A new maximal bicycle test using a prediction algorithm developed from four large COPD studies

ABSTRACT

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. FEV ₁ 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.