Back

Relationships between acute race-induced changes in creatine kinase activity and blood plasma myoglobin concentration and race performance in mountain bike and road cyclists

Hebisz, P.; Borkowski, J.; Hebisz, R.

2021-05-17 physiology
10.1101/2021.05.17.444439 bioRxiv
Show abstract

The aim of this study was to determine if the changes in plasma creatine kinase (CK) activity and myoglobin (MB) concentrations as markers of muscle damage differ between competitive road (n = 14) and mountain bike (n = 11) cyclists and if these biochemical markers show a relationship with real-world race performance. CK and MB were measured from blood samples collected 2 hours before race start and 1 hour after race completion and the change in pre- and post-race difference was calculated ({Delta}CK and {Delta}MB). An incremental exercise test was used to determine maximal oxygen uptake, maximal aerobic power, and power output at the second ventilatory threshold. Post-race CK and MB increased in the whole group of cyclists. Although the magnitude of change in CK was similar in both road and mountain bike cyclists, only the increase in road cyclists was significant. MB significantly increased only in mountain bike cyclists. Multiple regression analysis revealed a significant association between both road and mountain bike race performance and {Delta}CK and {Delta}MB. The other significant predictors for mountain bike race performance were maximal aerobic power (W{middle dot}kg-1) and power output at the second ventilatory threshold (W{middle dot}kg-1) and for road race performance both maximal oxygen uptake (l{middle dot}min-1) and power output at the second ventilatory threshold (W). In conclusion, mountain bike racing was associated with an increase in MB whereas road racing with an increase in CK, with the post-race changes in CK and MB related to race performance as high {Delta}CK and low {Delta}MB were obtained by better-performing cyclists.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.