Effect Of Energy Drink Consumption On Heart Rate Variability And Blood Glucose In Relation To Exercise
Bibliographic record
Abstract
There is high prevalence of adverse events associated with caffeinated energy drink (CED) consumption. PURPOSE: This study aimed to examine the acute physiological effects of CED in apparently-healthy volunteers, pre-, during-, and post-exercise. METHODS: A randomized cross-over double-blind design with three experimental conditions was used: a CED condition, a matched caffeine-carbohydrate beverage condition (MB), and a control beverage condition (CB). Participants underwent blood glucose, heart rate variability (HRV), and heart rate measures pre- and post-exercise. During the exercise component, participants increased cycling intensity to a respiratory exchange ratio of 0.96 to 0.98 and maintained the workload for 20-minutes. Blood glucose, HRV, and heart rate measures were compared using two-way ANOVA, and exercise measures were compared using one-way ANOVA. RESULTS: As seen in Figure 1, an effect of condition on blood glucose (p < 0.001), an effect of time on blood glucose (p < 0.001), and an effect of condition x time on blood glucose (p < 0.001) was observed. Specifically, pre-exercise there was a increase in blood glucose in the CED condition relative to the MB condition (6.59±0.63 vs. 5.61±0.76 mmol⋅L-1, p < 0.001), and in the MB condition relative to the CB condition (5.61±0.76 vs. 5.28±0.40 mmol⋅L-1, p = 0.045). There was no effect of condition on HRV, heart rate, or exercise measures. CONCLUSION: Given the increased blood glucose in the CED condition relative to the MB conditions it is concluded that an ingredient in commercial CED must stimulate the endogenous release of glucose into circulation.Fig. 1: Mean condition blood glucose concentration values over time. Effect of condition and time (p < 0.001), effect of condition x time (p < 0.001). * indicates statistical significance between conditions (p < 0.050).
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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) | 0.000 | 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) | 0.001 | 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".