Bordeaux University, INSERM, Bordeaux Population Health Research Center, team: EPICENE, UMR1219, Bordeaux, France.
Polyclinique Bordeaux Rive Droite, Lormont, France.
Respir Med. 2020 Aug;169:106018. doi: 10.1016/j.rmed.2020.106018. Epub 2020 May 11.
Exacerbations are key events in the natural history of COPD, but our understanding of their longitudinal determinants remains unclear. We used data from a large observational study to test the hypothesis that vaccination status and comorbidities could be associated with the occurrence of exacerbations profile.
Diagnosed COPD patients have been included by their pulmonologists, with up to 3 years of follow-up. Data were analyzed using the KmL method designed to cluster longitudinal data and receiver operating characteristic curve analysis to determine the best threshold to allocate patients to identified clusters.
932 COPD patients were included since January 2014, 446 patients (65.68% males, 35.59% current smokers) were followed over a period of 3 years with complete data. 239(28.15%) patients reported two or more exacerbations in the year before enrolment (frequent exacerbations). Among them 142(16.68%) also had frequent exacerbations in the first year of the study, and 69(8.10%) who remained frequent exacerbators in the second year. Based on our hypothesis, we were able to determine four phenotypes: A (infrequent), B (frequent in underweight patients), C (transient), and D (frequent in obese patients). Frequent exacerbators had more airflow limitation and symptoms. Irrespective of cut-offs set to define the optimal number of clusters, a history of exacerbations OR: 3.72[2.53-5.49], presence of anxiety OR: 2.03[1.24-3.31] and absence of the annual influenza vaccination OR: 1.97[1.20-3.24] remained associated with the frequent exacerbator phenotypes.
The most important determinants of frequent exacerbations are a history of exacerbations, anxiety and unvaccinated against influenza.
加重是 COPD 自然病程中的关键事件,但我们对其纵向决定因素的了解仍不清楚。我们使用来自一项大型观察性研究的数据来检验假设,即疫苗接种状况和合并症可能与加重发生情况相关。
通过其肺病专家,纳入确诊的 COPD 患者,进行了长达 3 年的随访。使用 KmL 方法分析数据,该方法旨在聚类纵向数据,以及接收者操作特征曲线分析,以确定最佳阈值将患者分配到确定的聚类中。
自 2014 年 1 月以来,共纳入 932 名 COPD 患者,446 名患者(65.68%为男性,35.59%为当前吸烟者)在 3 年内完成了完整的数据随访。239 名(28.15%)患者在入组前一年内报告了两次或两次以上加重(频繁加重)。其中 142 名(16.68%)在研究的第一年也有频繁加重,69 名(8.10%)在第二年仍为频繁加重患者。根据我们的假设,我们能够确定四个表型:A(不频繁)、B(体重不足患者的频繁)、C(短暂)和 D(肥胖患者的频繁)。频繁加重患者有更多的气流受限和症状。无论设置什么最佳聚类数的截止值,加重病史 OR:3.72[2.53-5.49]、焦虑症存在 OR:2.03[1.24-3.31]和未接种年度流感疫苗 OR:1.97[1.20-3.24]仍然与频繁加重表型相关。
频繁加重的最重要决定因素是加重病史、焦虑症和未接种流感疫苗。