Why the study?
It was unclear how metabolic thresholds derived from local muscle oxygen saturation signals agree with pulmonary ventilatory thresholds in trained cyclists across age groups and performance characteristics.
Although breakpoints can be identified in NIRS-captured SmO2 signals, their agreement with systemic ventilatory thresholds is too low to be used interchangeably in practical training for cyclists.
May support NIRS-derived thresholds in trained cyclists; hypothesis-generating and requires prospective validation before any clinical use.
This study focused on comparing metabolic thresholds derived from local muscle oxygen saturation (SmO2) signals, obtained using near-infrared spectroscopy (NIRS), with global pulmonary ventilation rates measured at the mouth. It was conducted among various Age Groups within a well-trained cyclist population. Additionally, the study examined how cycling performance characteristics impact the discrepancies between ventilatory thresholds (VTs) and SmO2 breakpoints (BPs). Methods: Junior (n = 18) and Senior (n = 15) cyclists underwent incremental cycling tests to assess their aerobic performance and to determine aerobic (AeT) and anaerobic (AnT) threshold characteristics through pulmonary gas exchange and changes in linearity of the vastus lateralis (VL) muscle SmO2 signals. We compared the relative power (Pkg) at ventilatory thresholds (VTs) and breakpoints (BPs) for the nondominant (ND), dominant (DO), and bilaterally averaged (Avr) SmO2 during the agreement analysis. Additionally, a 30 s sprint test was performed to estimate anaerobic performance capabilities and to assess the cyclists’ phenotype, defined as the ratio of P@VT2 to the highest 5 s sprint power. Results: The Pkg@BP for Avr SmO2 had higher agreement with VT values than ND and DO. Avr SmO2 Pkg@BP1 was lower (p < 0.05) than Pkg@VT1 (mean bias: 0.12 ± 0.29 W/kg; Limits of Agreement (LOA): −0.45 to 0.68 W/kg; R2 = 0.72) and mainly among Seniors (0.21 ± 0.22 W/kg; LOA: −0.22 to 0.63 W/kg); there was no difference (p > 0.05) between Avr Pkg@BP2 and Pkg@VT2 (0.03 ± 0.22 W/kg; LOA: −0.40 to 0.45 W/kg; R2 = 0.86). The bias between two methods correlated significantly with the phenotype (r = −0.385 and r = −0.515 for AeT and AnT, respectively). Conclusions: Two breakpoints can be defined in the NIRS-captured SmO2 signal of VL, but the agreement between the two methods at the individual level was too low for interchangeable usage of those methods in the practical training process. Older cyclists generally exhibited earlier thresholds in muscle oxygenation signals compared to systemic responses, unlike younger cyclists who showed greater variability and no significant differences in this regard in bias values between the two threshold evaluation methods with no significant difference between methods. More sprinter-type cyclists tended to have systemic VT thresholds earlier than local NIRS-derived thresholds than athletes with relatively higher aerobic abilities.
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Reinpõld et al. (2024) studied this question.
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