Dr Mark Cooke

Travel to high altitude is increasingly popular. With this comes an increased incidence of high-altitude illness and therefore an increased need to improve our strategies to prevent and accurately diagnose these. In this review, we provide a summary of recent advances of relevance to practitioners who may be advising travelers to altitude. Although the Lake Louise Score is now widely used as a diagnostic tool for acute mountain sickness (AMS), increasing evidence questions the validity of doing so, and of considering AMS as a single condition. Biomarkers, such as brain natriuretic peptide, are likely correlating with pulmonary artery systolic pressure, thus potential markers of the development of altitude illness. Established drug treatments include acetazolamide, nifedipine, and dexamethasone. Drugs with a potential to reduce the risk of developing AMS include nitrate supplements, propagators of nitric oxide, and supplemental iron. The role of exercise in the development of altitude illness remains hotly debated, and it appears that the intensity of exercise is more important than the exercise itself. Finally, despite copious studies demonstrating the value of preacclimatization in reducing the risk of altitude illness and improving performance, an optimal protocol to preacclimatize an individual remains elusive.

Introduction. Aldosterone decreases at high altitude (HA) but the effect of hypoxia on angiotensin converting-enzyme (ACE), a key step in the renin-angiotensin-aldosterone system, is unclear. Materials and Methods. We investigated the effects of exercise and acute normobaric hypoxia (NH, ~11.0% FiO2) on nine participants and six controls undertaking the same exercise at sea-level (SL). NH exposure lasted 5 hours with 90 min of submaximal treadmill walking. Blood samples for aldosterone, ACE and cortisol were taken throughout exposure and at rest during a trek to HA (5140 m) in eight separate participants. Results. There was no difference in cortisol or aldosterone between groups pre-exercise. Aldosterone rose with exercise to a greater extent at SL than in NH (post-exercise: 700±325 vs 335±238 pmol/L, mean ± SD, p=0.044). Conversely, cortisol rose to a greater extent in NH (post-exercise: 734±165 vs 344±159 nmol/L, mean ± SD, p=0.001). There were no differences in ACE activity. During the trek to HA resting aldosterone and cortisol reduced with no change in ACE. Conclusion. Acute NH subdues the exercise-associated rise in aldosterone but stimulates cortisol, whereas prolonged exposure at HA reduces both resting aldosterone and cortisol. As ACE activity was unchanged in both environments this is not the mechanism underlying the fall in aldosterone.

This report provides an analysis of all finalists’ best jumps and comprised a biomechanical analysis of the two steps before the take-off board along with the hop, step and jump sections also being presented. Finally, an analysis of the landing is also presented. This is a useful analysis for those interested in triple jump performance. The full report is available from the IAAF website: https://www.iaaf.org/about-iaaf/documents/research

This report provides a biomechanical analysis of the best performances of all men's long jump finalists of the three steps before take-off, with a more in-depth examination of the last step. This is a useful tool for those interested in the approach to to the take-off board. The full report is available from the IAAF website: https://www.iaaf.org/about-iaaf/documents/research

This report provides a biomechanical analysis of the best performances of all women's long jump finalists of the three steps before take-off, with a more in-depth examination of the last step. This is a useful tool for those interested in the approach to to the take-off board. The full report is available from the IAAF website: https://www.iaaf.org/about-iaaf/documents/research

This report provides an analysis of all finalists’ best jumps and comprised a biomechanical analysis of the two steps before the take-off board along with the hop, step and jump sections also being presented. Finally, an analysis of the landing is also presented. This is a useful analysis for those interested in triple jump performance. The full report is available from the IAAF website: https://www.iaaf.org/about-iaaf/documents/research

This study tested the performance of OpenPose on footage collected by two cameras at 200 Hz from a real-life competitive setting by comparing it with manually analyzed data in SIMI motion. The same take-off recording from the men's Long Jump finals at the 2017 World Athletics Championships was used for both approaches (markerless and manual) to reconstruct the 3D coordinates from each of the camera's 2D coordinates. Joint angle and Centre of Mass (COM) variables during the final step and take-off phase of the jump were determined. Coefficients of Multiple Determinations (CMD) for joint angle waveforms showed large variation between athletes with the knee angle values typically being higher (take-off leg: 0.727 ± 0.242; swing leg: 0.729 ± 0.190) than those for hip (take-off leg: 0.388 ± 0.193; swing leg: 0.370 ± 0.227) and ankle angle (take-off leg: 0.247 ± 0.172; swing leg: 0.155 ± 0.228). COM data also showed considerable variation between athletes and parameters, with position (0.600 ± 0.322) and projection angle (0.658 ± 0.273) waveforms generally showing better agreement than COM velocity (0.217 ± 0.241). Agreement for discrete data was generally poor with high random error for joint kinematics and COM parameters at take-off and an average ICC across variables of 0.17. The poor agreement statistics and a range of unrealistic values returned by the pose estimation underline that OpenPose is not suitable for in-competition performance analysis in events such as the long jump, something that manual analysis still achieves with high levels of accuracy and reliability.

This study compared angle-specific hamstring:quadricep (H:Q) ratios with their discrete counterparts during strength testing in pro fessional male footballers. Twenty-eight professional English Premier League footballers were recruited for this study (age: 22 6 4 years; stature: 1.81 6 0.07 m; body mass: 75.2 6 6.8 kg). Isokinetic testing of the knee flexors and extensors was conducted concentrically at 2 angular velocities (60˚ and 240˚·s21 ) and eccentrically (for the knee flexors only) at 30˚·s21 . Conventional H:Q ratio was calculated as the ratio between peak joint moment in the flexors and extensors at 60˚·s21 . Functional H:Q ratio was calculated as the peak joint moment in the flexors during the eccentric condition and the extensors at 240˚·s21 . Discrete conventional and functional H:Q ratios were 0.56 6 0.06% and 1.28 6 0.22%, respectively. The residual differences between discrete values and angle-specific residual values were 13.60 6 6.56% when normalized to the magnitude of the discrete value. For the functional ratios, the normalized residual was 21.72 6 5.61%. Therefore, neither discrete ratio was representative of angle-specific ratios, although the conventional ratio had lower error overall. Therefore, practitioners should consider H:Q ratio throughout the full isokinetic range of motion, not just the discrete ratio calculated from peak joint moments, when designing and implementing training programs or monitoring injury risk, recovery from injury, and readiness to return to play

INTRODUCTION: Whilst the link between physical factors and risk of high altitude (HA)-related illness and acute mountain sickness (AMS) have been extensively explored, the influence of psychological factors has been less well examined. In this study we aimed to investigate the relationship between 'anxiety and AMS risk during a progressive ascent to very HA. METHODS: Eighty health adults were assessed at baseline (848m) and over 9 consecutive altitudes during a progressive trek to 5140m. HA-related symptoms (Lake Louise [LLS] and AMS-C Scores) and state anxiety (State-Trait-Anxiety-Score [STAI Y-1]) were examined at each altitude with trait anxiety (STAI Y-2) at baseline. RESULTS: The average age was 32.1 ± 8.3 years (67.5% men). STAI Y-1 scores fell from 848m to 3619m, before increasing to above baseline scores (848m) at ≥4072m (p = 0.01). STAI Y-1 scores correlated with LLS (r = 0.31; 0.24-0.3; P<0.0001) and AMS-C Scores (r = 0.29; 0.22-0.35; P<0.0001). There was significant main effect for sex (higher STAI Y-1 scores in women) and altitude with no sex-x-altitude interaction on STAI Y-1 Scores. Independent predictors of significant state anxiety included female sex, lower age, higher heart rate and increasing LLS and AMS-C scores (p<0.0001). A total of 38/80 subjects (47.5%) developed AMS which was mild in 20 (25%) and severe in 18 (22.5%). Baseline STAI Y-2 scores were an independent predictor of future severe AMS (B = 1.13; 1.009-1.28; p = 0.04; r2 = 0.23) and STAI Y-1 scores at HA independently predicted AMS and its severity. CONCLUSION: Trait anxiety at low altitude was an independent predictor of future severe AMS development at HA. State anxiety at HA was independently associated with AMS and its severity.

There is evidence to suggest that high altitude (HA) exposure leads to a fall in heart rate variability (HRV) that is linked to the development of acute mountain sickness (AMS). The effects of sex on changes in HRV at HA and its relationship to AMS are unknown. HRV (5-minute single lead ECG) was measured in 63 healthy adults (41 men and 22 women) aged 18-56 years at sea level (SL) and during a HA trek at 3619m, 4600m and 5140m respectively. The main effects of altitude (SL, 3619, 4600 and 5140m) and sex (men vs women) and their potential interaction were assessed using a Factorial Repeated Measures ANOVA. Logistic regression analyses were performed to assess the ability of HRV to predict AMS. Men and women were of similar age (31.2 ±9.3 vs 31.7±7.5 years), ethnicity, body and mass index. There was main effect for altitude on heart rate, SDNN (standard deviation [SD] of normal-to-normal [NN] intervals), RMSSD (Root mean square of successive differences), NN50 (number of pairs of successive NNs differing by >50 ms), pNN50 (NN50 / total number of NNs), very low frequency (VLF), low frequency (LF), high frequency (HF) and total power (TP). The most consistent effect on post hoc analysis was reduction in these HRV measures between 3619 and 5140m at HA. Heart rate was significantly lower and SDNN, RMSSD, LF, HF and TP were higher in men compared with women at HA. There was no interaction between sex and altitude for any of the HRV indices measured. HRV was not predictive of AMS development. Increasing HA leads to a reduction in HRV. Significant differences between men and women emerge at HA. HRV was not predictive of AMS.

INTRODUCTION: Distance runners train at different speeds to enhance their physiological and biomechanical capabilities to ensure that their aerobic and anaerobic energy systems are optimised for the demands of racing. The kinematic, kinetic, spatiotemporal, and global stiffness changes that occur as an athlete increases speed are not well understood in well-trained middle-distance runners. The aim of this study was to analyse the biomechanical responses of middle-distance athletes to increases in treadmill speed. METHODS: Thirteen male athletes (1.79 ± 0.07 m, 66.7 ± 6.1 kg, 22.3 ± 3.2 y) and two female athletes (stature: 1.69 ± 0.01 m, mass: 55.7 ± 0.4 kg, 30.9 ± 2.6 y) participated. Their mean World Athletics points for personal best performances were 1114 (± 73). Each athlete ran on a Gaitway 3D instrumented treadmill (1000 Hz) during an incremental test at 12, 16, 20 and 24 km/h. Data were collected during the second half of each 1-min stage. Two Fastec T5 high-speed cameras (200 Hz) were placed to the sides of the treadmill to record each side of the body separately, and the starting times were synchronised with the treadmill’s data collection period. Ground reaction force (GRF) and spatiotemporal data were measured using the treadmill software; lower limb joint angles were measured using the high-speed videos in SIMI Motion; and global stiffness characteristics were calculated using peak vertical GRF via the methods of Morin et al. (JAB, 2005, 21(2), 167–180). RESULTS: Both step length and cadence increased at each faster running speed (from 1.24 m and 2.70 Hz at 12 km/h to 2.01 m and 3.32 Hz at 24 km/h). Ground contact time decreased during each stage (0.229, 0.194, 0.168 and 0.147 s, respectively), but flight time only increased until 20 km/h (0.143, 0.160 and 0.163 s), with lower values at 24 km/h (0.155 s). Duty factor decreased during each stage (0.308, 0.274, 0.254 and 0.244, respectively) although leg stiffness was consistent throughout testing (11.4, 11.4, 11.4 and 11.6 N/mm, respectively). Vertical push-off rate increased consistently during each stage (31.6, 41.4, 51.2 and 59.9 BW/s, respectively). The main changes that occurred in joint angles and positions at initial contact were an increase in thigh angle (21, 25, 28 and 29°, respectively), shank angle (3, 5, 7 and 8°, respectively) and hip-ankle horizontal distance (0.18, 0.22, 0.25 and 0.27 m, respectively). CONCLUSION: It was unsurprising that athletes increased step length and cadence with faster treadmill belt speeds, although the increase in cadence from 20 to 24 km/h was the only one that arose from both shorter contact and flight times. The lack of reliance on increased flight time, and the very small increases in joint angles and positions from 20 to 24 km/h, show that there is an anthropometric limit on achieving faster speeds, which require greater force production during the push-off phase. Athletes should thus note the need for appropriate strength and conditioning within their training regimens.

Central arterial systolic blood pressure (SBP) and arterial stiffness are known to be better predictors of adverse cardiovascular outcomes than brachial SBP. The effect of progressive high altitude (HA) on these parameters has not been examined. Ninety healthy adults were included. Central BP and the augmentation index (AI) were measured at the level of the brachial artery (Uscom BP + device) at <200 m and at 3619, 4600 and 5140 m. The average age of the subjects (70% men) were 32.2±8.7 years. Compared with central arterial pressures, brachial SBP (+8.1±6.4 mm Hg; P<0.0001) and pulse pressure (+10.9±6.6 mm Hg; P<0.0001) were significantly higher and brachial diastolic BP was lower (-2.8±1.6 mm Hg; P<0.0001). Compared with <200 m, HA led to a significant increase in brachial and central SBP. Central SBP correlated with AI (r=0.50; 95% confidence interval (CI): 0.41-0.58; P<0.0001) and age (r=0.32; 95% CI: 21-0.41; P<0.001). AI positively correlated with age (r=0.39; P<0.001) and inversely with subject height (r=-0.22; P<0.0001), weight (r=-0.19; P=0.006) and heart rate (r=-0.49; P<0.0001). There was no relationship between acute mountain sickness scores (Lake Louis Scoring System (LLS)) and AI or central BP. The independent predictors of central SBP were male sex (coefficient, t=4.7; P<0.0001), age (t=3.6; P=0.004) and AI (t=7.5; P<0.0001; overall r 2 =0.40; P<0.0001). Subject height (t=2.4; P=0.02), age (7.4; P<0.0001) and heart rate (t=11.4; P<0.0001) were the only independent predictors of AI (overall r 2 =0.43; P<0.0001). Central BP and AI significantly increase at HA. This rise was influenced by subject-related factors and heart rate but not independently by altitude, LLS or SpO 2.

Purpose To investigate whether there is a differential response at rest and following exercise to conditions of genuine high altitude (GHA), normobaric hypoxia (NH), hypobaric hypoxia (HH) and normobaric normoxia (NN). Method Markers of sympathoadrenal and adrenocortical function (plasma normetanephrine [PNORMET], metanephrine [PMET], cortisol), myocardial injury (highly sensitive cardiac troponin T [hscTnT]) and function (N-terminal brain natriuretic peptide [NT-proBNP]) were evaluated at rest and with exercise under NN, at 3375 m in the Alps (GHA) and at equivalent simulated altitude under NH and HH. Participants cycled for 2 hours {15 minute warm-up, 105 minutes at 55% Wmax (maximal workload)} with venous blood samples taken prior (T0), immediately following (T120) and 2 hours post-exercise (T240). Results Exercise in the three hypoxic environments produced a similar pattern of response with the only difference between environments being in relation to PNORMET. Exercise in NN only induced a rise in PNORMET and PMET. Conclusion Biochemical markers that reflect sympathoadrenal, adrenocortical and myocardial responses to physiological stress demonstrate significant differences in the response to exercise under conditions of normoxia versus hypoxia while NH and HH appear to induce broadly similar responses to GHA and may therefore be reasonable surrogates.

The British Service Dhaulagiri Research Expedition took place in March-May 2016. A total of 129 personnel took part in the expedition and were invited to consent to a variety of study protocols investigating adaptation to high altitudes and diagnosis of altitude illness. The study took place in a remote and inhospitable environment at altitudes up to 7500m. This paper gives an overview of the challenges involved, the research protocols investigated and the execution of the expedition in Nepal.

INTRODUCTION: Markerless motion capture (MMC) is increasing in popularity among biomechanists because of the reduced data collection time and removal of subjects needing to wear tight, minimalist clothing [1]. However, gait analysis often requires subjects to walk or run at multiple speeds, such as in an incremental exercise test. The sensitivity of MMC to detect kinematic changes across speeds has yet to be thoroughly explored, so the aim of this study was to compare kinematic responses to changes in gait speed when measured with a widely used marker-based system versus a MMC system. METHOD: Fifteen healthy, adult participants walked on an instrumented treadmill (1,000 Hz; Gaitway3D; h/p/cosmos) at 3 and 5 km/h and ran at 10, 11, and 12 km/h. A 14-camera optoelectronic motion capture system (Oqus 7+, Qualisys) was used to collect marker data, where markers were placed according to Cappozzo et al. [2]. Markerless video data were collected synchronously with 12 high-speed video cameras (Miqus, Qualisys). Both systems were sampling at 100 Hz. Markerless data were exported to Theia3D for processing, before being exported to Visual3D for modelling alongside marker data. Gait events were determined using the kinetic data, which was the same for both motion capture systems. Kinematic data were exported to MATLAB to calculate changes in sagittal angular data between gait speeds. RESULTS: For walking (changes between 3-5 km/h), MMC demonstrated the capacity to measure similar changes in joint range of motion (ROM), peak flexion, and peak extension for hip, knee, and ankle joints (ICC[3,1] ≥ 0.892) when compared to marker-based data, and there were no significant differences between the change in joint kinematics between systems (p > 0.05). MMC also displayed moderate-to-excellent agreement for knee and ankle joint kinematics during running (changes between 10-11 and 11-12 km/h), including ROM and peak flexion/extension (ICC ≥ 0.626). However, the hip joint was less consistent, with poor-to-moderate agreement generally being found, especially in peak hip extension (ICC = 0.198 when comparing differences between 11-12 km/h). There were no significant differences between systems during running (p < 0.05). CONCLUSION: MMC was able to measure small changes in joint angles during walking at similar magnitudes to traditional marker-based motion capture, which is promising for clinical biomechanists and gait analysis clinics. However, MMC importantly performs less well when trying to measure joint angle changes during different running speeds, with varying results between lower limb joints. Researchers and practitioners should be cautious when interpreting sagittal-plane kinematic changes during running when employing MMC as the chosen method of motion capture. REFERENCES: [1] Kanko, RM et al. (2021) J Biomech;127:110665 [2] Cappozzo, A et al. (1995) Clin Biomech;10:171-8