CIRO+, center of expertise for chronic organ failure, Horn, The Netherlands.
Department of Respiratory Medicine, Maastricht University Medical Centre+ (MUMC+), Maastricht, the Netherlands.
PLoS One. 2018 Sep 12;13(9):e0201593. doi: 10.1371/journal.pone.0201593. eCollection 2018.
While spirometry and particularly airflow limitation is still considered as an important tool in therapeutic decision making, it poorly reflects the heterogeneity of respiratory impairment in chronic obstructive pulmonary disease (COPD). The aims of this study were to identify pathophysiological clusters in COPD based on an integrated set of standard lung function attributes and to investigate whether these clusters can predict patient-related outcomes and differ in clinical characteristics.
Clinically stable COPD patients referred for pulmonary rehabilitation underwent an integrated assessment including clinical characteristics, dyspnea score, exercise performance, mood and health status, and lung function measurements (post-bronchodilator spirometry, body plethysmography, diffusing capacity, mouth pressures and arterial blood gases). Self-organizing maps were used to generate lung function based clusters.
Clustering of lung function attributes of 518 patients with mild to very severe COPD identified seven different lung function clusters. Cluster 1 includes patients with better lung function attributes compared to the other clusters. Airflow limitation is attenuated in clusters 1 to 4 but more pronounced in clusters 5 to 7. Static hyperinflation is more dominant in clusters 5 to 7. A different pattern occurs for carbon monoxide diffusing capacity, mouth pressures and for arterial blood gases. Related to the different lung function profiles, clusters 1 and 4 demonstrate the best functional performance and health status while this is worst for clusters 6 and 7. All clusters show differences in dyspnea score, proportion of men/women, age, number of exacerbations and hospitalizations, proportion of patients using long-term oxygen and number of comorbidities.
Based on an integrated assessment of lung function variables, seven pathophysiological clusters can be identified in COPD patients. These clusters poorly predict functional performance and health status.
虽然肺量测定术，尤其是气流受限，仍被认为是治疗决策的重要工具，但它并不能很好地反映慢性阻塞性肺疾病（COPD）患者呼吸损害的异质性。本研究旨在根据一套综合的标准肺功能指标，确定 COPD 的病理生理簇，并探讨这些簇是否可以预测患者相关结局，以及在临床特征上是否存在差异。
临床稳定的 COPD 患者因接受肺康复而接受综合评估，包括临床特征、呼吸困难评分、运动表现、情绪和健康状况以及肺功能测量（支气管扩张剂后肺量测定术、体描法、弥散量、口腔压力和动脉血气）。使用自组织映射生成基于肺功能的簇。
对 518 例轻度至重度 COPD 患者的肺功能属性进行聚类，确定了七个不同的肺功能簇。簇 1 包括与其他簇相比肺功能属性更好的患者。在簇 1 到 4 中，气流受限减弱，但在簇 5 到 7 中更明显。在簇 5 到 7 中，静态过度充气更为明显。一氧化碳弥散量、口腔压力和动脉血气的情况则不同。与不同的肺功能特征相关，簇 1 和 4 表现出最佳的功能表现和健康状况，而簇 6 和 7 则最差。所有簇在呼吸困难评分、男女比例、年龄、加重和住院次数、长期吸氧比例和合并症数量方面均存在差异。
基于肺功能变量的综合评估，可以在 COPD 患者中确定七个病理生理簇。这些簇不能很好地预测功能表现和健康状况。
