Ketone ester ingestion increases exogenous carbohydrate storage and lowers glycemia during post-exercise recovery: a randomised crossover trial
Bibliographic record
Abstract
Abstract β-hydroxybutyrate can suppress endogenous glucose production, with potential implications for carbohydrate metabolism during post-exercise recovery. The aim of the current study was to assess the effects of ketone ester ingestion during post-exercise recovery, on carbohydrate metabolism and subsequent exercise capacity. Thirteen endurance-trained men (age: 18–61 years, maximal aerobic capacity: 50 to 73 mL kg −1 min −1 ) completed two conditions in a randomized crossover design. During both conditions, participants performed two exhaustive bouts of running separated by 4 h of recovery, during which they ingested sucrose (1 g kg −1 h −1 and high natural abundance 13 C) and whey protein (0.4 g kg −1 h −1 ) beverages. In one condition, the beverage was supplemented with 0.29 g kg −1 h −1 of ketone monoester (KETONE), in the other, the beverage was supplemented with an isoenergetic (fat), taste-matched placebo (PLACEBO). Breath samples were analysed for CO 2 production and 13 C enrichment to determine the fate of ingested carbohydrate. Blood was sampled to examine metabolite and insulin concentrations. KETONE increased blood β-hydroxybutyrate concentrations (> 3.5 mmol L −1 versus PLACEBO, p < 0.0001) and retention of ingested sucrose (from 206 ± 26 g with PLACEBO to 220 ± 26 g with KETONE, p = 0.001) while lowering glycemia (> 1 mmol L −1 versus PLACEBO, p < 0.0001). This occurred with no evidence of increased gastrointestinal distress during recovery, but mild additional lower gastrointestinal distress during the second run ( p = 0.03). There was no evidence for differences in time-to-exhaustion during the second run (PLACEBO:54 ± 33 min, KETONE:52 ± 28 min; p = 0.87). In conclusion, ketone ester ingestion during post-exercise recovery augments retention of ingested carbohydrates and lowers glycemia. No evidence for increased exercise capacity was detected during subsequent running.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".