Prolonged durations of high-intensity exercises such as climbing, lead to an accumulation of metabolic compounds associated with different energy pathways to buffer decreases in muscular adenosine triphosphate (ATP) concentrations. Many of them have dilatative functions and therefore enhance blood flow kinetics. Even though many compounds accumulate, evidence suggests that the primary drivers causing muscular fatigue are inorganic phosphates (Pi) and hydrogen protons (H+) [20]. The latter one decreases pH levels, and those circumstances cause a configuration shift of hemoglobin due to changes in protein folding, classified as taut form. This results in releasing oxygen in favor of the attachment of H+, decreasing hemoglobin's affinity for oxygen, weakening its binding capacity, and increasing the likelihood of dissociation, which causes a rightward shift of the hemoglobin dissociation curve [21, 22]. Oxygen-dependent light absorption differences in the near-infrared light spectrum make it possible to measure changes between the two forms of hemoglobin. NIRS, therefore, represents a valid method for measuring oxidative muscle metabolism [23] and the simultaneous analysis of oxy[heme] (O2Hb) and deoxy[heme] (HHb), total[heme] (tHb), and tissue saturation index (TSI) gives interesting insights into muscle oxygenation in climbing-specific settings.
In sub-study 1, NIRS parameters that determined the number of valid repetitions in the intermittent finger endurance test were the mean maxima for O2Hb, the mean maxima in relation to baseline values for TSI, and the mean minima for O2Hb. Accordingly, climbers with better test performances showed higher O2Hb concentrations at the beginning of each load period (maxima) and lower O2Hb concentrations at the end of each load period (minima), representing a wider span between maxima and minima. In the context of the existing literature, higher O2Hb concentration changes between climbers and non-climbers were reported by MacLeod et al. (2007) [9] during the relief phase of intermittent finger endurance tests, which is in accordance with our study, whereas Baláš et al. (2021) [14] found no differences for various ability groups. When looking at continuous tests, climbers/ elite level climbers deoxygenated the flexor digitorum profundus significantly more [6, 9] and faster [6] than non-climbers/ lower level climbers, which is in line with our findings, but again, in contrast, Baláš et al. (2021) [14] found no ability group differences. The differences between studies remain unclear and require further investigations since it seems unlikely they relate to the participant's characteristics.
The physiological and anatomical adaptations behind the findings above might be macro-and microvascular adaptations and shorter muscle fiber relaxation times [9]. The evidence is partly conflicting regarding macrovascular adaptations: Thompson et al. (2015) [24] assessed brachial arterial structure, blood flow, and function. They found greater resting, peak, and maximal brachial artery diameters and a higher peak reactive hyperaemic blood flow but no differences in flow-mediated dilation between climbers and controls during rest or after ischaemic conditions. Fryer et al. (2015) [6] found no ability group differences for brachial artery blood velocity and blood flow during a continuous finger endurance test. Fergurson and Brown (1997) [25] reported a significantly higher vascular conductance of climbers than non-climbers using continuous and intermittent finger endurance tests. On the microvascular level, Thompson et al. (2015) [24] reported a higher capillary filtration capacity in climbers than in controls, which has been suggested to be the main factor for differences in oxygen kinetics measured via NIRS and being a training-induced adaptation [12, 26].
Even though climbers with better test performances had a wider span between minima and maxima O2Hb concentration levels, the direct measurements of concentration changes during single repetitions (delta contraction and delta relaxation) were no significant predictors of intermittent finger endurance test performance. This might be because the calculation of deltas requires an accurate minimum and maximum, which means they are more sensitive to motion-induced measurement artifacts than single minima and maxima.
Regarding the comparison between the last valid repetition and the first nonvalid repetition, the nonsignificant difference on the combined dependent variable indicates, that either muscular fatigue is a continuous process, at least in the case where the load is kept constant for the entire duration of the exercise, or that physiological breakpoints do not match with the declined force output responsible for the differentiation between valid and nonvalid repetitions
Regarding sub-study 2, evaluating oxygen kinetics during competitive lead climbing has not yet been done. Therefore, this study breaks new scientific and technological ground and reveals interesting insights into the oxygen kinetics in climbing.
In detail, O2Hb showed no significant univariate within-subjects effects. This is surprising given that most studies on the oxygen response in incremental ramp exercises showed decreases in O2Hb concentrations during the test period [27]. As explained, the physiological mechanism behind this would be the rightward shift of the hemoglobin dissociation curve[21, 22, 27]. We couldn't observe such a decrease because of the intermittent structure of load and relief phases of the forearm flexor muscles in lead climbing. In highly trained lead climbers, the short relief phases could be enough for sufficient reoxygenation of the forearm muscles. Studies during intermittent finger endurance tests on the fingerboard showed that climbers have higher relief phase reoxygenation than non-climbers, which explained 41.1% of the force-time integral [9, 12]. On the contrary, Baláš et al. (2021) [14] found no significant differences in relief phase reoxygenation between advanced and recreational climbers.
Regarding HHb changes, we observed an accumulation in the concentration levels during the competitive climbing test, similar to findings during incremental exercises (for a review, see Boone et al. (2016) [27]). This indicates a cumulative load on the participant's forearm flexor muscles due to increasing difficulties of the climbing route. When comparing the HHb curve shape with the one described by Boone et al. (2016)[27] (a sigmoid shape with a sluggish increase at the onset of incremental ramp exercise at very low work intensities), we observed a steep slope right from the beginning, which indicates that already the first moves required efforts of moderate intensities. Breakpoints in HHb response could be visually detected by identifying inflection points in 46% of the climbing attempts. HHb breakpoints are associated with integrated electromyography, ventilatory and muscle lactate thresholds, and critical power [27, 28]. However, in contrast to the study of Baláš et al. (2021) [14], the breakpoints could not precisely be calculated due to the influence of shaking, chalking, and clipping phases chosen by the athletes in a competition-like climbing route. In follow-up studies, rest phases could be eliminated to analyze the occurrence of breakpoints in HHb responses during wall climbing.
For the tHb response, significant univariate within-subjects effects had been found. T-tests further revealed a significant increase between the last 20 s interval and the first one, the comparison between the last and the second-last interval, however showed higher tHb concentration levels in the last interval, but didn't reach significance. It still seems unlikely that tHb, as observed in other studies by Boone et al. (2016) [27], levels off towards the end of incremental ramp exercises since we didn't observe any significant changes in the O2Hb concentration, and its attenuation of the decrease rate has been associated with a reduction in tHb. Instead, the data indicate a steady increase of tHb, given that tHb is calculated as the sum of O2Hb and HHb, with O2Hb remaining constant and HHb constantly increasing.
Lastly, TSI showed a decreasing trend during the climbing attempts. Similarly to tHb, significant differences were found between the last 20 s interval and the first but not between the last and the second-last intervals, even though the decreasing trend continued. Yet again, the rising HHb concentration is the main underlying driver for the observed changes in TSI.
Limitations
The study contains several limitations: First, limitations regarding the sample size in both sub-studies. In sub-study one, recreational to elite level climbers participated; however, despite the large range of ability groups, at a closer look, most of the participants were classified as recreational to advanced level climbers, with only one participant being categorized as an elite climber. The underrepresentation of elite to higher elite-level climbers, therefore, limits the generalizability of the study´s findings. The same is true for sub-study 2, where the sample consisted of a small and, in terms of climbing abilities, very homogenous group of climbers, with the sample size being considered too small for the calculation of regression analyses. Secondly, in sub-study one, two adjacent repetitions out of a whole series of repetitions were compared, with the criteria for distinguishing valid and nonvalid repetitions, even though being well thought of [17], do represent external criteria that are not based on physiological break points. Moreover, the calculation of NIRS parameters of the first nonvalid interval required participants to perform at least two more repetitions after not being able to exert the required target force anymore. This implies, that data sets of participants who couldn´t perform at least two more repetitions and therefore may have different fatigue kinetics, were systematically excluded. However, since we aimed to distinguish between valid and nonvalid repetitions, this is a study-inherent problem. Thirdly, in sub-study two, breakpoints in HHb response, which reveal interesting insights into muscle oxygen kinetics, could not be determined due to the influence of shaking, chalking, and clipping phases.