Overnight fasting compromises exercise intensity and volume during sprint interval training but improves high-intensity aerobic endurance
Bibliographic record
Abstract
BACKGROUND: The combined effects of sprint interval training (SIT) and exercising in the fasted state are unknown. We compared the effects of SIT with exogenous carbohydrate supplementation (SIT-CHO) and SIT following overnight fast (SIT-Fast) on aerobic capacity (peak oxygen consumption: V̇O2peak) and high-intensity aerobic endurance (time-to-exhaustion at 85% V̇O2peak [T85%]). METHODS: Twenty male cyclists were randomized to SIT-CHO and SIT-Fast. Both groups performed 30-second all-out cycling followed by 4-minute active recovery 3 times per week for 4 weeks, with the number of sprint bouts progressing from 4 to 7. Peak power output (PPO) and total mechanical work were measured for each sprint interval bout. The SIT-CHO group performed exercise sessions following breakfast and consumed carbohydrate drink during exercise, whereas the SIT-Fast group performed exercise sessions following overnight fast and consumed water during exercise. Before and after training, V̇O2peak and T85% were assessed. Blood glucose, non-esterified fatty acids, insulin and glucagon concentrations were measured during T85%. RESULTS: Overall PPO and mechanical work were lower in SIT-Fast than SIT-CHO (3664.9 vs. 3871.7 J/kg; P=0.021 and 10.6 vs. 9.9 W/kg; P=0.010, respectively). Post-training V̇O2peak did not differ between groups. Baseline-adjusted post-training T85% was longer in SIT-Fast compared to SIT-CHO (19.7±3.0 vs. 16.6±3.0 minutes, ANCOVA P=0.038) despite no changes in circulating energy substrates or hormones. CONCLUSIONS: Our results suggest that SIT-Fast compromises exercise intensity and volume but still can have a greater impact on the ability to sustain high-intensity aerobic endurance exercise compared to SIT-CHO.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".