Effect of the Fran CrossFit Workout on Oxygen Uptake Kinetics, Energetics, and Postexercise Muscle Function in Trained CrossFitters

PURPOSE

Fran is one of the most popular CrossFit benchmark workouts used to control CrossFitters' improvements. Detailed physiological characterization of Fran is needed for a more specific evaluation of CrossFitters' training performance improvements. The aim of the study was to analyze the oxygen uptake (V˙O2) kinetics and characterize the energy system contributions and the degree of postexercise fatigue of the unbroken Fran.

METHODS

Twenty trained CrossFitters performed Fran at maximal exertion. V˙O2 and heart-rate kinetics were assessed at baseline and during and post-Fran. Blood lactate and glucose concentrations and muscular fatigue were measured at baseline and in the recovery period.

RESULTS

A marked increase in V˙O2 kinetics was observed at the beginning of Fran, remaining elevated until the end (V˙O2peak: 49.2 [3.7] mL·kg-1·min-1, V˙O2 amplitude: 35.8 [5.2] mL·kg-1·min-1, time delay: 4.7 [2.5] s and time constant: 23.7 [11.1] s; mean [SD]). Aerobic, anaerobic lactic, and alactic pathways accounted for 62% (4%), 26% (4%), and 12% (2%) of energy contribution. Reduction in muscle function in jumping ability (jump height: 8% [6%], peak force: 6% [4%], and maximum velocity: 4% [2%]) and plank prone test (46% [20%]) was observed in the recovery period.

CONCLUSIONS

The Fran unbroken workout is a high-intensity effort associated with an elevated metabolic response. This pattern of energy response highlights the primary contribution of aerobic energy metabolism, even during short and very intense CrossFit workouts, and that recovery can take >24 hours due to cumulative fatigue.

Assessment of Cardiorespiratory and Metabolic Contributions in an Extreme Intensity CrossFit® Benchmark Workout

Our purpose was to characterize the oxygen uptake kinetics (VO2), energy systems contributions and total energy expenditure during a CrossFit® benchmark workout performed in the extreme intensity domain. Fourteen highly trained male CrossFitters, aged 28.3 ± 5.4 years, with height 177.8 ± 9.4 cm, body mass 87.9 ± 10.5 kg and 5.6 ± 1.8 years of training experience, performed the Isabel workout at maximal exertion. Cardiorespiratory variables were measured at baseline, during exercise and the recovery period, with blood lactate and glucose concentrations, including the ratings of perceived exertion, measured pre- and post-workout. The Isabel workout was 117 ± 10 s in duration and the VO2 peak was 47.2 ± 4.7 mL·kg-1·min-1, the primary component amplitude was 42.0 ± 6.0 mL·kg-1·min-1, the time delay was 4.3 ± 2.2 s and the time constant was 14.2 ± 6.0 s. The accumulated VO2 (0.6 ± 0.1 vs. 4.8 ± 1.0 L·min-1) value post-workout increased substantially when compared to baseline. Oxidative phosphorylation (40%), glycolytic (45%) and phosphagen (15%) pathways contributed to the 245 ± 25 kJ total energy expenditure. Despite the short ~2 min duration of the Isabel workout, the oxygen-dependent and oxygen-independent metabolism energy contributions to the total metabolic energy release were similar. The CrossFit® Isabel requires maximal effort and the pattern of physiological demands identifies this as a highly intensive and effective workout for developing fitness and conditioning for sports.

The reliability of back-extrapolation in estimating V˙O2peak in different swimming performances at the severe-intensity domain

The amount of anerobic energy released during exercise might modify the initial phase of oxygen recovery (fast-O2debt) post-exercise. Therefore, the present study aimed to analyze the reliability of peak oxygen uptake (V˙O2peak) estimate by back-extrapolation (BE−V˙O2peak) under different swimming conditions in the severe-intensity domain, verifying how the alterations of the V˙O2 recovery profile and anerobic energy demand might affect BE−V˙O2peak values. Twenty swimmers (16.7 ± 2.4 years, 173.5 ± 10.2 cm, and 66.4 ± 10.6 kg) performed an incremental intermittent step protocol (IIST: 6 × 250 plus 1 × 200 m, IIST_v200m) for the assessment of V˙O2peak. The V˙O2 off-kinetics used a bi-exponential model to discriminate primary amplitude, time delay, and time constant (A1off, TD1off, and τoff) for assessment of fast-O2debt post IIST_v200m, 200-m single-trial (v200 m), and rest-to-work transition at 90% delta (v90%Δ) tests. The linear regression estimated BE−V˙O2peak and the rate of V˙O2 recovery (BE-slope) post each swimming performance. The ANOVA (Sidak as post hoc) compared V˙O2peak to the estimates of BE−V˙O2peak in v200 m, IIST_v200 m, and v90%Δ, and the coefficient of dispersion (R2) analyzed the association between tests. The values of V˙O2peak during IIST did not differ from BE−V˙O2peak in v200 m, IIST_v200 m, and v90%Δ (55.7 ± 7.1 vs. 53.7 ± 8.2 vs. 56.3 ± 8.2 vs. 54.1 ± 9.1 ml kg−1 min−1, p > 0.05, respectively). However, the V˙O2peak variance is moderately explained by BE−V˙O2peak only in IIST_v200 m and v90%Δ (RAdj2 = 0.44 and RAdj2 = 0.43, p < 0.01). The TD1off and τoff responses post IIST_v200 m were considerably lower than those in both v200 m (6.1 ± 3.8 and 33.0 ± 9.5 s vs. 10.9 ± 3.5 and 47.7 ± 7.9 s; p < 0.05) and v90%Δ ( 10.1 ± 3.8 and 44.3 ± 6.3 s, p < 0.05). The BE-slope post IIST_v200m was faster than in v200 m and v90%Δ (-47.9 ± 14.6 vs. -33.0 ± 10.4 vs. -33.6 ± 13.8 ml kg−1, p < 0.01), and the total anerobic (AnaerTotal) demand was lower in IIST_v200 m (37.4 ± 9.4 ml kg−1) than in 200 m and 90%Δ (51.4 ± 9.4 and 46.2 ± 7.7 ml kg−1, p < 0.01). Finally, the τ1off was related to AnaerTotal in IIST_v200m, v200 m, and v90%Δ (r = 0.64, r = 0.61, and r = 0.64, p < 0.01). The initial phase of the V˙O2 recovery profile provided different (although reliable) conditions for the estimate of V˙O2peak with BE procedures, which accounted for the moderate effect of anerobic release on V˙O2 off-kinetics, but compromised exceptionally the V˙O2peak estimate in the 200-m single trial.

Anaerobic Contribution Determined in Free-Swimming: Sensitivity to Maturation Stages and Validity

Evaluation of anaerobic contribution is important under swimming settings (training and modification through ages), therefore, it is expected to change during maturation. The accumulated oxygen deficit (AOD) method can be used to determine the contribution of nonoxidative energy during swimming; however, it requires several days of evaluation. An alternative method to estimate anaerobic contribution evaluation (AC_ALT), which can also be evaluated without snorkel (i.e., free-swimming, AC_FS), has been proposed; however, these methods have never been compared. Thus, this study (i) analyzed the effect of maturation stage on AC_FS during maximal 400 m swimming (Part I), and (ii) compared AOD with AC_ALT and AC_FS, determined in a maximal 400 m effort (Part II). In Part I, 34 swimmers were divided into three groups, according to maturation stages (early-pubertal, middle-pubertal, and pubertal), and subjected to a maximal 400 m free-swimming to determine AC_FS. In Part II, six swimmers were subjected to one 400 m maximal effort, and four submaximal constant efforts. The AOD was determined by the difference between the estimated demand and accumulated oxygen during the entire effort. The AC_ALT and AC_FS (for Part I as well) was assumed as the sum of lactic and alactic anaerobic contributions. AC_FS was higher in pubertal (3.8 ± 1.1 L) than early (2.1 ± 0.9 L) and middle pubertal group (2.4 ± 1.1 L). No difference was observed among absolute AOD (3.2 ± 1.3 L), AC_ALT (3.2 ± 1.5 L), and AC_FS (4.0 ± 0.9 L) (F = 3.6; p = 0.06). Relative AOD (51.8 ± 12.2 mL·kg⁻¹), AC_ALT (50.5 ± 14.3 mL·kg⁻¹), and AC_FS (65.2 ± 8.8 mL·kg⁻¹) presented main effect (F = 4.49; p = 0.04), without posthoc difference. The bias of AOD vs. AC_ALT was 0.04 L, and AOD vs. AC_FS was −0.74 L. The limits of agreement between AOD and AC_ALT were +0.9 L and −0.8 L, and between AOD and AC_FS were +0.7 L and −2.7 L. It can be concluded that AC_FS determination is a feasible tool to determine anaerobic contribution in young swimmers, and it changes during maturation stages. Also, AC_FS might be useful to measure anaerobic contribution in swimmers, especially because it allows greater speeds.

The Effect of Inspiratory Muscle Warm-Up on VO2 Kinetics during Submaximal Rowing

The aim of the study was to investigate the effect of an inspiratory muscle warm-up on the VO₂ kinetics during submaximal intensity ergometer rowing. Ten competitive male rowers (age 23.1 ± 3.8 years; height 188.1 ± 6.3 cm; body mass 85.6 ± 6.6 kg) took part in this investigation. A submaximal constant intensity (90% P_VO2max) rowing test to volitional exhaustion was carried out twice with the standard rowing warm-up (Test 1) and with the standard rowing warm-up with additional specific inspiratory muscle warm-up of two sets of 30 repetitions at 40% maximal inspiratory pressure (Test 2). We found a significant correlation between time constant (τ₁) and the VO₂ value at 400 s in Test 1 (r = 0.78; p < 0.05); however, no correlation was found between those parameters in Test 2. In addition, we found a positive association between VO_2max from the incremental rowing test and τ₁ from Test 1 (r = 0.71; p < 0.05), whereas VO₂ did not correlate with τ₁ from Test 2. Adding inspiratory muscle warm-up of 40% maximal inspiratory pressure to regular rowing warm-up had no significant effect on oxygen consumption kinetics during submaximal rowing tests.

Recovery Off-Kinetics Following Exhaustive Upper Body Exercise in Spinal Cord Injury

Background

People with spinal cord injury (SCI) present with impaired autonomic control when the lesion is above T6. This could lead to delayed cardiorespiratory recovery following vigorous physical activity.

Objectives

To characterize and compare gas exchange off-kinetics following exhaustive exercise in individuals with SCI and an apparently healthy control group.

Methods

Participants were 19 individuals with SCI who presented with the inability to voluntarily lift their legs against gravity (age, 44.6 ± 14.2 years; AIS A, n = 5; AIS B, n = 7; AIS C, n = 7; paraplegia, n = 14; tetraplegia, n = 5) and 10 healthy comparisons (COM; age, 30.5 ± 5.3 years). All participants performed an arm ergometer cardiopulmonary exercise test (aCPET) to volitional exhaustion followed by a 10-minute passive recovery. O₂ uptake (V̇o₂ ) and CO₂ output (V̇co₂ ) off-kinetics was examined using a mono-exponential model in which tau off (τ_off ) and mean response time (MRT) were determined. The off-kinetics transition constant (Kt_off ) was calculated as ΔV̇o₂ /MRT. Student t tests were used to compare SCI versus COM group means.

Results

COM had a significantly higher relative peak V̇o₂ compared to SCI (1.70 ± 0.55 L/min vs 1.19 ± 0.51 L/min, p = .019). No difference was observed for τ_off between the groups, however Kt_off for both V̇o₂ and V̇co₂ was significantly lower in the SCI compared to the COM group.

Conclusion

A reduced Kt_off during recovery may suggest inefficiencies in replenishing muscle ATP stores and lactate clearance in these participants with SCI. These findings may contribute to the observed lower cardiorespiratory fitness and greater fatigability typically reported in individuals with SCI.

Post-swim oxygen consumption: assessment methodologies and kinetics analysis

OBJECTIVE

This study aimed at comparing different recovery-based methods to assess the highest exercise oxygen uptake value ([Formula: see text]O₂peak) when swimming at low-moderate, heavy and severe intensities. Complementarily, the different recovery curve kinetics were analysed.

APPROACH

Eighteen competitive swimmers performed a 5 × 200 m front crawl intermittent protocol (0.05 m · s^-1 increments and 3 min intervals), with respiratory gas exchange being continuously measured breath-by-breath during and post-exercise using a portable gas analyser. The directly determined [Formula: see text]O₂peak ([Formula: see text]O_2dir) was compared with the values obtained by linear and exponential backward extrapolations (of different intervals) and the recovery curve mathematical modelling.

MAIN RESULTS

[Formula: see text]O_2dir rose with intensity increase: 41.96 ± 6.22, 46.36 ± 6.89 and 50.97 ± 7.28 ml · kg^-1 min^-1 for low-moderate, heavy and severe swims. Linear and exponential regressions applied to the first 20 s of recovery presented the [Formula: see text]O₂peak values closest to [Formula: see text]O_2dir at low-moderate (42.80 ± 5.54 vs 42.88 ± 5.58 ml kg^-1 min^-1), heavy (47.12 ± 4.91 vs 47.48 ± 5.09 ml kg^-1 min^-1) and severe intensity domains (51.24 ± 6.89 vs 53.60 ± 8.54 ml kg^-1 · min^-1, respectively; r = 0.5-0.8, p < 0.05). The mono-exponential function was the best fit at low-moderate and heavy intensities, while the bi-exponential function better characterized the severe exercise domain (with a slow component amplitude, time delay and time constant of 6.2 ± 2.3 ml kg^-1 min^-1, 116.6 ± 24.3 and 39.9 ± 15.2 s, respectively).

SIGNIFICANCE

The backward extrapolation of the first 20 s of recovery is the best method to assess the [Formula: see text]O₂peak for a large spectrum of swimming intensities. Complementarily, intensity increases imply different recovery curve kinetics, particularly a mono-exponential behaviour for low-moderate and heavy exertions and a bi-exponential dynamics for severe paces.

Backward extrapolation technique: analysis of different criteria after supramaximal exercise in cycling

BACKGROUND

Backward extrapolation technique (BE) was used to estimate V̇O<inf>2</inf> from postexercise measuring, eliminating oronasal mask (OM) during the efforts. Despite its advantage, literature presents discrepancy in applied methods. Thus, the first aim of this study was to compare different mathematical criteria to estimate values of V̇O<inf>2</inf> during a supramaximal effort (V̇O<inf>2PEAK</inf>), while the second aim was to verify the effects of OM on cycling performance.

METHODS

Twenty-four male cyclists (35±6 years, 81.3±8.9 kg, 180±6 cm) performed three days of tests, with at least 24 h of interval between each test. Firstly, a graded exercise test was applied to determine V̇O<inf>2max</inf> and your correspondent intensity (MAP). The second and the third day were destined to supramaximal efforts at 120% of MAP, performed with (Supra<inf>mask</inf>) and without (Supra<inf>be</inf>) oronasal mask (OM) in a randomized order. After Supra<inf>be</inf>, OM was coupled, and BE was applied. Sixty-six values of V̇O<inf>2</inf> were obtained based on a linear regression fitting.

RESULTS

V̇O<inf>2peak</inf> can be estimated using different curve lengths. However, only curves between 20 and 60 s with extrapolation to 3 s or lesser shows at least one consistent criterion. The 60 s curve extrapoled to -3 s was the most accurate criteria (P=0.723; ES=-0.055; r=0.824; Bias=-0.36 and LoA=7.72 mL.kg.min^-1). Performance was not impaired with OM and was similar in both condition (P=0.84, ES=0.04).

CONCLUSIONS

We conclude that it was possible to accurately estimate V̇O<inf>2</inf> values of a supramaximal effort without any respiratory apparatus with a time-efficient analysis. Therefore, we recommended the use of a 60 seconds V̇O<inf>2</inf> curve analysis with a negative extrapolation for 3 seconds.

Sigmoidal VO2 on-kinetics: A new pattern in VO2 responses at the lower district of extreme exercise domain

The aim of the study was to analyse the VO₂ on-kinetics belonging to the work rates within the lower district of extreme exercise domain. Maximal O₂ utilisation and peak power outputs of eight well-trained cyclists were revealed by multisession trails. Critical threshold (CT) as the lower boundary of severe domain and aerobic limit power (ALP) as the upper boundary of severe domain were determined by multisession constant-load exercises. VO₂ on-kinetics over time were best fitted by multicomponent exponential models described by an initial concave-up response known as cardio-dynamic phase (τ = 18.2 ± 2.88 s; a = 1.56 ± 0.39 L·min^-1) before a primary concave-up phase (τ = 35.4 ± 12.4 s; a = 1.53 ± 0.36 L·min^-1), and then a slow component in two of the participants (τ = 80.8 ± 37 s; a = 0.47 ± 0.05 L·min^-1) or without a slow component in six of the participants during exercises performed at 50 W above the CT (R²≥0.96; SEE ≤ 0.24; p < 0.001). However, VO₂ on-kinetics over time belonging to exercises performed at 50 W above the ALP were best fitted by sigmoidal model (R²≥0.98; SEE ≤ 0.14; p < 0.001) in comparison with linear (R² = 0.37-0.66; SEE = 0.46-0.64; p < 0.01), or exponential functions (p> 0.05). Indeed, during those exercises, a short period of convex-up response (τ = 16.8 ± 3.1 s; a = 1.72 ± 0.39 L·min^-1) was determined just before a concave-up primary phase in VO₂ over time (τ = 24.6 ± 5.86 s; a = 1.31 ± 0.20 L·min^-1). It was shown that multicomponent exponential trend in VO₂ transformed into a sigmoidal shape, once the work rate exceeded the upper boundary of severe exercise domain.

Anaerobic capacity estimated by the sum of both oxygen equivalents from the glycolytic and phosphagen pathways is dependent on exercise mode: Running versus cycling

The purpose of this study was to verify whether the exercise modality (i.e., running and cycling) alters the magnitude of “anaerobic” capacity estimated by a single supramaximal effort (AC_{[La]+EPOCfast}). Fourteen healthy men (age: 26±9 years) underwent a maximum incremental test and a supramaximal effort to exhaustion at 115% of the intensity associated with maximal oxygen uptake to determine the AC_{[La]+EPOCfast} (i.e., the sum of both oxygen equivalents from the glycolytic and phosphagen pathways), performed on both a treadmill and cycle ergometer. The maximal oxygen uptake during running was higher (p = 0.001; large effect size) vs. cycling (48.9±3.9mL·kg^-1·min^-1 vs. 44.8±5.5mL·kg^-1·min^-1 respectively). Contrarily, the oxygen equivalent from the glycolytic metabolism was not different between exercise modalities (p = 0.133; small effect size; running = 2.35±0.48 L and cycling = 2.18±0.58 L). Furthermore, the “anaerobic” capacity was likely meaning fully (3.65±0.70 L) and very likely meaningfully (949.1±5.7 mL·kg^-1) greater in running than cycling (3.81±0.71 L and 52.0±8.1 mL·kg^-1). Additionally, the contribution of the phosphagen metabolism was higher (p = 0.001; large effect size) for running compared to cycling (1.6±0.3 L vs.1.3±0.3 L respectively). Therefore, the “anaerobic” capacity estimated by the sum of both oxygen equivalents from the glycolytic and phosphagen pathways during a supramaximal effort is influenced by exercise modality and is able to identify the difference in phosphagen metabolic contribution, based on the methodological conditions of this study.

Estimating peak oxygen uptake based on postexercise measurements in swimming

To assess the validity of postexercise measurements in estimating peak oxygen uptake (V̇O2peak) in swimming, we compared oxygen uptake (V̇O2) measurements during supramaximal exercise with various commonly adopted methods, including a recently developed heart rate - V̇O2 modelling procedure. Thirty-one elite swimmers performed a 200-m maximal swim where V̇O2 was measured breath-by-breath using a portable gas analyzer connected to a respiratory snorkel, 1 min before, during, and 3 min postexercise. V̇O2peak(-20-0) was the average of the last 20 s of effort. The following postexercise measures were compared: (i) first 20-s average (V̇O2peak(0-20)); (ii) linear backward extrapolation (BE) of the first 20 s (BE(20)), 30 s, and 3 × 20-, 4 × 20-, and 3 or 4 × 20-s averages; (iii) semilogarithmic BE at 20 s (LOG(20)) and at the other same time intervals as in linear BE; and (iv) predicted V̇O2peak using mathematical modelling (pV̇O2(0-20)]. Repeated-measures ANOVA and post-hoc Bonferroni tests compared V̇O2peak (criterion) and each estimated value. Pearson's coefficient of determination (r(2)) was used to assess correlation. Exercise V̇O2peak(-20-0) (mean ± SD 3531 ± 738 mL·min(-1)) was not different (p > 0.30) from pV̇O2(0-20) (3571 ± 735 mL·min(-1)), BE(20) (3617 ± 708 mL·min(-1)), or LOG(20) (3627 ± 746 mL·min(-1)). pV̇O2(0-20) was very strongly correlated with exercise V̇O2peak (r(2) = 0.962; p < 0.001), and showed a low standard error of the estimate (146 mL·min(-1), 4.1%) and the lowest mean difference (40 mL·min(-1); 1.1%). We confirm that the new modelling procedure based on postexercise V̇O2 and heart rate measurements is a valid and accurate procedure for estimating V̇O2peak in swimmers and avoids the estimation bias produced by other methods.