The effect of low- vs high-cadence interval training on the freely chosen cadence and performance in endurance-trained cyclists

Relative pedaling forces are low during cycling

We quantified and compared the mechanical force demands relative to the maximum dynamic force (MDF) of 11 cyclists when pedaling at different intensities (ventilatory threshold, maximum lactate steady state, respiratory compensation point, and maximal aerobic power), cadences (free, 40, 60 and 80 rpm), and all-out resisted sprints. Relative force demands (expressed as %MDF) progressively increased with higher intensities (p < 0.001) and lower cadences (p < 0.001). Notwithstanding, relative force demands were low (<54 % MDF) for all conditions, even during the so-called 'torque training'. These results might be useful when programming on-bike resistance training to improve torque production capacity.

Risk of bias and reporting practices in studies comparing VO2max responses to sprint interval vs. continuous training: A systematic review and meta-analysis

BACKGROUND

It remains unclear whether studies comparing maximal oxygen uptake (VO2max) response to sprint interval training (SIT) vs. moderate-intensity continuous training (MICT) are associated with a high risk of bias and poor reporting quality. The purpose of this study was to evaluate the risk of bias and quality of reporting in studies comparing changes in VO2max between SIT and MICT.

METHODS

We conducted a comprehensive literature search of 4 major databases: AMED, CINAHL, EMBASE, and MEDLINE. Studies were excluded if participants were not healthy adult humans or if training protocols were unsupervised, lasted less than 2 weeks, or utilized mixed exercise modalities. We used the Cochrane Collaboration tool and the CONSORT checklist for non-pharmacological trials to evaluate the risk of bias and reporting quality, respectively.

RESULTS

Twenty-eight studies with 30 comparisons (3 studies included 2 SIT groups) were included in our meta-analysis (n = 360 SIT participants: body mass index (BMI) = 25.9 ± 3.7 kg/m2, baseline VO2max = 37.9 ± 8.0 mL/kg/min; n = 359 MICT participants: BMI = 25.5 ± 3.8 kg/m2, baseline VO2max = 38.3 ± 8.0 mL/kg/min; all mean ± SD). All studies had an unclear risk of bias and poor reporting quality.

CONCLUSION

Although we observed a lack of superiority between SIT and MICT for improving VO2max (weighted Hedge's g = -0.004, 95% confidence interval (95%CI): -0.08 to 0.07), the overall unclear risk of bias calls the validity of this conclusion into question. Future studies using robust study designs are needed to interrogate the possibility that SIT and MICT result in similar changes in VO2max.

Comparison of training responses and performance adaptations in endurance-trained men and women performing high-intensity interval training

The efficacy of high-intensity interval training (HIIT) to elicit physiological and performance adaptations in endurance athletes has been established in men and to a lesser extent in women. This study compared lactate threshold (LT₂) and performance adaptations to HIIT between men and women. Nine male and eight female cyclists and triathletes completed trials to determine their LT₂ and 40 km cycling performance before, and after 10 HIIT sessions. Each HIIT session consisted of 10 × 90 s at peak power output, separated by 60 s active recovery. Main effects showed that HIIT improved peak power output (p = 0.05; ES: 0.2); relative peak power output (W.kg^-1; p = 0.04; ES: 0.3 and W.kg^-0.32; p = 0.04; ES: 0.3); incremental time to fatigue (p = 0.01; ES: 0.4), time trial time (p < 0.001; ES: 0.7) and time trial power output (p < 0.001; ES: 0.7) equally in both sexes. Although LT₂ power output explained 77% of the performance improvement in women, no variable explained the performance improvement in men, suggesting another mechanism(s) was involved. Although HIIT improved cycling performance in men and women, it might not be appropriate to evaluate the effectiveness of HIIT using the same variables for both sexes.

Power Assessment in Road Cycling: A Narrative Review

Nowadays, the evaluation of physiological characteristics and training load quantification in road cycling is frequently performed through power meter data analyses, but the scientific evidence behind this tool is scarce and often contradictory. The aim of this paper is to review the literature related to power profiling, functional threshold testing, and performance assessment based on power meter data. A literature search was conducted following preferred reporting items for review statement (PRISMA) on the topic of {“cyclist” OR “cycling” AND “functional threshold” OR “power meter”}. The reviewed evidence provided important insights regarding power meter-based training: (a) functional threshold testing is closely related to laboratory markers of steady state; (b) the 20-min protocol represents the most researched option for functional threshold testing, although shorter durations may be used if verified on an individual basis; (c) power profiling obtained through the recovery of recorded power outputs allows the categorization and assessment of the cyclist’s fitness level; and (d) power meters represent an alternative to laboratory tests for the assessment of the relationship between power output and cadence. This review elucidates the increasing amount of studies related to power profiling, functional threshold testing, and performance assessment based on power meter data, highlighting the opportunity for the expanding knowledge that power meters have brought in the road cycling field.

Performance determinants of fixed gear cycling during criteriums

Nowadays, fixed gear competitions on outdoor circuits such as criteriums are regularly organized worldwide. To date, no study has investigated this alternative form of cycling. The purpose of the present study was to examine fixed gear performance indexes and to characterize physiological determinants of fixed gear cyclists. This study was carried out in two parts. Part 1 (n = 36) examined correlations between performance indexes obtained during a real fixed gear criterium (time trial, fastest laps, averaged lap time during races, fatigue indexes) and during a sprint track time trial. Part 2 (n = 9) examined correlations between the recorded performance indexes and some aerobic and anaerobic performance outputs (VO_2max, maximal aerobic power, knee extensor and knee flexor maximal voluntary torque, vertical jump height and performance during a modified Wingate test). Results from Part 1 indicated significant correlations between fixed gear final performance (i.e. average lap time during the finals) and single lap time (time trial, fastest lap during races and sprint track time trial). In addition, results from Part 2 revealed significant correlations between fixed gear performance and aerobic indicators (VO_2max and maximal aerobic power). However, no significant relationship was obtained between fixed gear cycling and anaerobic qualities such as strength. Similarly to traditional cycling disciplines, we concluded that fixed gear cycling is mainly limited by aerobic capacity, particularly criteriums final performance. However, specific skills including technical competency should be considered.