m in water of below 5°C) is becoming increasingly popular. Since the foundation of the International Ice Swimming Association (IISA) in 2009, official races are held as World Cup Races and World Championships. Ice swimming was a demonstration sport at the 2014 Winter Olympics in Sochi, Russia. This case study aimed to identify core body temperature and selected hematological and biochemical parameters before and after repeated "Ice Miles." An experienced ice swimmer completed 6 consecutive Ice Miles within 2 days. Three Ice Miles adhered to the strict criteria for the definition of Ice Miles, whereas the other 3 were very close (i.e., 5.2, 6.1, and 6.6°C) to the temperature limit. Swimming times, changes in core body temperatures, and selected urinary and hematological parameters were recorded. The athlete showed after each Ice Mile a metabolic acidosis (i.e., an increase in lactate and TCO2; a decrease in base excess and HCO3) and an increase in blood glucose, cortisol, and creatine kinase concentration. The decrease in pH correlated significantly and negatively with the increase in cortisol level, indicating that this intense exercise causes a metabolic stress. The change in core body temperature between start and finish was negatively associated with metabolic acidosis. The increase in creatine kinase suggests skeletal muscle damages due to shivering after an Ice Mile. For athletes and coaches, swimming in cold water during Ice Miles leads to a metabolic acidosis, which the swimmer tries to compensate with a respiratory response. Considering the increasing popularity of ice swimming, the findings have practical value for swimmers and practitioners (e.g., coaches, exercise physiologists, and physicians) working with them because our results provide a detailed description of acute physiological responses to repeated swimming in cold conditions. These findings are of importance for athletes and coaches for National Championships and World Championships in Ice Swimming following the IISA rules.

Ice Mile swimming (1608 m in water of below 5 °Celsius) is becoming increasingly popular. This case study aimed to identify body core temperature and selected haematological and biochemical parameters before and after repeated Ice Miles. An experienced ice swimmer completed three consecutive Ice Miles within 15 h. Swim times, body core temperatures, and selected urinary and haematological parameters were recorded. Body core temperature reached its maximum between 5, 8 and 15 min after immersion (37.7°C, 38.1°C, and 38.0°C, respectively). The swimmer suffered hypothermia during the first Ice Mile (35.4°C) and body core temperature dropped furthermore to 34.5°C during recovery after the first Ice Mile. He developed a metabolic acidosis in both the first and the last Ice Mile (pH 7.31 and pH 7.34, respectively). We observed hyperkalaemia ([K⁺]> 5.5 mM) after the second Ice Mile (6.9 mM). This was followed by a drop in [K⁺] to3.7 mM after the third Ice Mile. Anticipatory thermogenesis (i.e. an initial increase of body core temperature after immersion in ice cold water) seems to be a physiological response in a trained athlete. The results suggest that swimming in ice-cold water leads to a metabolic acidosis, which the swimmer compensates with hyperventilation (i.e. leading to respiratory alkalosis). The shift of serum [K⁺] could increase the risk of a cardiac arrhythmia. Further studies addressing the physiology and potential risks of Ice Mile swimming are required to substantiate this finding.

Despite the increasing scientific interest in the relationship between pacing and performance in endurance sports, little information is available about pacing and pacing variation in ultra-endurance events such as ultra-triathlons. Therefore, we aimed to investigate the trends of pacing, pacing variation, the influence of age, sex, and performance level in ultra-triathlons of different distances. We analysed 969 finishers (849 men, 120 women) in 46 ultra-triathlons longer than the original Ironman® distance (e.g., Double-, Triple-, Quintuple- and Deca Iron ultra-triathlons) held from 2004 to 2015. Pacing speed was calculated for every cycling and running lap. Pacing variation was calculated as the coefficient of variation (%) between the average speed of each lap. Performance level (i.e., fast, moderate, slow) was defined according to the 33.3 and 66.6 percentile of the overall race time. A multivariate analysis (two-way ANOVA) was applied for the overall race time as the dependent variable with ‘sex’ and ‘age group’ as independent factors. Another multivariate model with ‘age’ and ‘sex’ as covariates (two-way ANCOVA) was applied with pacing variation (cycling and running) as the dependent variable with ‘race’ and ‘performance level’ as independent factors. Different pacing patterns were observed by event and performance level. The general pacing strategy applied was a positive pacing. In Double and Triple Iron ultra-triathlon, faster athletes paced more evenly with less variation than moderate or slower athletes. The variation in pacing speed increased with the length of the race. There was no significant difference in pacing variation between faster, moderate, and slower athletes in Quintuple and Deca Iron ultra-triathlon. Women had a slower overall performance than men. The best overall times were achieved at the age of 30–39 years. Successful ultra-triathlon athletes adapted a positive pacing strategy in all race distances. The variation in pacing speed increased with the length of the race. In shorter ultra-triathlon distances (i.e., Double and Triple Iron ultra-triathlon), faster athletes paced more evenly with less variation than moderate or slower athletes. In longer ultra-triathlon distances (i.e., Quintuple and Deca Iron ultra-triathlon), there was no significant difference in pacing variation between faster, moderate, and slower athletes.

Background: Despite the increasing scientific interest in the relationship between pacing and performance in endurance sports, little information is available about pacing and pacing variation in ultra-endurance events such as ultra-triathlons. Therefore, we aimed to investigate the trends of pacing, pacing variation, the influence of age, sex, and performance level in ultra-triathlons of different distances.Methods: We analysed 969 finishers (849 men, 120 women) in 46 ultra-triathlons longer than the original Ironman® distance (e.g., Double-, Triple-, Quintuple- and Deca Iron ultra-triathlons) held from 2004-2015. Pacing speed was calculated for every cycling and running lap. Pacing variation was calculated as the coefficient of variation (%) between the average speed of each lap. Performance level (i.e., fast, moderate, slow) was defined according to the 33.3 and 66.6 percentile of the overall race time. A multivariate analysis (two-way ANOVA) was applied for the overall race time as the dependent variable with ‘sex’ and ‘age group’ as independent factors. Another multivariate model with ‘age’ and ‘sex’ as covariates (two-way ANCOVA) was applied with pacing variation (cycling and running) as the dependent variable with ‘race’ and ‘performance level’ as independent factors.Results: Different pacing patterns were observed by event and performance level. The general pacing strategy applied was positive pacing. In Double and Triple Iron ultra-triathlon, faster athletes paced more evenly with less variation than moderate or slower athletes. The variation in pacing speed increased with the length of the race. There was no significant difference in pacing variation between faster, moderate, and slower athletes in Quintuple and Deca Iron ultra-triathlon. Women had a slower overall performance than men. The best overall times were achieved at the age of 30-39 years.Conclusion: Successful ultra-triathlon athletes adapted a positive pacing strategy in all race distances. The variation in pacing speed increased with the length of the race. In shorter ultra-triathlon distances (i.e., Double and Triple Iron ultra-triathlon), faster athletes paced more evenly with less variation than moderate or slower athletes. In longer ultra-triathlon distances (i.e., Quintuple and Deca Iron ultra-triathlon), there was no significant difference in pacing variation between faster, moderate, and slower athletes.