Prediction of lung hyperinflation in advanced COPD from spirometry and demographics

<bold>Background:</bold> Lung hyperinflation is a key selection criterion for lung volume reduction (LVR) eligibility. Lung hyperinflation is assessed using body plethysmography, which is time-consuming and not available in all healthcare settings. An ability to predict hyperinflation from routinely collected measures would allow early identification of potential LVR candidates. <bold>Objective:</bold> To predict lung hyperinflation using spirometry and demographic measures. Study design: Retrospective analysis of 209 COPD individuals with advanced COPD and full pulmonary function test data. Age, gender, height, weight, FEV1, and FVC were used to create a logistic regression. ROC analysis using an RV/TLC of 55% was used to assess the model’s performance. <bold>Results:</bold> Among the study participants, 56% were male. The mean age was 66 (39.4) years, the BMI was 25.7 (6.7) kg, and the FEV1% predicted was 34.78 (12.97). FEV1 and demographics explained 47% of the variability in RV/TLC. ROC analysis using the predicted values of the logistic regression of RV/TLC indicated good accuracy with an area under the curve of 0.85. The positive predictive value was 91.4%, and the negative predictive value was 72.14%. <bold>Conclusion:</bold> Lung hyperinflation can be estimated using spirometry and demographic data. This could help identify individuals with COPD who may be candidates for LVR.