Ketone Monoester Followed by Carbohydrate Ingestion after Glycogen-Lowering Exercise Does Not Improve Subsequent Endurance Cycle Time Trial Performance
Bibliographic record
Abstract
Relative to carbohydrate (CHO) alone, exogenous ketones followed by CHO supplementation during recovery from glycogen-lowering exercise have been shown to increase muscle glycogen resynthesis. However, whether this strategy improves subsequent exercise performance is unknown. The objective of this study was to assess the efficacy of ketone monoester (KME) followed by CHO ingestion after glycogen-lowering exercise on subsequent 20 km (TT20km) and 5 km (TT5km) best-effort time trials. Nine recreationally active men (175.6 ± 5.3 cm, 72.9 ± 7.7 kg, 28 ± 5 y, 12.2 ± 3.2% body fat, VO2max = 56.2 ± 5.8 mL· kg BM−1·min−1; mean ± SD) completed a glycogen-lowering exercise session, followed by 4 h of recovery and subsequent TT20km and TT5km. During the first 2 h of recovery, participants ingested either KME (25 g) followed by CHO at a rate of 1.2 g·kg−1·h−1 (KME + CHO) or an iso-energetic placebo (dextrose) followed by CHO (PLAC + CHO). Blood metabolites during recovery and performance during the subsequent two-time trials were measured. In comparison to PLAC + CHO, KME + CHO displayed greater (p < 0.05) blood beta-hydroxybutyrate concentration during the first 2 h, lower (p < 0.05) blood glucose concentrations at 30 and 60 min, as well as greater (p < 0.05) blood insulin concentration 2 h following ingestion. However, no treatment differences (p > 0.05) in power output nor time to complete either time trial were observed vs. PLAC + CHO. These data indicate that the metabolic changes induced by KME + CHO ingestion following glycogen-lowering exercise are insufficient to enhance subsequent endurance time trial performance.
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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 | 0.000 |
| 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) | 0.002 | 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".