M T W Veltmeijer 1 , D H J Thijssen 1 , M T E Hopman 1 , T M H Eijsvogels 1 . Show Affiliations »
Abstract
AIM: To assess the within-subject variation of thermoregulatory responses during 2 consecutive 15-km road races. Secondly, we explored whether gastrointestinal temperature (TGI) data from the first race could improve our previously established predictive model for finish TGI in the second race. METHODS: We measured TGI before and immediately after both races in 58 participants and determined correlation coefficients. Finish TGI in the second race was predicted using a linear regression analysis including age, BMI, pre-race fluid intake, TGI increase between baseline and the start of the race and finish TGI in the first race. RESULTS: Under cool conditions (WBGT 11-12°C), TGI was comparable between both races at baseline (37.6±0.4°C vs. 37.9±0.4°C; p=0.24) and finish (39.4±0.6°C vs. 39.4±0.6°C; p=0.83). Finish TGI correlated significantly between both races (r=0.50; p<0.001). The predictive model (p<0.001) could predict 32.2% of the finish TGI in the second race (vs. 17.1% without finish TGI in race 1). CONCLUSION: Our findings demonstrate that the use of previously obtained thermoregulatory responses results in higher predictability of finish core body temperatures in future races, enabling better risk assessment for those athletes that are most likely to benefit from preventive measures. © Georg Thieme Verlag KG Stuttgart · New York.
AIM: To assess the within-subject variation of thermoregulatory responses during 2 consecutive 15-km road races. Secondly, we explored whether gastrointestinal temperature (TGI) data from the first race could improve our previously established predictive model for finish TGI in the second race. METHODS: We measured TGI before and immediately after both races in 58 participants and determined correlation coefficients. Finish TGI in the second race was predicted using a linear regression analysis including age, BMI, pre-race fluid intake, TGI increase between baseline and the start of the race and finish TGI in the first race. RESULTS: Under cool conditions (WBGT 11-12°C), TGI was comparable between both races at baseline (37.6±0.4°C vs. 37.9±0.4°C; p=0.24) and finish (39.4±0.6°C vs. 39.4±0.6°C; p=0.83). Finish TGI correlated significantly between both races (r=0.50; p<0.001). The predictive model (p<0.001) could predict 32.2% of the finish TGI in the second race (vs. 17.1% without finish TGI in race 1). CONCLUSION: Our findings demonstrate that the use of previously obtained thermoregulatory responses results in higher predictability of finish core body temperatures in future races, enabling better risk assessment for those athletes that are most likely to benefit from preventive measures. © Georg Thieme Verlag KG Stuttgart · New York.
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Year: 2015
PMID: 25958942 DOI: 10.1055/s-0034-1398676
Source DB: PubMed Journal: Int J Sports Med ISSN: 0172-4622 Impact factor: 3.118