医学
慢性阻塞性肺病
共病
危险系数
内科学
肺病
比例危险模型
星团(航天器)
队列
体质指数
死亡率
糖尿病
队列研究
人口学
置信区间
计算机科学
程序设计语言
社会学
内分泌学
作者
Sebastián Gagatek,Sara Wijnant,Björn Ställberg,Karin Lisspers,Guy Brusselle,Xing Zhou,Mikael Hasselgren,Scott Montgomery,Josefin Sundh,Christer Janson,Össur Ingi Emilsson,Lies Lahousse,Andreï Malinovschi
标识
DOI:10.1183/13993003.congress-2020.4914
摘要
Introduction: Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous disease with a variable mortality risk. A simple clinical algorithm has been validated for short-term mortality by Burgel et al. (ERJ 2017). Aim: To study if Burgel’s clinical algorithm is valid to predict long-term mortality. Methods: Data from two COPD cohorts, the Swedish PRAXIS Study (PS) (n=784, mean age (SD) 64.0 years (7.5), 42% males) and the Rotterdam Study (RS) (n=735, mean age (SD) 72 years (9.2), 57% males), with 9-years of follow-up data including mortality was used. The five clinical clusters were derived from baseline data on age, body mass index, dyspnea grade (mMRC), FEV 1 (%pred) and comorbidity (cardiovascular disease or diabetes). Mortality risk was estimated by unadjusted Cox models. Results: The distribution of clinical clusters (1-5) was: 29%/45%/8%/6%/12% in PS and 23%/26%/36%/0/15% in RS. The cumulative proportion of deaths after 9-years of follow-up was highest among COPD clusters 1 (65%) and 4 (72%), and lowest among cluster 5 (10%) in the PS cohort. In RS, Cluster 1 (44%) had the highest cumulative mortality and cluster 5 (5%) the lowest. Compared to cluster 5, the meta-analysed hazard ratio (HR) (95%CI) for cluster 1 was 9.95 (6.52–15.19) and for cluster 4, 13.49 (6.41–28.38). The meta-analysed HR for clusters 2 and 3, compared with cluster 5, were: 2.80 (1.77 – 4.36) and 4.73 (3.02 – 7.42), respectively. Conclusions: Burgel’s clinical clusters can be used to predict long-term mortality risk. Clusters 1 and 4 are associated with the poorest prognosis, cluster 5 with best prognosis and clusters 2 and 3 with intermediate prognosis in two independent COPD cohorts from Sweden and Netherlands.
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