A new method for estimating the first ventilatory threshold in patients with chronic respiratory diseases: A feasibility study.

Pernot J; Ribon A; Degano B;

Respiratory medicine and research [Respir Med Res] 2023 Apr 29; Vol. 83, pp. 101022.
Date of Electronic Publication: 2023 Apr 29.

Background: The identification of the first ventilatory threshold (VT1) on an incremental cardiopulmonary exercise test (CPET) is useful to guide exercise reconditioning. However, determination of the VT1 is sometimes difficult in patients with chronic respiratory disease. Our hypothesis was that it would be possible to identify a “clinical threshold” based on patients’ perceptions at which they subjectively consider that they can perform endurance training during a rehabilitation programme.
Methods: Workloads at which patients identified a “clinical threshold” during a submaximal exercise were compared with workloads recorded at VT1 determined during a maximal CPET. Patients with a VT1 and/or a “clinical threshold” obtained at a workload <25 W were excluded from the analysis.
Results: A “clinical threshold” could be determined in the 86 patients included. Data from 63 patients were retained for the analysis, of which only 52 had a VT1 that could be identified. The agreement between the workloads determined at VT1 and at the “clinical threshold” was almost perfect, with a Lin’s concordance coefficient (cc) of 0.82.
Conclusions: In the context of chronic respiratory diseases, it is possible to use patients’ sensations (which are by nature subjective) to identify a workload on a cycle ergometer, which corresponds to the workload at the first ventilatory threshold determined objectively during CPET.
Competing Interests: Declaration of Competing Interest Prof. Degano reports personal fees and non-financial support from GSK, Chiesi, AstraZeneca, Nuvaira, Menarini and Boehringer Ingelheim, outside the submitted work. The other authors declare that they have no conflict of interest for the submitted work. The results of the present study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.