The aim of this study was to examine the influence of the performance level of athletes on pacing strategy during a simulated 10-km running race, and the relationship between physiological variables and pacing strategy. Twenty-four male runners performed an incremental exercise test on a treadmill, three 6-min bouts of running at 9, 12 and 15 km h(-1), and a self-paced, 10-km running performance trial; at least 48 h separated each test. Based on 10-km running performance, subjects were divided into terziles, with the lower terzile designated the low-performing (LP) and the upper terzile designated the high-performing (HP) group. For the HP group, the velocity peaked at 18.8 +/- 1.4 km h(-1) in the first 400 m and was higher than the average race velocity (P < 0.05). The velocity then decreased gradually until 2,000 m (P < 0.05), remaining constant until 9,600 m, when it increased again (P < 0.05). The LP group ran the first 400 m at a significantly lower velocity than the HP group (15.6 +/- 1.6 km h(-1); P > 0.05) and this initial velocity was not different from LP average racing velocity (14.5 +/- 0.7 km h(-1)). The velocity then decreased non-significantly until 9,600 m (P > 0.05), followed by an increase at the end (P < 0.05). The peak treadmill running velocity (PV), running economy (RE), lactate threshold (LT) and net blood lactate accumulation at 15 km h(-1) were significantly correlated with the start, middle, last and average velocities during the 10-km race. These results demonstrate that high and low performance runners adopt different pacing strategies during a 10-km race. Furthermore, it appears that important determinants of the chosen pacing strategy include PV, LT and RE.

This study investigated clinic and ambulatory blood pressure (BP) responses after a single bout of low-intensity resistance exercise in normotensive subjects. Fifteen healthy subjects underwent 2 experimental sessions: control-40 minutes of seated rest, and exercise-6 resistance exercises, with 3 sets of as many repetitions as possible until moderate fatigue, with an intensity of 50% of 1-repetition maximum (1RM). Before and for 60 minutes after interventions, clinic BP was measured by auscultatory and oscillometric methods. Postintervention ambulatory BP levels were also measured for 24 hours. In comparison with preintervention values, clinic systolic BP, as measured by the auscultatory method, did not change in the control group, but it decreased after exercise (-3.7 +/- 1.6 mm Hg, p < 0.05). Diastolic and mean BP levels increased after intervention in the control group (+3.4 +/- 1.0 and +3.0 +/- 0.8 mm Hg, respectively, p < 0.05) and decreased in the exercise group (-3.6 +/- 1.7 and -3.4 +/- 1.4 mm Hg, respectively, p < 0.05). Systolic and mean oscillometric BP levels did not change after interventions either in the control or exercise sessions, whereas diastolic BP increased after intervention in the control group (+5.0 +/- 1.7 mm Hg, p < 0.05) but not change after exercise. Ambulatory BP behaviors after interventions were similar in the control and exercise sessions. Significant and positive correlations were observed between preexercise values and postexercise clinic and ambulatory BP decreases. In conclusion, in the whole sample, a single bout of low-intensity resistance exercise decreased postexercise BP under clinic, but not ambulatory, conditions. However, considering individual responses, postexercise clinic and ambulatory hypotensive effects were greater in subjects with higher preexercise BP levels.

The aim of this study was to verify the power of VO2max, peak treadmill running velocity (PTV), and running economy (RE), unadjusted or allometrically adjusted, in predicting 10 km running performance. Eighteen male endurance runners performed: 1) an incremental test to exhaustion to determine VO2max and PTV; 2) a constant submaximal run at 12 km·h−1 on an outdoor track for RE determination; and 3) a 10 km running race. Unadjusted (VO2max, PTV and RE) and adjusted variables (VO2max0.72, PTV0.72 and RE0.60) were investigated through independent multiple regression models to predict 10 km running race time. There were no significant correlations between 10 km running time and either the adjusted or unadjusted VO2max. Significant correlations (p < 0.01) were found between 10 km running time and adjusted and unadjusted RE and PTV, providing models with effect size > 0.84 and power > 0.88. The allometrically adjusted predictive model was composed of PTV0.72 and RE0.60 and explained 83% of the variance in 10 km running time with a standard error of the estimate (SEE) of 1.5 min. The unadjusted model composed of a single PVT accounted for 72% of the variance in 10 km running time (SEE of 1.9 min). Both regression models provided powerful estimates of 10 km running time; however, the unadjusted PTV may provide an uncomplicated estimation.

PROPÓSITO: Caracterizar o comportamento do lactato sanguíneo ([La]), durante protocolo progressivo em esteira rolante, e investigar a aplicabilidade do modelo Dmax na detecção do limiar de lactato (LL) e rendimento esportivo. MÉTODOS: Vinte e sete homens atletas de nível regional executaram protocolo de Heck et al. (1985), com incrementos a cada três minutos. O rendimento esportivo foi obtido pela velocidade média da prova de 10km. O 1º e 2º LL foram determinados através de análise visual da curva das [La] (LLv1 e LLv2) e por interpolação na velocidade referente às concentrações de 2,0 e 3,5mmol.l¹ (LL2,0 e LL3,5). O modelo Dmax identificou o LL em valores medidos (DmaxMED) e preditos pelas funções polinomial (DmaxPOL), linear de dois segmentos (DmaxSEG) e exponencial contínua (DmaxEXP). A característica do lactato sanguíneo durante o teste incremental foi verificada pelos ajustes linear de dois segmentos e exponencial contínua. RESULTADOS: Não houve diferença significativa entre o somatório dos resíduos quadrados dos ajustes de curva, porém, houve tendência de melhor ajuste exponencial contínua em 70,4% da amostra. Enquanto não houve diferença significativa entre os DmaxMED, DmaxPOL, DmaxSEG e DmaxEXP, os métodos Dmax foram maiores do que LLv1, menores do que LL3,5 e não diferentes de LL2,0. Todos os critérios Dmax foram significativamente menores do que a velocidade média da prova de 10km. CONCLUSÕES: Enquanto as [La] tenderam a um aumento exponencial durante protocolos progressivos em esteira rolante, o modelo Dmax apresentou evidências da sua aplicabilidade para a detecção do LL, mas não do rendimento esportivo.

This study examined the influence of the O 2 kinetics on the running strategy adopted during a 10km running race in runners with different performance levels. Twenty-one runners (28.5 ± 5.3 years; 17.6 ± 7.3 cm; 66.3 ± 9.3 kg) performed 1) a test with increments of 1.2 km.h -1 every 3 min until exhaustion; 2) one 6-min test of constant velocity at 9 km.h -1 for determination of O 2 kinetics and; 3) a 10 km time trial simulation. The subjects were divided into two groups, Moderated Performance (MP) and Low Perfomance (LP), based on the 10-km running performance. Mean velocity (MP= 16.9 ± 0.8 vs BP= 14.9 ± 1 km.h -1 ) on the 10km race was significantly different (p<0.05) between groups. There were no differences (p>0.05) between groups in any kinetics parameters analyzed. However, the O 2 increase amplitude (A1 parameter) was inversely correlated with mean velocity (r= -0.48, p < 0.05) and with the partial velocities on time trial (r between -0.44 and -0.48, p < 0.05), except for the last session (r=-0.19, p > 0.05). In conclusion, the correlation of A1 parameter with the partial velocities suggests an influence of running economy on the strategy adopted during the 10 km time trial.