ECSS Paris 2023: OP-MH03
INTRODUCTION: Exercising under strenuous environmental conditions can lead to fatal exertional heat stroke (EHS) if not managed promptly and adequately. Also, the number of athletes who do not finish a race (DNF) is believed to be influenced by environmental stress during competition. To measure heat stress, international federations rely on thermal indices, such as the Wet Bulb Globe Temperature (WBGT) in Athletics. However, the relationship between thermal indices, EHS incidence, and DNF rates in elite endurance athletes remains unclear. The aim of this study was therefore to i) quantify the incidence of EHS and DNF events in World Athletics competitions, ii) examine their association with thermal indices, and iii) develop predictive models to estimate EHS and DNF risk before a race. METHODS: Eighty Athletics endurance races held between 2019 and 2024 were included in the analysis, encompassing the World Championships and the Olympic Games. Environmental parameters (e.g., temperature, humidity) and WBGT were measured on-site and linked to race-specific details (e.g., distance, race time), and the number of DNF and EHS (called dependent variables) were counted. Additionally, several thermal indices (e.g., PET, mPET, UTCI) and energy expenditure were estimated for each race. To analyse the relationship between predictors and the dependent variables, a linear regression analysis was conducted, with a significance level at 0.05. Additionally, Generalized Additive Models (GAM) with k-fold cross validation were used to assess the prediction power of models on unknown races. RESULTS: A total of 41 EHS cases were diagnosed among 4938 athletes (8/1000 athlete exposures) with 56 races (70%) reporting no EHS and 24 races (30%) recording between 1 and 5 cases. In average, each race led 6 ± 9 DNF, ranging from 0 to 60. The strongest EHS linear regression was observed for UTCI (R²=0.10, p=0.003), while WBGT showed a lower association (R²=0.06, p=0.025). For DNF, race distance was the strongest linear regression (R²=0.40, p<0.001) while WBGT association was not significant (R²=0.01, p=0.58). The best GAM for predicting EHS included temperature, WBGT, mean radiant temperature, and the days elapsed since the last spring onset, with an R² of 0.20 ± 0.15. For DNF, the best GAM included WBGT, race time, and mean velocity, achieving an R² of 0.80 ± 0.03. CONCLUSION: Our analysis showed that WBGT alone has only a weak linear relationship with EHS and DNF in Athletics and that more recent thermal indices (e.g., UTCI), while improved, still do not demonstrate a sufficiently strong association. Likewise, non-linear prediction models incorporating environmental parameters and race-specific details do not provide a robust estimation of EHS. This suggests that key factors contributing to EHS were not accounted for in our analysis. However, the prediction models for DNF proved to be robust, allowing for an accurate estimation of the number of athletes who will not finish the race, before the start of the competition.
Read CV David BandieraECSS Paris 2023: OP-MH03
INTRODUCTION: Genetic variance is an important risk factor for many musculoskeletal soft-tissue injuries, including ACL rupture. Several direct-to-consumer genetic tests have emerged that claim to be able to test for susceptibility to such injuries[1]. Only a single company uses injury-specific genetic markers based on the findings of genome-wide association studies (GWAS), an arguably more robust and scientifically reliable approach than the traditional candidate gene studies. The genetic markers identified by GWAS used to determine ACL rupture risk include rs188099931 (A/G), rs186727643 (C/T) and rs144051132 (T/A)[2]. However, their viability as reliable markers of injury risk has yet to be critically and scientifically evaluated in independent cohorts. Thus, this study aimed to determine whether rs188099931, rs186727643 and rs144051132 are associated with ACL rupture across multiple population groups. METHODS: A genetic association study, comprising cases clinically diagnosed with ACL rupture (ACL), a subset of cases who had sustained an ACL rupture via a non-contact mechanism (NON) and a control group (CON), was conducted whereby participants from four cohorts of European ancestry; South African (CON=229, ACL=242, NON=161), Australian (CON=82, ACL=330, NON=149), Polish (CON=147, ACL=142, NON=56) and Swedish (CON=116, ACL=95, NON=79), as well as a South African mixed ancestry (MA) cohort (CON=106, ACL=99, NON=51), were genotyped for the three variants using TaqMan™ Genotyping assays. Genotype distributions were compared between ACL and CON groups, as well as NON and CON groups. RESULTS: No significant associations between the three variants and ACL rupture were reported. Furthermore, several genotypes were either absent or rare. Specifically, the rs188099931 GG, rs186727643 TT and rs144051132 AA genotypes were not detected. Six rs188099931 AG [CON(0.2%, n=1) vs ACL(0.6%, n=5), p=0.410; CON vs NON(0.7%, n=3), p=0.448)], one rs186727643 CT [ACL(0.1%, n=1), p=1.000; NON(0.2%, n=1), p=0.589) and 12 rs144051132 TA [CON(0.7%, n=4) vs ACL(1.0%, n=8), p=0.770; CON vs NON(0.9%, n=4), p= 0.819] genotypes were identified across the European cohorts. In the MA cohort, one rs188099931 AG [CON(0.9%, n=1), p=1.000], eight rs186727643 CT [CON(2.8%, n=3) vs ACL(5.1%, n=5), p=0.486; NON(2.0%, n=1), p=0.092] and three rs144051132 TA [CON(0.9%, n=1) vs ACL(2.0%, n=2), p=0.611; NON(2.0%, n=1), p=0.489] genotypes were identified. All three heterozygote genotypes were absent from the Swedish cohort, while rs188099931 AG and rs186727643 CT were absent from the Polish cohort. The rs186727643 CT genotype was also absent from the South African cohort. CONCLUSION: The scientific evidence is too weak to support an association between ACL rupture and rs188099931, rs186727643 or rs144051132. The observed rarity of the effect alleles suggests that the use of these variants as reliable markers of ACL rupture risk is not viable, and we do not support their inclusion as markers of ACL rupture risk in a genetic test.
Read CV Caryn PhipsonECSS Paris 2023: OP-MH03
INTRODUCTION: Repetitive head impacts in contact sports may have significant effects on neural function even in the absence of a diagnosed concussion. While much attention has been given to the cognitive and motor consequences of concussive injuries, less is known about the impact of sub-concussive head impacts on auditory processing. This is an essential function for communication in dynamic sporting environments but also acts as a physiological marker for brain health. This study investigates how contact sports influence auditory neural responses by comparing cortical and sub-cortical electrophysiological markers between contact and non-contact athletes. METHODS: We tested n=54 tier 2 athletes age (mean ± SD) (20.24 ± 1.99 years), height (1.76 ± 0.09m) and body mass (77.2 ± 12.7kg) divided into two groups of n=28 contact sport and n=26 non-contact sport athletes. Groups were matched for age (contact: 20.25 ± 1.92 years; non-contact: 20.23 ± 2.1 years, t(52) = -0.035, p >0.05) and body mass index (BMI) (contact: 25.38 ± 3.35; non-contact: 24.08 ± 2.44, t(52) = -1.76, p >0.05). There was no significant difference in sex distribution (contact: 10 female, 18 male; non-contact: 17 female, 9 male, χ²(1) = 3.63, p >0.05). Cortical (N100) and sub-cortical (auditory brainstem responses) responses were recorded using 32-channel electroencephalography (EEG) to measure auditory neural processing under two conditions: (i) low neurophysiological stress (no background noise) and (ii) high neurophysiological stress (background noise). RESULTS: Results from a mixed-model two-way ANOVA revealed a significant main effect of group (F(1,52) = 4.476, p <0.05) for the auditory cortical responses, where contact athletes showed a reduced neural response to sound (N100 amplitudes, -2.07 ± 1.7µV) compared to non-contact athletes (-2.81 ± 1.54µV). There was no significant main effect of stress condition (F(1,52) = 2.060, p >0.05) and no significant group x stress condition interaction (F(1,52) = 1.822, p >0.05). Sub-cortical neural responses (F0 amplitudes) showed no significant group (F(1,52) = 1.246, p >0.05), stress condition (F(1,52) = 2.088, p >0.05) or interaction effect (F(1,52) = 2.181, p >0.05). CONCLUSION: These findings show that cortical auditory processing may be more vulnerable to repetitive sub-concussive head impacts than sub-cortical responses. This suggests that cortical brain areas are more susceptible to impact-induced dysfunction than sub-cortical brain areas, indicating that sub-concussive injury is potentially damaging to cortical neural generators of the auditory N100 response.
Read CV Jessica AndrewECSS Paris 2023: OP-MH03