Towards an individualized protocol for workload increments in cardiopulmonary exercise testing in children and adolescents with cystic fibrosis

Abstract

Background: There is no single optimal exercise testing protocol for children and adolescents with cystic fibrosis (CF) that differs widely in age and disease status. The aim of this study was to develop a CF-specific, individualized approach to determine workload increments for a cycle ergometry testing protocol.

Methods: A total of 409 assessments consisting of maximal exercise data, anthropometric parameters, and lung function measures from 160 children and adolescents with CF were examined. 90% of the database was analyzed with backward linear regression with peak workload (W(peak)) as the dependent variable. Afterwards, we [1] used the remaining 10% of the database (model validation group) to validate the model's capacity to predict W(peak) and [2] validated the protocol's ability to provide a maximal effort within a 10±2 minute time frame in 14 adolescents with CF who were tested using this new protocol (protocol validation group).

Results: No significant differences were seen in W(peak) and predicted W(peak) in the model validation group or in the protocol validation group. Eight of 14 adolescents with CF in the protocol validation group performed a maximal effort, and seven of them terminated the test within the 10±2 minute time frame. Backward linear regression analysis resulted in the following equation: W(peak) (W)=-142.865+2.998×Age (years)-19.206×Sex (0=male; 1=female)+1.328×Height (cm)+23.362×FEV(1) (L) (R=.89; R(2)=.79; SEE=21). Bland-Altman analysis showed no systematic bias between the actual and predicted W(peak).

Conclusion: We developed a CF-specific linear regression model to predict peak workload based on standard measures of anthropometry and FEV(1), which could be used to calculate individualized workload increments for a cycle ergometry testing protocol.