Application and performance of heart-rate-based methods to estimate oxygen consumption at different exercise intensities in postmenopausal women.

PURPOSE: Heart rate (HR) is a widespread method to estimate oxygen consumption ( V ˙ O2), exercise intensity, volume, and energy expenditure. Still, accuracy depends on lab tests or using indexes like HRnet and HRindex. This study addresses HR indexes' applicability in postmenopausal women (PMW), who constitute over 50% of the aging population and may have unique characteristics (e.g., heart size) affecting HR use. METHODS: Fourteen PMW underwent a cycling ramp incremental test to establish the relationships between V ˙ O2 (in MET) and absolute HR, HRnet, and HRindex. In a second group of ten PMW, population-specific and general equations were tested to predict MET and energy expenditure during six constant work exercises at various intensities. Pulmonary gas exchange and HR were continuously measured using a metabolic cart. Correlations, Bland-Altman analysis, and two-way RM-ANOVA were used to compare estimated and measured values. RESULTS: Strong linear relationships between the three HR indexes and MET were found in Group 1. In Group 2, population-specific equations showed medium-to-high correlations, precision, and no significant biases when estimating MET and energy expenditure. HRnet and HRindex outperformed absolute HR in accuracy. General HR equations had similar correlations but exhibited larger biases and imprecision. Statistical differences between measured and estimated values were observed at all intensities with general equations. CONCLUSION: This investigation confirms the suitability of HR for estimating aerobic metabolism in one of the most significant aging populations. However, it emphasizes the importance of considering individual variability and developing population-specific models when utilizing HR to infer metabolism.

The effect of acute heat exposure on the determination of exercise thresholds from ramp and step incremental exercise.

PURPOSE: The aim of this study was to examine how respiratory (RT) and lactate thresholds (LT) are affected by acute heat exposure in the two most commonly used incremental exercise test protocols (RAMP and STEP) for functional evaluation of aerobic fitness, exercise prescription and monitoring training intensities. METHODS: Eleven physically active male participants performed four incremental exercise tests, two RAMP (30 W·min-1) and two STEP (40 W·3 min-1), both in 18 °C (TEMP) and 36 °C (HOT) with 40% relative humidity to determine 2 RT and 16 LT, respectively. Distinction was made within LT, taking into account the individual lactate kinetics (LTIND) and fixed value lactate concentrations (LTFIX). RESULTS: A decrease in mean power output (PO) was observed in HOT at LT (-6.2 ± 1.9%), more specific LTIND (-5.4 ± 1.4%) and LTFIX (-7.5 ± 2.4%), compared to TEMP, however not at RT (-1.0 ± 2.7%). The individual PO difference in HOT compared to TEMP over all threshold methods ranged from -53 W to +26 W. Mean heart rate (HR) did not differ in LT, while it was increased at RT in HOT (+10 ± 8 bpm). CONCLUSION: This study showed that exercise thresholds were affected when ambient air temperature was increased. However, a considerable degree of variability in the sensitivity of the different threshold concepts to acute heat exposure was found and a large individual variation was noticed. Test design and procedures should be taken into account when interpreting exercise test outcomes.

Critical power, W' and W' reconstitution in women and men.

PURPOSE: The aim of this study was to compare critical power (CP) and work capacity W', and W' reconstitution (W'REC) following repeated maximal exercise between women and men. METHODS: Twelve women ([Formula: see text]O2PEAK: 2.53 ± 0.37 L·min-1) and 12 men ([Formula: see text]O2PEAK: 4.26 ± 0.30 L·min-1) performed a minimum of 3 constant workload tests, to determine CP and W', and 1 maximal exercise repetition test with three work bouts (WB) to failure, to quantify W'REC during 2 recovery periods, i.e., W'REC1 and W'REC2. An independent samples t test was used to compare CP and W' values between women and men, and a repeated-measures ANOVA was used to compare W'REC as fraction of W' expended during the first WB, absolute W'REC, and normalized to lean body mass (LBM). RESULTS: CP normalized to LBM was not different between women and men, respectively, 3.7 ± 0.5 vs. 4.1 ± 0.4 W·kgLBM-1, while W' normalized to LBM was lower in women 256 ± 29 vs. 305 ± 45 J·kgLBM-1. Fractional W'REC1 was higher in women than in men, respectively, 74.0 ± 12.0% vs. 56.8 ± 9.5%. Women reconstituted less W' than men in absolute terms (8.7 ± 1.2 vs. 10.9 ± 2.0 kJ) during W'REC1, while normalized to LBM no difference was observed between women and men (174 ± 23 vs. 167 ± 31 J·kgLBM-1). W'REC2 was lower than W'REC1 both in women and men. CONCLUSION: Sex differences in W'REC (absolute women < men; fractional women > men) are eliminated when LBM is accounted for. Prediction models of W'REC might benefit from including LBM as a biological variable in the equation. This study confirms the occurrence of a slowing of W'REC during repeated maximal exercise.

Easy Prediction of the Maximal Lactate Steady-State in Young and Older Men and Women.

Maximal Lactate steady-state (MLSS) demarcates sustainable from unsustainable exercise and is used for evaluation/monitoring of exercise capacity. Still, its determination is physically challenging and time-consuming. This investigation aimed at validating a simple, submaximal approach based on blood lactate accumulation ([Δlactate]) at the third minute of cycling in a large cohort of men and women of different ages. 68 healthy adults (40♂, 28♀, 43 ± 17 years (range 19-78), VO2max 45 ± 11 ml-1·kg-1·min-1 (25-68)) performed 3-5 constant power output (PO) trials with a target duration of 30 minutes to determine the PO corresponding to MLSS. During each trial, [Δlactate] was calculated as the difference between the third minute and baseline. A multiple linear regression was computed to estimate MLSS based on [Δlactate], subjects` gender, age and the trial PO. The estimated MLSS was compared to the measured value by paired t-test, correlation, and Bland-Altman analysis. The group mean value of estimated MLSS was 180 ± 51 W, not significantly different from (p = 0.98) and highly correlated with (R2 = 0.89) measured MLSS (180 ± 54 watts). The bias between values was 0.17 watts, and imprecision 18.2 watts. This simple, submaximal, time- and cost-efficient test accurately and precisely predicts MLSS across different samples of healthy individuals (adjusted R2 = 0.88) and offers a practical and valid alternative to the traditional MLSS determination.

Performance and Anthropometrics of Classic Powerlifters: Which Characteristics Matter?

ABSTRACT: Ferrari, L, Colosio, AL, Teso, M, and Pogliaghi, S. Performance and anthropometrics of classic powerlifters: Which characteristics matter? J Strength Cond Res 36(4): 1003-1010, 2022-The purpose of this study is: (a) provide normative performance and anthropometric data of Southern European classic powerlifters of both sexes; (b) determine the possible relationships between these variables and performance; and (c) develop population-specific predictive equations for single lifts and overall powerlifting performance. During an unofficial national-level competition, we recruited 74 athletes (51 men and 23 women) and recorded their individual, anthropometric, and performance characteristics and divided them into sex and 2 performance categories based on their Wilks points. Weaker (<370 Wilks points) and stronger (>370 Wilks points) athletes of both sexes were compared by two-way analysis of variance. Simple correlation and multiple linear regression between individual/anthropometric characteristics and performance were modeled. We applied a step-forward multiple linear regression model to predict single lifts and overall performance. All parameters significantly differed between sexes (p < 0.05 for all comparisons). Stronger male athletes had a significantly larger neck (42 ± 2.8 cm; effect size [ES] = 0.59), and flexed (40.6 ± 3.3 cm; ES = 1.18) and relaxed upper-arm (37.5 ± 3.1 cm; ES = 1.34) and thigh girths (63.6 ± 7.0 cm; ES = 0.77) compared to weaker male athletes. Furthermore, stronger women had significantly larger flexed (32.6 ± 3.3 cm; ES = 0.88) and relaxed upper-arm (33 ± 1.5 cm; ES = 2.28) and chest girths (99.3 ± 9.2 cm; ES = 1.10) compared to weaker female athletes. A combination of experience, fat mass, and upper-limb and lower-limb muscle mass indexes can accurately and precisely predict overall and individual lift performance (r2 ≥ 0.83 for all the predictions). This is the first study to provide normative performance and anthropometric data in Southern European male and female powerlifters.

Metabolic instability vs fibre recruitment contribution to the [Formula: see text] slow component in different exercise intensity domains.

This study focused on the steady-state phase of exercise to evaluate the relative contribution of metabolic instability (measured with NIRS and haematochemical markers) and muscle activation (measured with EMG) to the oxygen consumption ([Formula: see text]) slow component ([Formula: see text]) in different intensity domains. We hypothesized that (i) after the transient phase, [Formula: see text], metabolic instability and muscle activation tend to increase differently over time depending on the relative exercise intensity and (ii) the increase in [Formula: see text] is explained by a combination of metabolic instability and muscle activation. Eight active men performed a constant work rate trial of 9 min in the moderate, heavy and severe intensity domains. [Formula: see text], root mean square by EMG (RMS), deoxyhaemoglobin by NIRS ([HHb]) and haematic markers of metabolic stability (i.e. [La-], pH, HCO3-) were measured. The physiological responses in different intensity domains were compared by two-way RM-ANOVA. The relationships between the increases of [HHb] and RMS with [Formula: see text] after the third min were compared by simple and multiple linear regressions. We found domain-dependent dynamics over time of [Formula: see text], [HHb], RMS and the haematic markers of metabolic instability. After the transient phase, the rises in [HHb] and RMS showed medium-high correlations with the rise in [Formula: see text] ([HHb] r = 0.68, p < 0.001; RMS r = 0.59, p = 0.002). Moreover, the multiple linear regression showed that both metabolic instability and muscle activation concurred to the [Formula: see text] (r = 0.75, [HHb] p = 0.005, RMS p = 0.042) with metabolic instability possibly having about threefold the relative weight compared to recruitment. Seventy-five percent of the dynamics of the [Formula: see text] was explained by [HHb] and RMS.

Bioenergetics of the VO2 slow component between exercise intensity domains.

During heavy and severe constant-load exercise, VO2 displays a slow component (VO2sc) typically interpreted as a loss of efficiency of locomotion. In the ongoing debate on the underpinnings of the VO2sc, recent studies suggested that VO2sc could be attributed to a prolonged shift in energetic sources rather than loss of efficiency. We tested the hypothesis that the total cost of cycling, accounting for aerobic and anaerobic energy sources, is affected by time during metabolic transitions in different intensity domains. Eight active men performed 3 constant load trials of 3, 6, and 9 min in the moderate, heavy, and severe domains (i.e., respectively below, between, and above the two ventilatory thresholds). VO2, VO2 of ventilation and lactate accumulation ([La-]) were quantified to calculate the adjusted oxygen cost of exercise (AdjO2Eq, i.e., measured VO2 - VO2 of ventilation + VO2 equivalent of [La-]) for the 0-3, 3-6, and 6-9 time segments at each intensity, and compared by a two-way RM-ANOVA (time × intensity). After the transient phase, AdjO2Eq was unaffected by time in moderate (ml*3 min-1 at 0-3, 0-6, 0-9 min: 2126 ± 939 < 2687 ± 1036, 2731 ± 1035) and heavy (4278 ± 1074 < 5121 ± 1268, 5225 ± 1123) while a significant effect of time was detected in the severe only (5863 ± 1413 < 7061 ± 1516 < 7372 ± 1443). The emergence of the VO2sc was explained by a prolonged shift between aerobic and anaerobic energy sources in heavy (VO2 - VO2 of ventilation: ml*3 min-1 at 0-3, 0-6, 0-9 min: 3769 ± 1128 < 4938 ± 1256, 5091 ± 1123, [La-]: 452 ± 254 < 128 ± 169, 79 ± 135), while a prolonged metabolic shift and a true loss of efficiency explained the emergence of the VO2sc in severe.

Quantification of energy expenditure of military loaded runs: what is the performance of laboratory-based equations when applied to the field environment?

INTRODUCTION: Performance during army loaded runs provides a synthetic indicator of a soldier's capacity to move while carrying loads and thereby remain able to execute a mission. The aim of this study was to estimate and compare the energy expenditure (EE) of army loaded runs, conducted in a field environment using laboratory-based equations and HR index (HRindex). METHODS: 45 Ranger recruits had HR monitored during three loaded runs (10, 15 and 20 km) in full military equipment in the field environment. EE was calculated using reference equations (EE-Eq) and estimates of oxygen consumption based on HRindex (EE-HRindex). Correspondence between EE-Eq and EE-HRindex estimates was evaluated using a two-way analysis of variance, correlation test and Bland-Altman analysis. RESULTS: EE-Eq relative to time and weight was significantly higher for the 10 km (0.175±0.016) compared with 15 and 20 km (0.163±0.016 and 0.160±0.013 kcal/kg/min, not different). The overall EE-Eq increased significantly with distance (1129±59, 1703±80 and 2250±115 kcal for 10, 15 and 20 km). EE-Eq was not different from and highly correlated with EE-HRindex, with a small and non-significant bias and good precision between methods. CONCLUSIONS: Our study provides the first comprehensive data on HR and EE during long-distance loaded army runs, in full combat equipment, in actual field conditions. Equation-based estimates of EE during these heavy-intensity activities were not significantly different from and highly correlated with HR-based estimates. This corroborates the general applicability of the predictive equations in the field environment. Furthermore, our study suggests that time-resolved HR-based estimates of EE during army runs can be used to evaluate for the effects of context specificity, individual variability and fatigue in movement economy.

Heart Rate-Index Estimates Oxygen Uptake, Energy Expenditure and Aerobic Fitness in Rugby Players.

The purpose of the study was to verify the suitability of heart rate-index (HRindex) in predicting submaximal oxygen consumption (VO2), energy expenditure (EE) and maximal oxygen consumption (VO2max) during treadmill running in rugby players. Fifteen professional rugby players (99.8 ± 12.7 kg, 1.85 ± 0.09 m) performed a running incremental test while VO2 (breath-by-breath) and heart rate (HR) were measured. HRindex was calculated (actual HR/resting HR) to predict submaximal and maximal VO2 ({[(HRindex x 6)-5.0] x (3.5 body weight)}) and EE. Measured and predicted VO2 and EE were compared by two-way RM-ANOVA (method, speed), correlation and Bland-Altman analysis. Measured and predicted VO2max were compared by paired t-test, correlation and Bland-Altman analysis. Submaximal VO2 and EE significantly increased (baseline VO2: 8.1 ± 1.6 ml·kg-1·min-1VO2max: 46.8 ± 4.3 ml·kg-1·min-1, baseline EE: 0.03 ± 0.01 kcal·kg-1·min-1, peak EE: 0.23 ± 0.03 kcal·kg-1·min-1) as a function of speed (p < 0.001 and p < 0.001 for VO2 and EE respectively) yet measured and predicted values at equal treadmill speeds were not significantly different (p = 0.17; p = 0.16) and highly correlated (r = 0.95; r = 0.94). The Bland-Altman analysis confirmed a non-significant bias between measured and estimated VO2 (measured: 40.3 ± 10.7, estimated: 40.7 ± 10.1 ml·kg-1·min-1, bias = 1.35 ml·kg-1·min-1, z = 1.12, precision = 3.39 ml·kg-1·min-1) and EE (measured: 20.0 ± 0.05 kcal·kg-1·min-1, estimated: 20.0 ± 0.05 kcal·kg-1·min-1, bias = 0.00 kcal·kg-1·min-1, z = 0.04, precision = 0.02 kcal·kg-1·min-1). Estimated and predicted VO2max were not statistically different (p = 0.91), highly correlated (r = 0.96), and showed a non-significant bias (bias = 0.17, z = 0.22, precision = 1.29 ml·kg-1·min-1). HRindex is a valid field method to track VO2, EE and VO2max during running in rugby players.

Identification of critical intensity from a single lactate measure during a 3-min, submaximal cycle-ergometer test.

We tested the hypothesis that critical intensity in cycling can be determined from a single delta blood lactate in the third minute of a submaximal cycle ergometer trial. Fourteen healthy young men performed four to six constant-power-output trials on a cycle ergometer to the limit of tolerance. Critical intensity was calculated via a linear model and subsequently validated. Lactate was measured at baseline and at 3 min from exercise onset. Delta lactate was the difference between these measures. Based on individual trials, we obtained the delta lactate-% validated critical intensity relationship and thereafter an estimate of critical intensity was computed. Validated and estimated critical intensity were compared by effects sizes, paired-sample t-test and Bland-Altman analysis. Delta lactate was a linear function of the intensity of exercise, expressed as % validated critical intensity (R2 = 0.89). Estimated critical intensity was not different from (d = 0.03, P = 0.98) and highly correlated with (R2 = 0.88) validated critical intensity. The bias between measures was 0.03 W (≠0) with a precision of 7 W. The results suggest that critical intensity in cycling can be accurately and precisely determined from delta lactate during a sub-maximal trial and so provides a practical and valid alternative to direct determination.

Characterizing the Exponential Profile of W' Recovery Following Partial Depletion.

PURPOSE: The aim of this study was to characterize W' recovery kinetics in response to a partial W' depletion. We hypothesized that W' recovery following partial depletion would be better described by a biexponential than by a monoexponential model. METHODS: Nine healthy men performed a ramp incremental exercise test, three to five constant load trials to determine critical power and W', and ten experimental trials to quantify W' depletion. Each experimental trial consisted of two constant load work bouts (WB1 + WB2) interspersed by a recovery interval. WB1 was designed to evoke a 25% or 75% W' depletion (DEP 25% + DEP 75% ). Subsequently, participants recovered for 30, 60, 120, 300 or 600 s, and then performed WB2 to exhaustion in order to calculate the observed W' recovery (W' OBS ). W' OBS data were fitted using monoexponential and biexponential models, both with a variable and a fixed model amplitude. Root mean square error (RMSE) and Akaike information criterion (AIC c ) were calculated to evaluate the models' goodness-of-fit. RESULTS: The biexponential model fits were associated with overall lower RMSE values (0.4-5.0%) compared to the monoexponential models (2.9-8.0%). However, ΔAIC c resulted in negative values (-15.5 and -23.3) for the model fits where the amplitude was free, thereby favoring the use of a monoexponential model for both depletion conditions. For the model fits where the amplitude was fixed at 100%, ΔAIC c was negative for DEP 25% (-15.0), but positive for DEP 75% (11.2). W' OBS values were strongly correlated between both depletion conditions ( r = 0.92), and positively associated with V̇O 2peak , CP and GET ( r = 0.67-0.77). CONCLUSIONS: The present study results did not provide evidence in favor of a biexponential modeling technique to characterize W' recovery following partial depletion. Moreover, we demonstrated that fixed t values were insufficient to model W' recovery across different depletion levels, and that W' recovery was positively associated with aerobic fitness. These findings underline the importance of employing variable and individualized t values in future predictive W' models.

Effect of acute heat exposure on the determination of critical power and W' in women and men.

The goal of this study was to investigate to what extent acute heat exposure would affect the parameters of the power-duration relationship, i.e. CP and W', using multiple constant workload tests to task failure, in women and men. Twenty four young physically active participants (12 men, 12 women) performed 3-5 constant load tests to determine CP and W', both in temperate (TEMP; 18°C) and hot (HOT; 36°C) environmental conditions. A repeated-measures ANOVA was executed to find differences between TEMP and HOT, and between women and men. In HOT, CP was reduced by 6.5% (227 ± 50 vs. 212 ± 47 W), while W' increased 12.4% (16.4 ± 4.4 vs. 18.5 ± 5.6 kJ). No significant two-way sex × temperature interactions were observed, indicating that the environmental conditions did not have a different effect in men compared with women. The intersection of the average curvatures in TEMP and HOT occurred at 137 s and 280 W in women, and 153 s and 397 W in men. Acute heat exposure had an impact on the parameters CP and W', i.e. CP decreased whereas W' increased. The increase in W' might be a consequence of the mathematical modelling for the used test methodology, rather than a physiological accurate value of W' in HOT. No differences induced by heat exposure were observed between women and men.

The determination of CP and W' was done using multiple constant workload tests to task failure and acute heat exposure induced changes in CP (decrease) and W' (increase).The increase in W' with acute heat exposure might be a consequence of the mathematical modelling for the used test methodology, rather than a physiological accurate value of W'.Acute heat exposure had a similar effect on performance parameters in women and men.

An Intensity-dependent Slow Component of HR Interferes with Accurate Exercise Implementation in Postmenopausal Women.

PURPOSE: We tested the hypothesis that a slow component of HR (i.e., scHR) occurs in all intensity domains, greater than the slow component of oxygen uptake (scV˙O2), and we developed an equation to predict it across exercise intensities. METHOD: Eighteen healthy, postmenopausal women (54 ± 4 yr) performed on a cycle ergometer: i) a ramp incremental test for thresholds and V˙O2max detection; ii) 30-min constant work exercise at 40%, 50%, 60%, 70%, and 80% V˙O2max for the measurement of scHR, scV˙O2, stroke volume, and body temperature (T°). scHR and scV˙O2 were compared by two-way repeated-measures ANOVA (intensity and variable). Pearson correlation was calculated between the slow component of all variables, relative intensity, and domain. scHR (in beats per minute) was predicted with a linear model based on exercise intensity relative to the respiratory compensation point (RCP). RESULTS: A positive scHR was present in all domains, twice the size of scV̇O2 (P < 0.001), and significantly correlated with the slow components of V̇O2 (r2 = 0.46), T° (r2 = 0.52), and relative intensity (r2 = 0.66). A linear equation accurately predicts scHR based on %RCP (r2 = 0.66, SEE = 0.15). CONCLUSIONS: A mismatch exists between the slow components of HR and metabolic intensity. Whenever exercise is prescribed based on HR, target values should be adjusted over time to grant that the desired metabolic stimulus is maintained throughout the exercise session.

Physical Preparation of a World-Class Lightweight Men's Double Sculls Team for the Tokyo 2020 Olympics.

PURPOSE: To analyze the physical profile and training program of a world-class lightweight double sculls rowing crew toward the Tokyo 2020 Olympics. METHOD: A case study in which both rowers performed physical testing in November 2020 and April 2021 (anthropometrics, incremental rowing test, and power profiling). The training program (38 wk) in the buildup to the Olympics was analyzed, providing insight into training characteristics (volume; contribution of rowing, alternative, and strength training; prescribed and recorded [heart rate] training-intensity distribution). The entire period was split into 3 phases: preparation period (8 wk), competition period 1 (11 wk), and competition period 2 (9 wk), and training characteristics were compared. RESULTS: In the April 2021 testing, rower A (1.89 m, 74.6 kg, 4.4% body fat) had a peak oxygen uptake of 5.8 L·min-1 (77.8 mL·min-1·kg-1) and a peak power output of 491 W. Rower B (1.82 m, 70.6 kg, 7.8% body fat) had a peak oxygen uptake of 5.5 L·min-1 (77.9 mL·min-1·kg-1) and a peak power output of 482 W. The mean weekly training volume was 14 hours 47 minutes (4 h 5 min), of which 58.5% (14.6%) consisted of rowing, 13.4% (6.8%) strength training, and 28.1% (2.6%) alternative training. Heart-rate training-intensity distribution was 77.8% (4.2%) in zone 1, 16.6% (3.7%) in zone 2, and 5.6% (2.8%) in zone 3 with a lower contribution of zone 1 in competition period 1 (P = .029) and competition period 2 (P = .023) compared with the preparation period, and a higher contribution of zone 3 in competition period 1 (P = .018) and competition period 2 (P = .011) compared with the preparation period. CONCLUSION: The crew combined a high volume of rowing, alternative, and strength training in a pyramidal heart-rate training-intensity distribution throughout the year.

Modeling V̇o2 on-kinetics based on intensity-dependent delayed adjustment and loss of efficiency (DALE).

This study presents and evaluates a new mathematical model of V̇o2 on-kinetics, with the following properties: 1) a progressively slower primary phase following the size-principle of motor unit recruitment, explaining the delayed V̇o2 steady state seen in the heavy exercise intensity domain, and 2) a severe-domain slow component modeled as a time-dependent decrease in efficiency. Breath-by-breath V̇o2 measurements from eight subjects performing step cycling transitions, in the moderate, heavy, and severe exercise domains, were fitted to the conventional three-phase model and the new model. Model performance was evaluated with a residual analysis and by comparing Bayesian (BIC) and corrected Akaike (AICc) information criteria. The residual analysis showed no systematic deviations, except perhaps for the initial part of the primary phase. BIC favored the new model, being 9.3 (SD 7.1) lower than the conventional model whereas AICc was similar between models. Compared with the conventional three-phase model, the proposed model distinguishes between the kinetic adaptations in the heavy and severe domains by predicting a delayed steady-state V̇o2 in the heavy and no steady-state V̇o2 in the severe domain. This allows to determine when stable oxygen costs of exercise are attainable and it also represents a first step in defining time-dependent oxygen costs when stable energy conversion efficiency is not attainable.NEW & NOTEWORTHY We propose and assess a new minimalistic integrated model for the V̇o2 on-kinetics, inspired by the currently available best evidence of the underlying mechanisms. We show that the model provides a similar fit as the conventionally used three-phase model, even though a stricter data fitting method is used for the proposed model. The proposed model clarifies misconceptions related to the V̇o2 slow component's behavior, by clearly predicting that steady-state V̇o2 is attainable in the moderate and heavy exercise intensity domains. Furthermore, the model opens new possibilities for assessing oxygen cost during severe intensity exercise without the fallible assumption of time-constant energy-conversion efficiency.

Repeated Passive Mobilization to Stimulate Vascular Function in Individuals of Advanced Age Who Are Chronically Bedridden: A Randomized Controlled Trial.

BACKGROUND: Vascular dysfunction and associated disorders are major side effects of chronic bed rest, yet passive mobilization as a potential treatment has only been theorized so far. This study investigated the effects of passive mobilization treatment on vascular function in older, chronically bedridden people. METHOD: The study sample was 45 chronically bedridden people of advanced age (mean age: 87 years; 56% female; mean bed rest: 4 years) randomly assigned to a treatment (n = 23) or a control group (CTRL, n = 22). The treatment group received passive mobilization twice daily (30 minutes, 5 times/wk) for 4 weeks. A kinesiologist performed passive mobilization by passive knee flexion/extension at 1 Hz in one leg (treated leg [T-leg] vs control leg [Ctrl-leg]). The CTRL group received routine treatment. The primary outcome was changes in peak blood flow (∆peak) as measured with the single passive leg movement test at the common femoral artery. RESULTS: ∆Peak was increased in both legs in the Treatment group (+90.9 mL/min, p < .001, in T-leg and +25.7 mL/min, p = .039 in Ctrl-leg). No difference in peak blood flow after routine treatment was found in the CTRL group. CONCLUSION: Improvement in vascular function after 4 weeks of passive mobilization was recorded in the treatment group. Passive mobilization may be advantageously included in standard clinical practice as an effective strategy to treat vascular dysfunction in persons with severely limited mobility.

Prolonged static stretching causes acute, nonmetabolic fatigue and impairs exercise tolerance during severe-intensity cycling.

We tested the hypothesis that static stretching, an acute, nonmetabolic fatiguing intervention, reduces exercise tolerance by increasing muscle activation and affecting muscle bioenergetics during cycling in the "severe" intensity domain. Ten active men (age, 24 ± 2 years; body mass, 74 ± 11 kg; height, 176 ± 8 cm) participated in identical constant-load cycling tests of equal intensity, of which 2 tests were carried out under control conditions and 2 were done after stretching. This resulted in a 5% reduction of maximal isokinetic sprinting power output. We measured (i) oxygen consumption, (ii) electromyography, (iii) deoxyhemoglobin, (iv) blood lactate concentration; (v) time to exhaustion, and (vi) perception of effort. Finally, oxygen consumption and deoxyhemoglobin kinetics were determined. Force reduction following stretching was accompanied by augmented muscle excitation at a given workload (p = 0.025) and a significant reduction in time to exhaustion (p = 0.002). The time to peak oxygen consumption was reduced by stretching (p = 0.034), suggesting an influence of the increased muscle excitation on the oxygen consumption kinetics. Moreover, stretching was associated with a mismatch between O2 delivery and utilization during the isokinetic exercise, increased perception of effort, and blood lactate concentration; these observations are all consistent with an increased contribution of the glycolytic energy system to sustain the same absolute intensity. These results suggest a link between exercise intolerance and the decreased ability to produce force. Novelty We provided the first characterization of the effects of prolonged stretching on the metabolic response during severe cycling. Stretching reduced maximal force and augmented muscle activation, which in turn increased the metabolic response to sustain exercise.

Heart rate-index estimates aerobic metabolism in professional soccer players.

OBJECTIVES: This study aimed at proposing a new heart rate (HR) method to track aerobic metabolism in soccer by: (i) validating a recently developed HR index (HRindex) in professional soccer players, (ii) comparing HRindex vs the most common HR parameters and (iii) testing the agreement between measured and estimated VO2 values using HRindex. DESIGN: cross-sectional. METHODS: 184 professional soccer players performed a step incremental running test on a treadmill while VO2 and HR were recorded. HRindex was calculated (actual HR/resting HR) and its relationship with VO2 was compared with the relationships with the metabolism of actual HR, net HR, and % of HR reserve. Finally, HRindex was used to predict VO2=((HRindex·6)-5)·3.5) and measured and estimated VO2 were compared by 2W RM-ANOVA and Bland-Altman analysis. RESULTS: HRindex/VO2 relationship explained 85% of the variability in data, showing a higher performance than actual HR (77%) and similar values to the other parameters. Measured and estimated VO2 were not significantly different ≤14kmh-1, whereas at speeds ≥14kmh-1 measured VO2 was higher than estimated VO2. Finally, measured and estimated VO2 were highly correlated (R2=0.85, p=0.000), and showed no significant bias (bias=-1.03, z=-0.69, precision=3.75mlkgmin-1). CONCLUSIONS: We validated the HRindex/VO2 relationship in professional soccer players. HRindex showed better agreement with metabolism than actual HR and similar agreement to the other HR parameters. HRindex allowed to estimate VO2, but at very high-intensity HRindex underestimated VO2. Future studies should test this in real game conditions. HRindex could offer a time-efficient and easy-to-use "field" method to monitor aerobic metabolism in soccer.