Breath acetone as a measure of systemic ketosis assessed in a rat model of the ketogenic diet.
Bibliographic record
Abstract
BACKGROUND: The mechanism of a high-fat, low-carbohydrate ketogenic diet (KD) in alleviating drug-resistant epilepsy is unknown but may be related to systemic ketosis induced under this treatment. The need for frequent measurement of systemic ketosis, which is essential for improving maintenance of the KD in patients and for studying mechanism of the KD action, has prompted us to validate the breath acetone test as a fast, reliable, and noninvasive tool for ketosis assessment. METHODS: A rat model of the KD that allowed frequent blood sampling was used to investigate how well breath acetone reflects plasma beta-hydroxybutyrate (beta-HBA), the most commonly measured ketone body. Rat pups (20 days of age) were introduced to and maintained on a KD or control diet for 33 days. During this period, breath acetone, plasma beta-HBA, blood glucose, and body weight were measured approximately every 4th day. A correlational analysis of breath acetone and plasma beta-HBA was conducted. RESULTS: Breath acetone was found to be a significant predictor of plasma beta-HBA over a clinically relevant range of beta-HBA concentrations (r(2) = 0.75; P <0.001). We have proposed a general formula that allows the value of plasma beta-HBA to be estimated based on breath acetone measurement. CONCLUSIONS: Breath acetone is an accurate measure of mild to moderate systemic ketosis. The noninvasive nature of this test will be useful for day-to-day implementation of the KD, searching for better forms of this diet, and understanding the role of ketosis in the mechanism of the KD action.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".