Heterogeneity and incidence of non-response for changes in cardiorespiratory fitness following time-efficient sprint interval exercise training
Bibliographic record
Abstract
Interindividual variability for training-induced changes in maximal oxygen uptake (V̇O2max) is well described following continuous aerobic and high-intensity interval training. Whether similar variability is observed following time-efficient sprint interval training with minimal training volume (i.e., reduced-exertion high-intensity interval training; REHIT) is unknown. We conducted a pooled analysis of n = 117 (68 men) training participants (mean ± SD: age: 30 ± 10 y; V̇O2max: 34.8 ± 7.5 mL·kg−1·min−1), who completed a V̇O2max assessment before and 3 days after 6 weeks of REHIT comprising of two 10–20-s ‘all-out’ cycling sprints per session, and n = 40 no-intervention control participants (age: 30 ± 13 y; V̇O2max: 31.5 ± 6.5 mL·kg−1·min−1) who completed repeated V̇O2max tests over a comparable timeframe. Individual responses estimated using 50% confidence intervals derived from the technical error were interpreted against a smallest worthwhile change of 1.75 mL·kg−1·min−1. The standard deviation of individual responses was 2.39 mL·kg−1·min−1 demonstrating clinically meaningful heterogeneity in training-induced changes in V̇O2max following REHIT that exceed the technical, biological and random within-subjects variability of V̇O2max assessment. The likely (75% probability) non-response rate was 18% (21/117), and 49% (57/117) of individuals demonstrated increases in V̇O2max likely higher than the smallest worthwhile change. We conclude that the well-described increase in V̇O2max following REHIT at the group level is subject to substantial variability in magnitude at an individual level. This has important implications for exercise prescription and can be harnessed to elucidate mechanisms of adaptation. Novelty: There is substantial heterogeneity in V̇O2max responses following time-efficient sprint interval training. Proportion of non-response was 18% and ∽50% of individuals show clinically meaningful increases in V̇O2max.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".