Validation of a Revised V-Slope Algorithm for Automated First Ventilatory Threshold Detection in Healthy Adults

The first ventilatory threshold (VT1) is a key indicator of submaximal aerobic fitness. Its determination typically relies on visual assessment, which is time-consuming and subject to interobserver variability. Automated solutions may offer a more objective, reproducible and time-efficient alternative. This study evaluated the accuracy of a revised V-slope method.

This retrospective study was conducted at University Hospitals Leuven, Belgium, using cardiopulmonary exercise test (CPET) data of 271 healthy adults collected between 2010 and 2020. Automated VT1 detection using a revised V-slope algorithm was compared with manual determination via the visual V-slope method in 262 participants with a determinable VT1. Agreement was evaluated using Bland-Altman analysis, intraclass correlation coefficients (ICC), Deming regression and equivalence testing (TOST). Interobserver agreement was evaluated using ICC.

Median oxygen uptake at VT1 was higher with automated compared to manual assessment (1151 vs. 1122 mL/min; p < 0.001). Mean difference was 29 mL/min (95% CI [19, 40]. Relative mean bias was 2.2% ± 7.1% (LoA [- 11.7 to 16.0%], with excellent agreement (ICC 0.97 [95% CI 0.96-0.98] and a Deming regression slope of 0.95 [95% CI 0.92-0.99] and intercept of 26.1 mL/min [95% CI -11.9 to 64.7]. TOST with equivalence bounds [- 100, 100] was significant (p < 0.001; 90% CI [20, 38]).

The revised V-slope algorithm demonstrated strong group-level agreement with visual assessment for VT1 determination, supporting the reliability and practical applicability for large-scale research applications in healthy adults. However, given the observed individual-level variability, caution is warranted when applying automated VT1 values to guide exercise prescription for individual patients without expert review.