The Effect of Pre-Exercise Caffeine and Glucose Ingestion on Endurance Capacity in Hypoxia: A Double-Blind Crossover Trial
Bibliographic record
Abstract
The impact of caffeine and glucose supplementation in a hypoxic environment on endurance exercise performance remains inconclusive. The current study examined the effect of pre-exercise carbohydrate and caffeine supplementation on endurance exercise performance in an acute hypoxic environment. Eight healthy active young males participated in this double-blind, within-subjects crossover study. Participants ingested the test drink 60 min before exercising at 50% Wmax for 90 min on a cycle ergometer (fatiguing preload); there followed an endurance performance test at 85% Wmax until exhaustion in a hypoxic chamber (~15%O2). Participants completed four experimental trials in a randomized order: caffeine (6 mg·kg−1; Caff), glucose (1 g·kg−1; CHO), caffeine (6 mg·kg−1) + glucose (1 g·kg−1; Caff−CHO), and taste- and color-matched placebo with no caffeine or CHO (PLA). Blood samples were collected during fasting, pre-exercise, every 30 min throughout the exercise, and immediately after exhaustion. The caffeine and glucose trials significantly enhanced endurance capacity in hypoxic conditions by Caff, 44% (68.8–31.5%, 95% confidence interval), CHO, 31% (44.7–15.6%), and Caff−CHO, 46% (79.1–13.2%). Plasma-free fatty-acid and glycerol concentrations were higher in Caff and PLA than in CHO and Caff−CHO (p < 0.05). The estimated rate of fat oxidation was higher in Caff and PLA than in CHO and Caff−CHO (p < 0.05). There were no significant differences in ratings of perceived exertion between trials. In conclusion, the ingestion of caffeine, glucose, or caffeine + glucose one hour before exercising in hypoxic conditions significantly improved 85% Wmax endurance performance after prolonged exercise.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".