Search

Background: The use of maintenance medication in patients with chronic obstructive pulmonary disease (COPD) in real life is known to deviate from recommendations in guidelines, which are largely based on randomized controlled trials and selected populations. Objectives: We used the COSYCONET (CO PD and Sy stemic Consequences – Co morbidities Net work) cohort to analyze factors linked to the use of COPD drugs under non-interventional circumstances. Design: COSYCONET is an ongoing, multi-center, non-interventional cohort of patients with COPD. Methods: Patients with COPD of Global Initiative for Chronic Obstructive Lung Disease (GOLD) grades 0–4 participating in visits 1–5 were included. Data covered the period from 2010 to 2018. Generalized linear models were used to examine the relation of COPD characteristics to different types of respiratory medication. Results: A total of 1043 patients were included. The duration of observation was 4.5 years. Use of respiratory medication depended on GOLD grades 0–4 and groups A-D. Long-acting muscarinic antagonist therapy increased over time, and was associated with low carbon monoxide (CO) diffusing capacity, while inhaled corticosteroid (ICS) use decreased. Active smoking was associated with less maintenance therapy in general, and female sex with less ICS use. From the eight items of the COPD Assessment Test, only hill and stair climbing were consistently linked to treatment. Conclusion: Using data from a large, close to real-life observational cohort, we identified factors linked to the use of various types of respiratory COPD medication. Overall, use was consistent with GOLD recommendations. Beyond this, we identified other correlates of medication use that may help us to understand and improve therapy decisions in clinical practice. Trial registration: ClinicalTrials.gov NCT01245933. [ABSTRACT FROM AUTHOR]

Background: Lung emphysema is an important phenotype of chronic obstructive pulmonary disease (COPD), and CT scanning is strongly recommended to establish the diagnosis. This study aimed to identify criteria by which physicians with limited technical resources can improve the diagnosis of emphysema.Methods: We studied 436 COPD patients with prospective CT scans from the COSYCONET cohort. All items of the COPD Assessment Test (CAT) and the St George's Respiratory Questionnaire (SGRQ), the modified Medical Research Council (mMRC) scale, as well as data from spirometry and CO diffusing capacity, were used to construct binary decision trees. The importance of parameters was checked by the Random Forest and AdaBoost machine learning algorithms.Results: When relying on questionnaires only, items CAT 1 & 7 and SGRQ 8 & 12 sub-item 3 were most important for the emphysema- versus airway-dominated phenotype, and among the spirometric measures FEV1/FVC. The combination of CAT item 1 (≤ 2) with mMRC (> 1) and FEV1/FVC, could raise the odds for emphysema by factor 7.7. About 50% of patients showed combinations of values that did not markedly alter the likelihood for the phenotypes, and these could be easily identified in the trees. Inclusion of CO diffusing capacity revealed the transfer coefficient as dominant measure. The results of machine learning were consistent with those of the single trees.Conclusions: Selected items (cough, sleep, breathlessness, chest condition, slow walking) from comprehensive COPD questionnaires in combination with FEV1/FVC could raise or lower the likelihood for lung emphysema in patients with COPD. The simple, parsimonious approach proposed by us might help if diagnostic resources regarding respiratory diseases are limited. Trial registration ClinicalTrials.gov, Identifier: NCT01245933, registered 18 November 2010, https://clinicaltrials.gov/ct2/show/record/NCT01245933 . [ABSTRACT FROM AUTHOR]