Smartphone-Enabled Heart Rate Variability and Acute Mountain Sickness.

INTRODUCTION: The autonomic system and sympathetic activation appears integral in the pathogenesis of acute mountain sickness (AMS) at high altitude (HA), yet a link between heart rate variability (HRV) and AMS has not been convincingly shown. In this study we investigated the utility of the smartphone-derived HRV score to predict and diagnose AMS at HA. METHODS: Twenty-one healthy adults were investigated at baseline at 1400 m and over 10 days during a trek to 5140 m. HRV was recorded using the ithlete HRV device. RESULTS: Acute mountain sickness occurred in 11 subjects (52.4%) at >2650 m. HRV inversely correlated with AMS Scores (r = -0.26; 95% CI, -0.38 to -0.13: P < 0.001). HRV significantly fell at 3700, 4100, and 5140 m versus low altitude. HRV scores were lower in those with both mild (69.7 ± 14.0) and severe AMS (67.1 ± 13.1) versus those without AMS (77.5 ± 13.1; effect size n = 0.043: P = 0.007). The HRV score was weakly predictive of severe AMS (AUC 0.74; 95% CI, 0.58-0.89: P = 0.006). The change (delta) in the HRV Score (compared with baseline at 1400 m) was a moderate diagnostic marker of severe AMS (AUC 0.80; 95% CI, 0.70-0.90; P = 0.0004). A fall in the HRV score of >5 had a sensitivity of 83% and specificity of 60% to identify severe AMS (likelihood ratio 1.9). Baseline HRV at 1400 m was not predictive of either AMS at higher altitudes. CONCLUSIONS: The ithlete HRV score can be used to help in the identification of severe AMS; however, a baseline score is not predictive of future AMS development at HA.

Are Habitual Hydration Strategies of Female Rugby League Players Sufficient to Maintain Fluid Balance and Blood Sodium Concentration During Training and Match-Play? A Research Note From the Field.

Limited data exist on the hydration status of female athletes, with no data available on female rugby players. The objective of this study was to investigate the habitual hydration status on arrival, sweat loss, fluid intake, sweat Na loss, and blood [Na+] during field training and match-play in 10 international female rugby league players. Urine osmolality on arrival to match-play (382 ± 302 mOsmol·kg(-1)) and training (667 ± 260 mOsmol·kg(-1)) was indicative of euhydration. Players experienced a body mass loss of 0.50 ± 0.45 and 0.56 ± 0.53% during match-play and training, respectively. During match-play, players consumed 1.21 ± 0.43 kg of fluid and had a sweat loss of 1.54 ± 0.48 kg. During training, players consumed 1.07 ± 0.90 kg of fluid, in comparison with 1.25 ± 0.83 kg of sweat loss. Blood [Na+] was well regulated (Δ-0.7 ± 3.4 and Δ-0.4 ± 2.6 mmol·L(-1)), despite sweat [Na+] of 47.8 ± 5.7 and 47.2 ± 6.3 mmol·L(-1) during match-play and training. The findings of this study show mean blood [Na+] that seems to be well regulated despite losses of Na in sweat and electrolyte-free fluid consumption. For the duration of the study, players did not experience a body mass loss (dehydration >2%) indicative of a reduction in exercise performance, thus habitual hydration strategies seem adequate. Practitioners should evaluate the habitual hydration status of athletes to determine whether interventions above habitual strategies are warranted.

Physiological and Movement Demands of Rugby League Referees: Influence on Penalty Accuracy.

Research into the physiological and movement demands of Rugby League (RL) referees is limited, with only 1 study in the European Super League (SL). To date, no studies have considered decision making in RL referees. The purpose of this study was to quantify penalty accuracy scores of RL referees and to determine the relationship between penalty accuracy and total distance covered (TD), high-intensity running (HIR), and heart rate per 10-minute period of match play. Time motion analysis was undertaken on 8 referees over 148 European SL games during the 2012 season using 10-Hz global positioning system analysis and heart rate monitors. The number and timing of penalties awarded was quantified using Opta Stats. Referees awarded the correct decision on 74 ± 5% of occasions. Lowest accuracy was observed in the last 10-minute period of the game (67 ± 13%), with a moderate drop (effect size = 0.86) in accuracy observed between 60-70 minutes and 70-80 minutes. Despite this, there were only small correlations observed between mean heart rate, TD, HIR efforts, and penalty accuracy. Although a moderate correlation was observed between maximum velocity and accuracy. Despite only small correlations observed, it would be rash to assume that physiological and movement demands of refereeing have no influence on decision making. More likely, other confounding variables influence referee decision-making accuracy, requiring further investigation. Findings can be used by referees and coaches to inform training protocols, ensuring training is specific to both cognitive and physical match demands.

Dehydration and hyponatremia in professional rugby union players: a cohort study observing english premiership rugby union players during match play, field, and gym training in cool environmental conditions.

Fluid and sodium balance is important for performance and health; however, limited data in rugby union players exist. The purpose of the study was to evaluate body mass (BM) change (dehydration) and blood[Na] change during exercise. Data were collected from 10 premiership rugby union players, over a 4-week period. Observations included match play (23 subject observations), field (45 subject observations), and gym (33 subject observations) training sessions. Arrival urine samples were analyzed for osmolality, and samples during exercise were analyzed for [Na]. Body mass and blood[Na] were determined pre- and postexercise. Sweat[Na] was analyzed from sweat patches worn during exercise, and fluid intake was measured during exercise. Calculations of fluid and Na loss were made. Mean arrival urine osmolality was 423 ± 157 mOsm·kg, suggesting players were adequately hydrated. After match play, field, and gym training, BM loss was 1.0 ± 0.7, 0.3 ± 0.6, and 0.1 ± 0.6%, respectively. Fluid loss was significantly greater during match play (1.404 ± 0.977 kg) than field (1.008 ± 0.447 kg, p = 0.021) and gym training (0.639 ± 0.536 kg, p < 0.001). Fluid intake was 0.955 ± 0.562, 1.224 ± 0.601, and 0.987 ± 0.503 kg during match play, field, and gym training, respectively. On 43% of observations, players were hyponatremic when BM increased, 57% when BM was maintained, and 35% when there was a BM loss of 0.1-0.9%. Blood[Na] was the representative of normonatremia when BM loss was >1.0%. The findings demonstrate that rugby union players are adequately hydrated on arrival, fluid intake is excessive compared with fluid loss, and some players are at risk of developing hyponatremia.

Mouth Rinsing With Carbohydrate Solutions at the Postprandial State Fail to Improve Performance During Simulated Cycling Time Trials.

Mouth rinsing with carbohydrate (CHO) solutions during cycling time trials results in performance enhancements; however, most studies have used approximately 6% CHO solutions. Therefore, the purpose of this study was to compare the effectiveness of mouth rinsing with 4, 6, and 8% CHO solutions on 1-hour simulated cycling time trial performance. On 4 occasions, 7 trained male cyclists completed at the postprandial period, a set amount of work as fast as possible in a randomized counterbalanced order. The subjects rinsed their mouth for 5 seconds, on completion of each 12.5% of the trial, with 25 ml of a non-CHO placebo and 4, 6, and 8% CHO solutions. No additional fluids were consumed during the time trial. Heart rate (HR), ratings of perceived exertion (RPE), thirst (TH), and subjective feelings (SF) were recorded after each rinse. Furthermore, blood samples were drawn every 25% of the trial to measure blood glucose and blood lactate concentrations, whereas whole-body CHO oxidation was monitored continuously. Time to completion was not significant between conditions with the placebo, 4, 6, and 8% conditions completing the trials in 62.0 ± 3.0, 62.8 ± 4.0, 63.4 ± 3.4, and 63 ± 4.0 minutes, respectively. There were no significant differences between conditions in any of the variables mentioned above; however, significant time effects were observed for HR, RPE, TH, and SF. Post hoc analysis showed that TH and SF of subjects in the CHO conditions but not in the placebo were significantly increased by completion of the time trial. In conclusion, mouth rinsing with CHO solutions did not impact 1-hour cycling performance in the postprandial period and in the absence of fluid intake. Our findings suggest that there is scope for further research to explore the activation regions of the brain and whether they are receptive to CHO dose, before specific recommendations for athletic populations are established. Consequently, mouth rinsing as a practical strategy for coaches and athletes is questionable under specific conditions and should be carefully considered before its inclusion. Emphasis should be focused on appropriate dietary and fluid strategies during training and competition.

Variable and changing trajectories in youth athlete development: further verification in advocating a long-term inclusive tracking approach.

Athlete development through adolescence can vary greatly because of maturational processes. For example, variation can be observed in anthropometric and fitness measures with later maturing individuals "catching up" their earlier maturing peers at later time points. This study examined a methodological issue concerning how best to assess anthropometric and fitness change (i.e., "across age categories" or "per year") relative to an age and skill-matched population (N = 1,172). Furthermore, it examined changes in anthropometric and fitness characteristics in 3 cases of youth rugby league players (aged 13-15) across a 2-year period. Findings identified the "per year" method as generating less deviated z-scores across anthropometric and fitness measures (e.g., mean change p < 0.001), suggesting less substantial change in case players relative to the population. When applied to additional players, z-score and radar graphs showed developmental variability and longitudinal change. The possibility of a "later maturing player" increasing anthropometric (e.g., height: player 4 = 3.3 cm; player 5 = 13.2 cm; and player 6 = 15.7 cm) and fitness (e.g., 30-m sprint: player 4 = -0.18 s, player 5 = -0.46 s, and player 6 = -0.59 s) characteristics compared with early maturing players was confirmed. Findings affirm the potential for variable and changing trajectories in adolescent athletes. Practical implications advocate a long-term inclusive tracking approach of athletes, the avoidance of (de)selection, and the reduction of a performance emphasis in adolescent stages of sport systems.

An individualized longitudinal approach to monitoring the dynamics of growth and fitness development in adolescent athletes.

This study evaluated the development of anthropometric and fitness characteristics of 3 individual adolescent junior rugby league players and compared their characteristics with a cross-sectional population matched by age and skill level. Cross-sectional anthropometric and fitness assessments were conducted on 1,172 players selected to the Rugby Football League's talent development program (i.e., the Player Performance Pathway) between 2005 and 2008. Three players of differing relative age, maturational status, and playing position were measured and tracked once per year on 3 occasions (Under 13s, 14s, 15s age categories) and compared against the cross-sectional population. Results demonstrated that the later maturing players increased height (player 1 = 9.2%; player 2 = 7.8%) and a number of fitness characteristics (e.g., 60-m speed-player 1 = -14.9%; player 2 = -9.9%) more than the earlier maturing player (player 3-Height = 2.0%, 60-m sprint = -0.7%) over the 2-year period. The variation in the development of anthropometric and fitness characteristics between the 3 players highlights the importance of longitudinally monitoring individual characteristics during adolescence to assess the dynamic changes in growth, maturation, and fitness. Findings showcase the limitations of short-term performance assessments at one-off time points within annual-age categories, instead of advocating individual development and progression tracking without deselection. Coaches should consider using an individual approach, comparing data with population averages, to assist in the prescription of appropriate training and lifestyle interventions to aid the development of junior athletes.