Prediction of lung emphysema in COPD by spirometry and clinical symptoms: results from COSYCONET.

ABSTRACT:

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 quest

SUBMITTER: Kellerer C 

PROVIDER: S-EPMC8427948 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature