Acute Ingestion of Ketone Monoesters and Precursors Do Not Enhance Endurance Exercise Performance: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
There has been much consideration over whether exogenous ketone bodies have the capacity to enhance exercise performance through mechanisms such as altered substrate metabolism, accelerated recovery, or neurocognitive improvements. This systematic review aimed to determine the effects of both ketone precursors and monoesters on endurance exercise performance. A systematic search was conducted in PubMed, SPORTDiscus, and CINAHL for randomized controlled trials investigating endurance performance outcomes in response to ingestion of a ketone supplement compared to a nutritive or nonnutritive control in humans. A meta-analysis was performed to determine the standardized mean difference between interventions using a random-effects model. Hedge's g and 95% confidence intervals (CI) were reported. The search yielded 569 articles, of which eight were included in this review (80 participants; 77 men and three women). When comparing endurance performance among all studies, no significant differences were found between ketone and control trials (Hedges g = 0.136; 95% CI [-0.195, 0.467]; p = .419). Subanalyses based on type of endurance tests showed no significant differences in time to exhaustion (Hedge's g = -0.002; 95% CI [-0.312, 0.308]; p = .989) or time trial (Hedge's g = 0.057; 95% CI [-0.282, 0.395]; p = .744) values. Based on these findings, exogenous ketone precursors and monoesters do not exert significant improvements on endurance exercise performance. While all studies reported an increase in blood ketone concentrations after ingestion, ketone monoesters appear to be more effective at raising concentrations than precursors.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".