Data Processing Strategies to Determine Maximum Oxygen Uptake: A Systematic Scoping Review and Experimental Comparison with Guidelines for Reporting.

BACKGROUND: Gas exchange data from maximum oxygen uptake ([Formula: see text]) testing typically require post-processing. Different processing strategies may lead to varying [Formula: see text] values affecting their interpretation. However, the exact processing strategies used in the literature have yet to be systematically investigated. Previous research investigated differences across methods at the group level only. METHODS: Out of a random sample, we investigated 242 recently published articles that measured [Formula: see text] during ramp tests. Reported data processing methods and their rationale were extracted. We compared the most common processing strategies on a data set of 72 standardized exercise tests in trained athletes. RESULTS: Half of the included studies did not report their data processing strategy and almost all articles failed to provide a rationale for the particular strategy chosen. Most studies use binned time averages to determine [Formula: see text], with a minority using moving time or moving breath averages. The processing strategies found in the literature can lead to mean differences in [Formula: see text] of more than 5% (range 0-7%) with considerable variation at the individual level. CONCLUSIONS: We advise researchers to change their processing strategy and use moving averages or digital filters instead of binned averages. Researchers should report their data processing strategy used to determine [Formula: see text]. We provide a reporting checklist of seven items that can function as a template for reporting.

Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running?

Endurance running performance can be predicted by maximal oxygen uptake (V̇O2max), the fractional utilisation of oxygen uptake (%V̇O2max) and running economy at lactate threshold (REOBLA). This study aims to assess maximal lactate accumulation rate (cLamax) in terms of improving running performance prediction in trained athletes. Forty-four competitive female and male runners/triathletes performed an incremental step test, a 100-m sprint test and a ramp test to determine their metabolic profile. Stepwise linear regression was used to predict 5000-m time trial performance. Split times were recorded every 200-m to examine the 'finishing kick'. Females had a slower t5k and a lower V̇O2max, cLamax, 'finishing kick' and REOBLA. Augmenting Joyner's model by means of cLamax explained an additional 4.4% of variance in performance. When performing the same analysis exclusively for males, cLamax was not included. cLamax significantly correlated with %V̇O2max (r=-0.439, p=0.003) and the 'finishing kick' (r=0.389, p=0.010). cLamax allows for significant (yet minor) improvements in 5000-m performance prediction in a mixed-sex group. This margin of improvement might differ in middle-distance events. Due to the relationship to the 'finishing kick', cLamax might be related to individual pacing strategies, which should be assessed in future research.