Coagulation activity and thrombotic risk following high-volume endurance exercise in recreationally active cyclists

Despite the prognostic effect of physical activity, acute bouts of high-volume endurance exercise can induce cardiac stress and post-exercise hypercoagulation associated with increased thrombotic risk. The aim of this study was to explore the effect of high-volume endurance exercise on coagulation and thrombotic activity in recreational cyclists. Thirty-four recreational cyclists completed 4.8 ± 0.3 hours cycling at 45 ± 5% of maximal power output on a bicycle ergometer. Intravenous blood samples were collected pre-exercise, immediately post-exercise, 24 and 48 hours post-exercise and analysed for brain natriuretic peptide (BNP), cardiac troponin (cTn), C-reactive protein (CRP), D-dimer, thrombin-antithrombin (TAT) complex, tissue factor (TF), tissue factor pathway inhibitor (TFPI) and TF to TFPI ratio (TF:TFPI). An increase in cTn was observed post-exercise (p < 0.001). CRP concentrations were increased at 24 and 48 hours post-exercise compared to pre-exercise concentrations (p ≤ 0.001). TF was elevated at 24 hours post-exercise (p < 0.031) and TFPI was higher immediately post-exercise (p < 0.044) compared to all other time points. TF:TFPI was increased at 24 and 48 hours post-exercise compared to pre-exercise (p < 0.025). TAT complex was reduced at 48 hours post-exercise compared to pre-exercise (p = 0.015), D-dimer was higher immediately post-exercise compared to all other time points (p ≤ 0.013). No significant differences were observed in BNP (p > 0.05). High-volume endurance cycling induced markers of cardiac stress among recreational cyclists. However, plasma coagulation and fibrinolytic activity suggests no increase in thrombotic risk after high-volume endurance exercise.

Effects of an intermittent exercise protocol on ankle control during a single-legged landing

Purpose

To identify the effects of fatigue from an exercise protocol (similar to a soccer match) on ankle motion and forces during single-legged drop landing.

Methods

Seventeen males aged (mean ± SD) 22.2 ± 2.0 years participated in this repeated measures study. A 90-min intermittent exercise protocol with a 15-min rest at halftime was performed. Before, at halftime and after the exercise, participants were tested via a single-legged drop landing task onto a force platform whilst wearing a three-dimensional inertial measurement system (Xsens). Ankle angles (plantarflexion/dorsiflexion and inversion/eversion) were analysed before landing and at peak ground reaction force after landing, and center of pressure was analysed at peak ground reaction force.

Results

No significant differences were found for the outcomes between pre-, halftime and post-exercise (p > 0.05).

Conclusions

Findings suggest that exercises simulating a soccer match (regarding exertion) do not necessarily lead to significant changes in ankle motion or forces around the ankle.

Residual neuromuscular fatigue influences subsequent on-court activity in basketball

AbstractThe aim of this study was to determine if residual neuromuscular fatigue influenced subsequent match and training activity in professional women's basketball. Prior to matches and training sessions throughout a season, players performed countermovement jumps while wearing a magnetic, angular rate and gravity (acceleration) sensor on their upper back. Flight time to contraction time ratio was used to determine neuromuscular performance and to identify neuromuscular fatigue. Average session intensity and volume, proportion of live time spent in different intensity bands (matches), and absolute and relative time spent in different intensity bands (training) were quantified using accelerometry. Residual neuromuscular fatigue was deemed to be present when the decrement in neuromuscular performance relative to pre-season baseline was greater than the smallest worthwhile change. Players displayed residual neuromuscular fatigue before 16% of matches and 33% of training sessions. When players were fatigued prior to matches, the proportion of live time undertaking supramaximal activity was 5.7% less (p = 0.02) and moderate-vigorous activity was 3.7% more than when not fatigued (p = 0.02). When fatigued prior to training, the players displayed a 2.6% decrement in average intensity (p = 0.02), 2.8% decrement in absolute (p = 0.01) and 5.0% decrement in relative (p = 0.01) maximal activity, as well as 13.3% decrement in absolute (p < 0.01) and 6.8% decrement in relative (p < 0.01) supramaximal activity when compared to not being fatigued. These findings suggest that residual neuromuscular fatigue influences players' ability to perform supramaximal activity, which highlights the importance of monitoring neuromuscular performance throughout a professional season.

Sympathovagal Balance Is a Strong Predictor of Post High-Volume Endurance Exercise Cardiac Arrhythmia

Regular physical activity is important for cardiovascular health. However, high-volume endurance exercise has been associated with increased number of electrocardiogram (ECG) abnormalities, including disturbances in cardiac rhythm (arrhythmias) and abnormalities in ECG pattern. The aim of this study was to assess if heart rate variability (HRV) is associated with ECG abnormalities. Fifteen participants with previous cycling experience completed a 21-day high-volume endurance exercise cycle over 3,515 km. Participants wore a 5-lead Holter monitor for 24 h pre- and post-exercise, which was used to quantify ECG abnormalities and export sinus R-to-R intervals (NN) used to calculate HRV characteristics. As noise is prevalent in 24-h HRV recordings, both 24-h and heart rate collected during stable periods of time (i.e., deep sleep) were examined. Participants experienced significantly more arrhythmias post high-volume endurance exercise (median = 35) compared to pre (median = 12; p = 0.041). All 24-h and deep sleep HRV outcomes were not different pre-to-post high-volume endurance exercise (p &gt; 0.05). Strong and significant associations with arrhythmia number post-exercise were found for total arrhythmia (total arrhythmia number pre-exercise, ρ = 0.79; age, ρ = 0.73), supraventricular arrhythmia (supraventricular arrhythmia number pre-exercise: ρ = 0.74; age: ρ = 0.66), and ventricular arrhythmia (age: ρ = 0.54). As a result, age and arrhythmia number pre-exercise were controlled for in hierarchical regression, which revealed that only deep sleep derived low frequency to high frequency (LF/HF) ratio post high-volume endurance exercise predicted post total arrhythmia number (B = 0.63, R2Δ = 34%, p = 0.013) and supraventricular arrhythmia number (B = 0.77, R2Δ = 69%, p &lt; 0.001). In this study of recreationally active people, only deep sleep derived LF/HF ratio was associated with more total and supraventricular arrhythmias after high-volume endurance exercise. This finding suggests that measurement of sympathovagal balance during deep sleep might be useful to monitor arrhythmia risk after prolonged high-volume endurance exercise performance.

The influence of considering individual resistance training variables as a whole on muscle strength: A systematic review and meta-analysis protocol

Examinations of the effect of resistance training (RT) on muscle strength have attempted to determine differences between prescriptions, mostly examining individual training variables. The broad interaction of variables does not appear to be completely considered, nor has a dose-response function been determined. This registered (doi.org/10.17605/OSF.IO/EH94V) systematic review with meta-analysis aims to determine if the interaction of individual training variables to derive RT dose, dosing, and dosage can influence muscle strength and determine if an optimal prescription range exists for developing muscle strength. To derive RT dose, the following calculation will be implemented: number of sets × number of repetitions × number of exercises × exercise intensity, while RT dosing factors in frequency and RT dosage considers program duration. A keyword search strategy utilising interchangeable terms for population (adult), intervention (resistance training), and outcomes (strength) will be conducted across three databases (CINAHL, MEDLINE, and SPORTDiscus). Novel to the field of exercise prescription, an analytical approach to determine the dose-response function for continuous outcomes will be used. The pooled standardised mean differences for muscle strength will be estimated using DerSimonian and Laird random effects method. Linear and non-linear dose-response relationships will be estimated by fitting fixed effects and random effects models using the one-stage approach to evaluate if there is a relationship between exercise dose, dosing and dosage and the effect on muscle strength. Maximised log-likelihood and the Akaike Information Criteria will be used to compare alternative best fitting models. Meta regressions will investigate between-study variances and a funnel plot and Egger's test will assess publication bias. The results from this study will identify if an optimal prescription range for dose, dosing and dosage exists to develop muscle strength.

Misuse of the term 'load' in sport and exercise science

Despite the International System of Units (SI), as well as several publications guiding researchers on correct use of terminology, there continues to be widespread misuse of mechanical terms such as 'work' in sport and exercise science. A growing concern is the misuse of the term 'load'. Terms such as 'training load' and 'PlayerLoad' are popular in sport and exercise science vernacular. However, a 'load' is a mechanical variable which, when used appropriately, describes a force and therefore should be accompanied with the SI-derived unit of the newton (N). It is tempting to accept popular terms and nomenclature as scientific. However, scientists are obliged to abide by the SI and must pay close attention to scientific constructs. This communication presents a critical reflection on the use of the term 'load' in sport and exercise science. We present ways in which the use of this term breaches principles of science and provide practical solutions for ongoing use in research and practice.

Criterion Validity of a MARG Sensor to Assess Countermovement Jump Performance in Elite Basketballers

ABSTRACT

Staunton, CA, Stanger, JJ, Wundersitz, DW, Gordon, BA, Custovic, E, and Kingsley, MI. Criterion validity of a MARG sensor to assess countermovement jump performance in elite basketballers. J Strength Cond Res 35(3): 797-803, 2021-This study assessed the criterion validity of a magnetic, angular rate, and gravity (MARG) sensor to measure countermovement jump (CMJ) performance metrics, including CMJ kinetics before take-off, in elite basketballers. Fifty-four basketballers performed 2 CMJs on a force platform with data simultaneously recorded by a MARG sensor located centrally on the player's back. Vertical accelerations recorded from the MARG sensor were expressed relative to the direction of gravity. Jumps were analyzed by a blinded assessor and the best jump according to the force platform was used for comparison. Pearson correlation coefficients (r) and mean bias with 95% ratio limits of agreement (95% RLOA) were calculated between the MARG sensor and the force platform for jumps performed with correct technique (n = 44). The mean bias for all CMJ metrics was less than 3%. Ninety-five percent RLOA between MARG- and force platform-derived flight time and jump height were 1 ± 7% and 1 ± 15%, respectively. For CMJ performance metrics before takeoff, impulse displayed less random error (95% RLOA: 1 ± 13%) when compared with mean concentric power and time to maximum force displayed (95% RLOA: 0 ± 29% and 1 ± 34%, respectively). Correlations between MARG and force platform were significant for all CMJ metrics and ranged from large for jump height (r = 0.65) to nearly perfect for mean concentric power (r = 0.95). Strong relationships, low mean bias, and low random error between MARG and force platform suggest that MARG sensors can provide a practical and inexpensive tool to measure impulse and flight time-derived CMJ performance metrics.

Impact of endurance exercise on the heart of cyclists: A systematic review and meta-analysis

OBJECTIVE

To compare heart structure and function in endurance athletes relative to participants of other sports and non-athletic controls in units relative to body size. A secondary objective was to assess the association between endurance cycling and cardiac abnormalities.

PATIENTS AND METHODS

Five electronic databases (CINAHL, Cochrane Library, Medline, Scopus, and SPORTdiscus) were searched from the earliest record to 14 December 2019 to identify studies investigating cardiovascular structure and function in cyclists. Of the 4865 unique articles identified, 70 met inclusion criteria and of these, 22 articles presented 10 cardiovascular parameters in units relative to body size for meta-analysis and five presented data relating to incidence of cardiac abnormalities. Qualitative analysis was performed on remaining data. The overall quality of evidence was assessed using GRADE. Odds ratios were calculated to compare the incidence of cardiac abnormality.

RESULTS

Heart structure was significantly larger in cyclists compared to non-athletic controls for left ventricular: mass; end-diastolic volume, interventricular septal diameter and internal diameter; posterior wall thickness, and end-systolic internal diameter. Compared to high static and high dynamic sports (e.g., kayaking and canoeing), low-to-moderate static and moderate-to-high dynamic sports (e.g., running and swimming) and moderate-to-high static and low-to-moderate dynamic sports (e.g., bodybuilding and wrestling), endurance cyclists end-diastolic left ventricular internal diameter was consistently larger (mean difference 1.2-3.2 mm/m²). Cardiac abnormalities were higher in cyclists compared to controls (odds ratio: 1.5, 95%CI 1.2-1.8), but the types of cardiac abnormalities in cyclists were not different to other athletes.

CONCLUSION

Endurance cycling is associated with a larger heart relative to body size and an increased incidence of cardiac abnormalities relative to controls.

Validity of a Wearable Accelerometer Device to Measure Average Acceleration Values During High-Speed Running

Alexander, JP, Hopkinson, TL, Wundersitz, DWT, Serpell, BG, Mara, JK, and Ball, NB. Validity of a wearable accelerometer device to measure average acceleration values during high-speed running. J Strength Cond Res 30(11): 3007-3013, 2016-The aim of this study was to determine the validity of an accelerometer to measure average acceleration values during high-speed running. Thirteen subjects performed three sprint efforts over a 40-m distance (n = 39). Acceleration was measured using a 100-Hz triaxial accelerometer integrated within a wearable tracking device (SPI-HPU; GPSports). To provide a concurrent measure of acceleration, timing gates were positioned at 10-m intervals (0-40 m). Accelerometer data collected during 0-10 m and 10-20 m provided a measure of average acceleration values. Accelerometer data was recorded as the raw output and filtered by applying a 3-point moving average and a 10-point moving average. The accelerometer could not measure average acceleration values during high-speed running. The accelerometer significantly overestimated average acceleration values during both 0-10 m and 10-20 m, regardless of the data filtering technique (p < 0.001). Body mass significantly affected all accelerometer variables (p < 0.10, partial η = 0.091-0.219). Body mass and the absence of a gravity compensation formula affect the accuracy and practicality of accelerometers. Until GPSports-integrated accelerometers incorporate a gravity compensation formula, the usefulness of any accelerometer-derived algorithms is questionable.

Classification of team sport activities using a single wearable tracking device

Wearable tracking devices incorporating accelerometers and gyroscopes are increasingly being used for activity analysis in sports. However, minimal research exists relating to their ability to classify common activities. The purpose of this study was to determine whether data obtained from a single wearable tracking device can be used to classify team sport-related activities. Seventy-six non-elite sporting participants were tested during a simulated team sport circuit (involving stationary, walking, jogging, running, changing direction, counter-movement jumping, jumping for distance and tackling activities) in a laboratory setting. A MinimaxX S4 wearable tracking device was worn below the neck, in-line and dorsal to the first to fifth thoracic vertebrae of the spine, with tri-axial accelerometer and gyroscope data collected at 100Hz. Multiple time domain, frequency domain and custom features were extracted from each sensor using 0.5, 1.0, and 1.5s movement capture durations. Features were further screened using a combination of ANOVA and Lasso methods. Relevant features were used to classify the eight activities performed using the Random Forest (RF), Support Vector Machine (SVM) and Logistic Model Tree (LMT) algorithms. The LMT (79-92% classification accuracy) outperformed RF (32-43%) and SVM algorithms (27-40%), obtaining strongest performance using the full model (accelerometer and gyroscope inputs). Processing time can be reduced through feature selection methods (range 1.5-30.2%), however a trade-off exists between classification accuracy and processing time. Movement capture duration also had little impact on classification accuracy or processing time. In sporting scenarios where wearable tracking devices are employed, it is both possible and feasible to accurately classify team sport-related activities.

Classification of team sport activities using a single wearable tracking device

Wearable tracking devices incorporating accelerometers and gyroscopes are increasingly being used for activity analysis in sports. However, minimal research exists relating to their ability to classify common activities. The purpose of this study was to determine whether data obtained from a single wearable tracking device can be used to classify team sport-related activities. Seventy-six non-elite sporting participants were tested during a simulated team sport circuit (involving stationary, walking, jogging, running, changing direction, counter-movement jumping, jumping for distance and tackling activities) in a laboratory setting. A MinimaxX S4 wearable tracking device was worn below the neck, in-line and dorsal to the first to fifth thoracic vertebrae of the spine, with tri-axial accelerometer and gyroscope data collected at 100Hz. Multiple time domain, frequency domain and custom features were extracted from each sensor using 0.5, 1.0, and 1.5s movement capture durations. Features were further screened using a combination of ANOVA and Lasso methods. Relevant features were used to classify the eight activities performed using the Random Forest (RF), Support Vector Machine (SVM) and Logistic Model Tree (LMT) algorithms. The LMT (79-92% classification accuracy) outperformed RF (32-43%) and SVM algorithms (27-40%), obtaining strongest performance using the full model (accelerometer and gyroscope inputs). Processing time can be reduced through feature selection methods (range 1.5-30.2%), however a trade-off exists between classification accuracy and processing time. Movement capture duration also had little impact on classification accuracy or processing time. In sporting scenarios where wearable tracking devices are employed, it is both possible and feasible to accurately classify team sport-related activities.

Validation of a Trunk-mounted Accelerometer to Measure Peak Impacts during Team Sport Movements

This study assessed the validity of an accelerometer to measure impacts in team sports. 76 participants completed a team sport circuit. Accelerations were collected concurrently at 100 Hz using an accelerometer and a 36-camera motion analysis system. The largest peak accelerations per movement were compared in 2 ways: i) pooled together and filtered at 13 different cut-off frequencies (range 6-25 Hz) to identify the optimal filtering frequency, and ii) the optimal cut-off frequency split into the 7 movements performed (n=532). Raw and 25-16 Hz filtering frequencies significantly overestimated and 6 Hz underestimated motion analysis peak accelerations (P <0.007). The 12 Hz filtered accelerometer data revealed the strongest relationship with motion analysis data (accuracy - 0.01±0.27 g, effect size - 0.01, agreement - 0.55 to 0.53 g, precision 0.27 g, and relative error 5.5%; P=1.00). The accelerometer underestimated peak accelerations during tackling and jumping, and overestimated during walking, jogging, sprinting and change of direction. Lower agreement and reduced precision were associated with sprinting, jumping and tackling. The accelerometer demonstrated an acceptable level of concurrent validity compared to a motion analysis system when filtered at a cut-off frequency of 12 Hz. The results advocate the use of accelerometers to measure movements in team sport.

Validity of a trunk-mounted accelerometer to assess peak accelerations during walking, jogging and running

The purpose of this study was to validate peak acceleration data from an accelerometer contained within a wearable tracking device while walking, jogging and running. Thirty-nine participants walked, jogged and ran on a treadmill while 10 peak accelerations per movement were obtained (n = 390). A single triaxial accelerometer measured resultant acceleration during all movements. To provide a criterion measure of acceleration, a 12-camera motion analysis (MA) system tracked the position of a retro-reflective marker affixed to the wearable tracking device. Peak raw acceleration recorded by the accelerometer significantly overestimated peak MA acceleration (P < 0.01). Filtering accelerometer data improved the relationship with the MA system (P < 0.01). However, only the 10 Hz and 8 Hz cut-off frequencies significantly reduced the errors found. The walk movement demonstrated the highest accuracy, agreement and precision and the lowest relative errors. Linear increases in error were observed for jog compared with walk and for run compared to both other movements. As the magnitude of acceleration increased, the strength of the relationship between the accelerometer and the criterion measure decreased. These results indicate that filtered accelerometer data provide an acceptable means of assessing peak accelerations, in particular for walking and jogging.

Validity of an upper-body-mounted accelerometer to measure peak vertical and resultant force during running and change-of-direction tasks

This study assessed the validity of a tri-axial accelerometer worn on the upper body to estimate peak forces during running and change-of-direction tasks. Seventeen participants completed four different running and change-of-direction tasks (0 degrees, 45 degrees, 90 degrees, and 180 degrees; five trials per condition). Peak crania-caudal and resultant acceleration was converted to force and compared against peak force plate ground reaction force (GRF) in two formats (raw and smoothed). The resultant smoothed (10 Hz) and crania-caudal raw (except 180 degrees) accelerometer values were not significantly different to resultant and vertical GRF for all running and change-of-direction tasks, respectively. Resultant accelerometer measures showed no to strong significant correlations (r = 0.00-0.76) and moderate to large measurement errors (coefficient of variation [CV] = 11.7-23.9%). Crania-caudal accelerometer measures showed small to moderate correlations (r = -0.26 to 0.39) and moderate to large measurement errors (CV = 15.0-20.6%). Accelerometers, within integrated micro-technology tracking devices and worn on the upper body, can provide a relative measure of peak impact force experienced during running and two change-of-direction tasks (45 degrees and 90 degrees) provided that resultant smoothed values are used.