Prior ingestion of a ketone monoester supplement reduces postprandial glycemic responses in young healthy-weight individuals
Bibliographic record
Abstract
The main objective of this study was to determine whether acute ingestion of a ketone monoester (KME) supplement impacted mixed-meal tolerance test (MMTT) glucose area under the curve (AUC). Nineteen healthy young volunteers (10 males/9 females; age, 24.7 ± 4.9 years; body mass index, 22.7 ± 2.4 kg/m2) participated in a double-blind, placebo-controlled crossover study. Following overnight fasting (≥10 h), participants consumed 0.45 mL/kg of a KME supplement or taste-matched placebo followed by an MMTT 15 min later. Blood samples were collected every 15–30 min over 2.5 h. KME supplementation acutely raised β-hydroxybutyrate AUC (590%, P < 0.0001, d = 2.4) and resulted in decreases in blood glucose AUC (−9.4%, P = 0.03, d = 0.56) and nonesterified fatty acid (NEFA) AUC (−27.3%, P = 0.023, d = 0.68) compared with placebo. No differences were found for plasma insulin AUC (P = 0.70) or gastric emptying estimated by co-ingested acetaminophen AUC (P = 0.96) between ketone and placebo. Overall, results indicate that KME supplementation attenuates postprandial glycemic and NEFA responses when taken 15 min prior to a mixed meal in young healthy individuals. Future studies are warranted to investigate whether KME supplementation may benefit individuals with impaired glycemic control. Novelty: Acute ketone monoester supplementation 15 min prior to a mixed meal decreased postprandial glucose and NEFA levels without significantly impacting postprandial insulin or estimates of gastric emptying. Glucose- and NEFA-lowering effects of ketone monoester supplementation are apparently not mediated by changes in insulin release or gastric emptying.
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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) | 0.001 | 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".