Caffeine Attenuates Decreases in Leg Power Without Increased Muscle Damage
Bibliographic record
Abstract
Ribeiro, BG, Morales, AP, Sampaio-Jorge, F, Barth, T, de Oliveira, MBC, Coelho, GMdO, and Leite, TC. Caffeine attenuates decreases in leg power without increased muscle damage. J Strength Cond Res 30(8): 2354-2360, 2016-Caffeine ingestion has been shown to be an effective ergogenic aid in several sports. Caffeine administration may increase exercise capacity, which could lead to a greater degree of muscle damage after exercise. This was a randomized, double-blind, placebo-controlled crossover study. Six male handball athletes ingested placebo (PLA) or caffeine (CAF) (6 mg·kg body mass) capsules on 2 different occasions. Sixty minutes after ingestion of the capsules, serum CAF levels were evaluated. Thereafter, all participants performed a protocol of vertical jumps (VJs). The protocol consisted of 4 sets of 30 seconds of continuous VJs with 60 seconds of recovery between sets. Blood lactate (LAC) and creatine kinase (CK) levels were determined before and after the protocol. We found significant differences in serum CAF levels between PLA (0.09 ± 0.18 µg·ml) vs. CAF (6.59 ± 4.44 µg·ml) (p < 0.001). Caffeine elicited a 5.23% (p ≤ 0.05) improvement in the leg power compared with PLA. The CAF trial displayed higher LAC (p ≤ 0.05) compared with PLA (6.26 ± 2.01 vs. 4.39 ± 2.42 mmol·L, respectively) after protocol of VJs, whereas no difference in CK was observed between trials (p > 0.05). These results indicate that immediate ingestion of CAF (6 mg·kg body weight) can reduce the level of muscle fatigue and preserve leg power during the test, possibly resulting in increase in LAC. There was no increase in muscle damage, which indicates that immediate administration of (6 mg·kg body weight) CAF is safe. Thus, nutritional interventions with CAF could help athletes withstand a greater physiological overload during high-intensity training sessions. The results of this study would be applicable to sports and activities that require repetitive leg power.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".