比(HR)为1.18,≥3个阻塞节段的HR为1.27。这证实了先前关于黏液栓视觉计数的研究,并证明了黏液栓在慢性阻塞性肺疾病病理学中的相关性以及作为风险评估标志物的作用。自动黏液栓量化方法可能为临床评估和研究提供一种有效的工具。