BMJ open respiratory research · 2017
Predictive value of prebronchodilator and postbronchodilator spirometry for COPD features and outcomes.
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Fortis Spyridon, Eberlein Michael, Georgopoulos Dimitris, Comellas Alejandro P
Аннотация
INTRODUCTION: We compared the predictive value of prebronchodilator and postbronchodilator spirometry for chronic obstructive pulmonary disease (COPD) features and outcomes.
METHODS: We analysed COPDGene data of 10 192 subjects with smoking history. We created regressions models with the following dependent variables: clinical, functional and radiographic features, and the following independent variables: prebronchodilator airflow obstruction (PREO) and postbronchodilator airflow obstruction (POSTO), prebronchodilator and postbronchodilator FEV1% predicted. We compared the model performance using the Akaike information criterion (AIC).
RESULTS: The COPD prevalence was higher using PREO. About 8.5% had PREO but no airflow obstruction in postbronchodilator spirometry (POSTN) (PREO-POSTN) and 3% of all subjects had no aiflow obstruction in prebronchodilator spirometry (PREN) but POSTO (PREN-POSTO). We found no difference in COPD features and outcomes between PREO-POSTN and PREN-POSTO subjects. Although, both prebronchodilator and postbronchodilator spirometries are both associated with chronic bronchitis, dyspnoea, exercise capacity and COPD radiographic findings, models that included postbronchodilator spirometric measures performed better than models with prebronchodilator measures to predict these COPD features. The predictive value of prebronchodilator and postbronchodilator spirometries for respiratory exacerbations, change in forced expiratory volume in 1 s, dyspnoea and exercise capacity during a 5-year period is relatively similar, but postbronchodilator spirometric measures are better predictors of mortality based on AIC.
CONCLUSIONS: Postbronchodilator spirometry may be a more accurate predictor of COPD features and outcomes.
METHODS: We analysed COPDGene data of 10 192 subjects with smoking history. We created regressions models with the following dependent variables: clinical, functional and radiographic features, and the following independent variables: prebronchodilator airflow obstruction (PREO) and postbronchodilator airflow obstruction (POSTO), prebronchodilator and postbronchodilator FEV1% predicted. We compared the model performance using the Akaike information criterion (AIC).
RESULTS: The COPD prevalence was higher using PREO. About 8.5% had PREO but no airflow obstruction in postbronchodilator spirometry (POSTN) (PREO-POSTN) and 3% of all subjects had no aiflow obstruction in prebronchodilator spirometry (PREN) but POSTO (PREN-POSTO). We found no difference in COPD features and outcomes between PREO-POSTN and PREN-POSTO subjects. Although, both prebronchodilator and postbronchodilator spirometries are both associated with chronic bronchitis, dyspnoea, exercise capacity and COPD radiographic findings, models that included postbronchodilator spirometric measures performed better than models with prebronchodilator measures to predict these COPD features. The predictive value of prebronchodilator and postbronchodilator spirometries for respiratory exacerbations, change in forced expiratory volume in 1 s, dyspnoea and exercise capacity during a 5-year period is relatively similar, but postbronchodilator spirometric measures are better predictors of mortality based on AIC.
CONCLUSIONS: Postbronchodilator spirometry may be a more accurate predictor of COPD features and outcomes.