Exploring the ergogenic potential of carbohydrate–caffeine combined mouth rinse on exercise and cognitive performance: a systematic review
Bibliographic record
Abstract
Carbohydrate (CHO) and caffeine (CAF) mouth rinsing have been independently reported to benefit sport performance. The proposed mechanisms by which mouth rinsing CHO exerts an influence are reported to be different from those for mouth rinsing CAF. However, the potential ergogenic effects of combining CHO and CAF in a single mouth rinse solution, are unclear. This study aimed to review the available evidence of CHO–CAF combined mouth rinse on exercise and cognitive performance in human participants. A systematic literature search was conducted using five databases until April 2024, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) recommendations. Among the nine randomized crossover studies included, only one study showed significant improvements in lower-body muscular endurance with CHO–CAF mouth rinse (effect size (ES): 0.48; p < 0.05), while two studies reported non-statistically significant improvements in repeated sprint performance compared to other mouth rinse and placebo conditions (ES: 0.20–0.81; p = 0.07–0.18). However, for other performance measures, including repeated jumps, upper-body strength and endurance, endurance cycling, and intermittent recovery run, most evidence (five studies) did not demonstrate significant ergogenic effects. Notably, of the two studies that examined cognitive performance, both reported significant improvements with CHO–CAF mouth rinse compared with the placebo condition (ES: 0.45–3.45; p < 0.05). Overall, a synergistic influence of CHO–CAF mouth rinse on physical exercise performance is not evident, but preliminary evidence suggests potential benefits on cognitive performance. Future studies are required to address various methodological issues identified in this review, while practitioners and athletes should exercise caution when considering this novel nutritional strategy.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".