Alterations in energy balance following exenatide administration
Bibliographic record
Abstract
Exenatide is a medication similar in structure and effect to native glucagon-like peptide-1, an incretin hormone with glucose-lowering properties. The aim of the study was to measure the change in total energy expenditure (TEE) and body composition during exenatide administration and by deduction the relative contributions of energy expenditure and energy intake to exenatide-induced weight loss. Forty-five obese (body mass index, 30-40 kg·m⁻²) subjects were identified. After exclusion criteria application, 28 subjects entered into the study and 18 subjects (12 female, 6 male) completed the study, which consisted of 6 visits over 14 weeks and injection of exenatide for an average of 84 ± 5 days. Respiratory gas analysis and doubly labeled water measurements were performed before initiation of exenatide and after approximately 3 months of exenatide administration. The average weight loss from the beginning of injection period to the end of the study in completed subjects was 2.0 ± 2.8 kg (p = 0.01). Fat mass declined by 1.3 ± 1.8 kg (p = 0.01) while the fat-free mass trended downward but was not significant (0.8 ± 2.2 kg, p = 0.14). There was no change in weight-adjusted TEE (p = 0.20), resting metabolic rate (p = 0.51), or physical activity energy expenditure (p = 0.38) and no change in the unadjusted thermic effect of a meal (p = 0.37). The significant weight loss because of exenatide administration was thus the result of decreasing energy intake. In obese nondiabetic subjects, exenatide administration did not increase TEE and by deduction the significant weight loss and loss of fat mass was due to decreased energy intake.
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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 | 0.001 |
| 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".