The respiratory physiome: Clustering based on a comprehensive lung function assessment in patients with COPD

Area of Science:

• Pulmonary Medicine
• Respiratory Physiology
• Medical Data Analysis

Background:

• Spirometry and airflow limitation are key in chronic obstructive pulmonary disease (COPD) treatment decisions.
• However, these measures inadequately capture the diverse respiratory impairments seen in COPD patients.
• This study aimed to address this gap by identifying distinct pathophysiological groups within COPD.

Purpose of the Study:

• To identify pathophysiological clusters in COPD using integrated lung function data.
• To determine if these clusters correlate with clinical characteristics and patient-related outcomes.
• To improve understanding of COPD heterogeneity beyond standard airflow limitation metrics.

Main Methods:

• Integrated assessment of 518 clinically stable COPD patients undergoing pulmonary rehabilitation.
• Included clinical data, symptom scores, exercise capacity, mood, health status, and comprehensive lung function tests.
• Self-organizing maps were employed to create lung function-based clusters.

Main Results:

• Seven distinct lung function clusters were identified among COPD patients.
• Clusters varied in airflow limitation, static hyperinflation, diffusing capacity, and gas exchange.
• Clusters 1 and 4 showed better functional performance and health status, while clusters 6 and 7 had the worst outcomes.
• Significant differences were observed across clusters in dyspnea, demographics, exacerbation history, and comorbidities.

Conclusions:

• Seven pathophysiological clusters in COPD patients can be identified using an integrated lung function assessment.
• These clusters demonstrate heterogeneity in respiratory impairment.
• The identified clusters showed limited ability to predict functional performance and health status.