Side differences and reproducibility of the Moxy muscle oximeter during cycling in trained men.

PURPOSE: Portable near-infrared spectroscopy devices allow measurements of muscle oxygen saturation (SmO2) in real time and non-invasively. To use NIRS for typical applications including intensity control and load monitoring, the day-to-day variability needs to be known to interpret changes confidently. This study investigates the absolute and relative test-retest reliability of the Moxy Monitor and investigates side differences of SmO2 at the vastus lateralis muscle of both legs in cyclists. METHODS: Twelve trained cyclists and triathletes completed 3 incremental step tests with 5 min step duration starting at 1.0 W/kg with an increase of 0.5 W/kg separated by 2-7 days. SmO2 was averaged over the last minute of each stage. For all power outputs, the intra-class coefficient (ICC), the standard error of measurement (SEM) and the minimal detectable change (MDC) were calculated. Dominant and non-dominant leg SmO2 were compared using a three-factor ANOVA and limits of agreement (LoA). RESULTS: ANOVA showed no significant systematic differences between trials and side. For both legs and all intensities, the ICC ranged from 0.79 to 0.92, the SEM from 5 to 9% SmO2 and the MDC from 14 to 18% SmO2. The bias and LoA between both legs were -2.0% ± 19.9% SmO2. CONCLUSION: Relative reliability of SmO2 was numerically good to excellent according to current standards. However, it depends on the specific analytical goal whether the test-retest reliability is deemed sufficient. Wide LoA indicate side differences in muscle oxygenation during exercise unexplained by leg dominance.

Blood-Borne Markers of Fatigue in Competitive Athletes - Results from Simulated Training Camps.

Assessing current fatigue of athletes to fine-tune training prescriptions is a critical task in competitive sports. Blood-borne surrogate markers are widely used despite the scarcity of validation trials with representative subjects and interventions. Moreover, differences between training modes and disciplines (e.g. due to differences in eccentric force production or calorie turnover) have rarely been studied within a consistent design. Therefore, we investigated blood-borne fatigue markers during and after discipline-specific simulated training camps. A comprehensive panel of blood-born indicators was measured in 73 competitive athletes (28 cyclists, 22 team sports, 23 strength) at 3 time-points: after a run-in resting phase (d 1), after a 6-day induction of fatigue (d 8) and following a subsequent 2-day recovery period (d 11). Venous blood samples were collected between 8 and 10 a.m. Courses of blood-borne indicators are considered as fatigue dependent if a significant deviation from baseline is present at day 8 (Δfatigue) which significantly regresses towards baseline until day 11 (Δrecovery). With cycling, a fatigue dependent course was observed for creatine kinase (CK; Δfatigue 54±84 U/l; Δrecovery -60±83 U/l), urea (Δfatigue 11±9 mg/dl; Δrecovery -10±10 mg/dl), free testosterone (Δfatigue -1.3±2.1 pg/ml; Δrecovery 0.8±1.5 pg/ml) and insulin linke growth factor 1 (IGF-1; Δfatigue -56±28 ng/ml; Δrecovery 53±29 ng/ml). For urea and IGF-1 95% confidence intervals for days 1 and 11 did not overlap with day 8. With strength and high-intensity interval training, respectively, fatigue-dependent courses and separated 95% confidence intervals were present for CK (strength: Δfatigue 582±649 U/l; Δrecovery -618±419 U/l; HIIT: Δfatigue 863±952 U/l; Δrecovery -741±842 U/l) only. These results indicate that, within a comprehensive panel of blood-borne markers, changes in fatigue are most accurately reflected by urea and IGF-1 for cycling and by CK for strength training and team sport players.

Can the Lamberts and Lambert Submaximal Cycle Test Indicate Fatigue and Recovery in Trained Cyclists?

The Lamberts and Lambert Submaximal Cycle Test (LSCT) is a novel test designed to monitor performance and fatigue/recovery in cyclists. Studies have shown the ability to predict performance; however, there is a lack of studies concerning monitoring of fatigue/recovery. In this study, 23 trained male cyclists (age 29 ± 8 y, VO2max 59.4 ± 7.4 mL · min(-1) · kg(-1)) completed a training camp. The LSCT was conducted on days 1, 8, and 11. After day 1, an intensive 6-day training period was performed. Between days 8 and 11, a recovery period was realized. The LSCT consists of 3 stages with fixed heart rates of 6 min at 60% and 80% and 3 min at 90% of maximum heart rate. During the stages, power output and rating of perceived exertion (RPE) were determined. Heart-rate recovery was measured after stage 3. Power output almost certainly (standardized mean difference: 1.0) and RPE very likely (1.7) increased from day 1 to day 8 at stage 2. Power output likely (0.4) and RPE almost certainly (2.6) increased at stage 3. From day 8 to day 11, power output possibly (-0.4) and RPE likely (-1.5) decreased at stage 2 and possibly (-0.1) and almost certainly (-1.9) at stage 3. Heart-rate recovery was likely (0.7) accelerated from day 1 to day 8. Changes from day 8 to day 11 were unclear (-0.1). The LSCT can be used for monitoring fatigue and recovery, since parameters were responsive to a fatiguing training and a following recovery period. However, consideration of multiple LSCT variables is required to interpret the results correctly.

Effects of training-induced fatigue on pacing patterns in 40-km cycling time trials.

INTRODUCTION: In some endurance sports, athletes complete several competitions within a short period, resulting in accumulated fatigue. It is unclear whether fatigued athletes choose the same pacing pattern (PP) as when they have recovered. PURPOSE: This study aimed to analyze effects of fatigue on PP of cyclists during a 40-km time trial (TT). METHODS: Twenty-three male cyclists (28.8 ± 7.6 yr) completed three 40-km TT on a cycle ergometer. TT were conducted before (TT1) and after (TT2) a 6-d training period. A third TT was carried out after 72 h of recovery (TT3). Training days consisted of two cycling sessions: mornings, 1 h at 95% of lactate threshold or 3 × 5 × 30 s all-out sprint; afternoons, 3 h at 80% individual anaerobic threshold. Four-kilometer split times (min) and RPE were recorded during TT. RESULTS: Performance decreased from TT1 to TT2 (65.7 ± 3.5 vs 66.7 ± 3.3 min; P < 0.05) and increased from TT2 to TT3 (66.7 ± 3.3 vs 65.5 ± 3.3 min; P < 0.01). PP showed a significant difference between TT1 and TT2 (P < 0.001) as well as between TT2 and TT3 (P < 0.01). PP in TT1 and TT3 showed no significant difference (P > 0.05). In TT1 and TT3, cyclists started faster in the first 4 km compared with TT2. RPE course showed no significant difference between TT (P > 0.05). CONCLUSIONS: Fatigue reversibly changes the PP of cyclists during a 40-km TT. Participants reduced their power output until premature exhaustion seemed very unlikely. This supports the assumption that pacing includes a combination of anticipation and feedback mechanisms.