A New Maximal Bicycle Test Using A Prediction Algorithm Developed From Four Large Copd Studies

Background: Maximum exercise workload (W-MAX) is today assessed as the first part of Cardiopulmonary Exercise testing. The W-MAX test exposes patients with COPD, often having cardiovascular comorbidity, to risks. Our research project was initiated with the final aim to eliminate the W-MAX test and replace this test with a predicted value of W-MAX, based on a prediction algorithm of W-MAX derived from multicentre studies. Methods: Baseline data (W-MAX, demography, lung function parameters) from 850 COPD patients from four multicentre studies were collected and standardized. A prediction algorithm was prepared using Random Forest modelling. Predicted values of W-MAX were used in a new W-MAX test, which used a linear increase in order to reach the predicted W-MAX within 8 min. The new W-MAX test was compared with the standard stepwise W-MAX test in a pilot study including 15 patients with mild/moderate COPD. Results: The best prediction algorithm of W-MAX included age, sex, height, weight, and six lung function parameters. FEV1 and DLCO were the most important predictors. The new W-MAX test had a better correlation (R-2 = 0.84) between predicted and measured W-MAX than the standard W-MAX test (R-2 = 0.66), with slopes of 0.50 and 0.46, respectively. The results from the new W-MAX test and the standard W-MAX test correlated well. Conclusion: A prediction algorithm based on data from four large multicentre studies was used in a new W-MAX test. The prediction algorithm provided reliable values of predicted W-MAX. In comparison with the standard W-MAX test, the new W-MAX test provided similar overall results.