Prediction Of Time-trial Performance In cycling By Various Exercise Testing Protocols

Nicolas BENOIT [UCL] Francaux, Marc [UCL]

Prediction of time-trial performance in cycling by various exercise testing protocols Benoit N., Champenois A., Francaux M. Institute of Neuroscience, Université catholique de Louvain, Louvain-la-Neuve, Belgium Purpose For several years, researchers have tried to predict cycling performance on the basis of various exercise tests. The purpose of the present study was to determine which exercise protocol - among the commonly used in literature- provides the physiological data enabling the best prediction for a time-trial performance. Methods : On two separate occasions (from 48h to 72h between each), 10 male well-trained young cyclists (24.3±3.3 yrs) took part in 4 exercise protocols. An incremental maximal test provided VO2max, maximal power output at VO2max (MPO), maximal blood lactate concentration (LaMAX), power output at onset of blood lactate accumulation (POBLA) and mechanical efficiency (MEFF). The power output at maximal lactate steady state (PMLSS) was obtained by measuring blood lactate concentration at mid-duration and at the end of each step during a 3 x 8 minutes progressive intensity protocol. The isokinetic maximal power output (MIP) was calculated by fitting a parabolic function in the power output/pedaling rate obtained from 7 bouts of 6-s maximal exercise. The pedaling rates were fixed from 80 to 140 rpm. The performance was assessed by the time and the mean power output developed during a 600 kJ performance test (Power Time Trial, PTT). Results : The mean time to complete the prescribed work was 35min49s ± 3min18s (±SD) corresponding to a PTT of 281.5±26.1W. Correlation analyses showed a significant relationship between PTT and VO2max (71.19±7.76ml.min.kg-1 , r=0.61 , P>0.05), MPO (361±33.2W , r=0.89 , P<0.001), LaMAX (11.5±2.1mmol.L-1 , r=0.25 , P>0.05), POBLA (288.3±29.1W , r=0.92 , P<0.001), MEFF (21.5±1.7% , r=0.61 , P>0.05), PMLSS (259±26.6W , r=0.97 , P<0.001) and MIP (962.2±140.8W , r=0.18 , P>0.05). Stepwise multiple linear regression analysis identified PMLSS as the best predictor of PTT. No other variable was able to improve significantly the variance explained, leading to the following equation : PTT=3991-7.1xPMLSS. Conclusion : PMLSS seems to be the best predictor of a middle-duration time trial performance (35min) in well-trained cyclists.