Analysis of Influencing Factors for Exercise Ventilation Efficiency of COPD Patients

Dynamic pulmonary hyperinflation and abnormal air exchange are the primary causes of the exercise limitation of chronic obstructive pulmonary disease (COPD) patients. During exercise, COPD sufferers' lungs are dynamically hyperinflated. Increased inefficient ventilation reduces ventilation efficiency and causes a mismatch between ventilation volume and blood flow. The ventilatory equivalent for CO(2) (VeqCO(2)) is a physiological parameter that can be measured using cardiopulmonary exercise testing. Therefore, the aim of this exploratory study was to perform cardiopulmonary exercise testing on people with COPD, investigate the impact of static pulmonary function on ventilation efficiency under the exercise state, and screen the predictive indicators of ventilation efficiency. Subject. The aim of this study was to look at the factors that influence the exercise ventilation efficiency of people with COPD. Method. A total of 76 people with COPD were recruited during the stable period. Age, gender, body height, body mass, and other basic information were recorded. The body mass index (BMI) was determined, and forced vital capacity (FVC), forced expiratory volume in one second (FEV1), residual volume/total lung capacity (RV/TLC), diffusing capacity of the lung for carbon monoxide (DLCO), and DLCO divided by the alveolar volume (DLCO/VA) were measured. The ventilatory equivalent for carbon dioxide (VE/VCO2) under the rest state (EqCO(2)rest), anaerobic threshold (EqCO(2)at), and maximum exercise state (EqCO(2) max) were calculated to investigate the influencing factors for ventilation efficiency of people with COPD. Results. FEV1% was negatively correlated with EqCO(2)rest (r = −0.277, P value <0.05); FEV1/FVC % was negatively correlated with EqCO2rest and EqCO2at (r = −0.311, −0.287, P value <0.05); DLCO% was negatively correlated with EqCO(2)rest, EqCO(2)at, and EqCO(2)max (r = −0.408, −0.462, and −0.285, P value <0.05); DLCO/VA% was negatively correlated with EqCO(2)rest, EqCO(2)at, and EqCO(2)max (r = −0.390, −0.392, and −0.245, P value <0.05); RV/TLC was positively correlated with EqCO2rest and EqCO2at (r = 0.289, 0.258, P-value <0.05). The prediction equation from the multivariable regression analysis equation was Y = 40.04–0.075X (Y = EqCO(2), X = DLCO/VA%). Conclusions. As the degree of ventilatory obstruction increased, the ventilation efficiency of the stable people with COPD under the exercise state showed a progressive decrease; the ventilation efficiency of the people with COPD decreased significantly under the maximum exercise state, and the ventilation capacity and diffusion capacity were the significant factors that affected the exercise ventilation efficiency. The diffusion function may predict the maximum ventilation efficiency and enable primary hospitals without exercise test equipment in developing countries to predict and screen patients at risk for current exercise based on limited information.