Forced oscillatory parameters as predictors of COPD assessment test improvement in untreated COPD patients

Background Few studies have examined whether baseline spirometry and the forced oscillation technique (FOT) would predict The COPD Assessment Test (CAT) score improvement after treatment of untreated COPD patients. Methods The study subjects included 65 untreated COPD patients. They underwent the CAT, spirometry, and FOT (MostGraph) before and after treatment for more than 2 months. In addition, recursive partitioning analysis was performed using spirometry and the FOT parameters to identify the predictors of CAT improvement (CAT score ≥2). Results CAT scores and lung function significantly improved after treatment. Recursive partitioning analysis identified 3 improved classes, defined by Rrs at 20 Hz (R20), Xrs at 5 Hz (X5), and ΔX5, but not by spirometry. The accuracy of predicting CAT improvement was as follows: odds ratio, 25.3; 95 % confidence interval, 6.1 to 104.1; sensitivity, 91.2 %; specificity, 71.0 %; positive likelihood ratio, 3.14; and negative likelihood ratio, 0.12. Conclusions FOT helps predict improved health status in untreated COPD patients.