Acute Effects of Single-Dose Olanzapine on Metabolic, Endocrine, and Inflammatory Markers in Healthy Controls
Bibliographic record
Abstract
Atypical antipsychotics may "directly" influence glucose homeostasis, increasing risk of type 2 diabetes independently of changes in adiposity. Animal models suggest direct effects after even a single dose of certain atypical antipsychotics on glucose dysregulation. Here, we investigated effects of a single-dose olanzapine (OLA) on glucose metabolism in healthy volunteers, thereby minimizing confounding effects of the illness of schizophrenia and adiposity. In a randomized double-blind crossover design, 15 subjects were administered 10 mg of OLA or placebo at 7:00 A.M. on separate study dates. A frequently sampled intravenous glucose tolerance test was initiated 4.25 hours later to assess changes in glucose homeostasis, including an index of insulin sensitivity, disposition index, glucose effectiveness, and acute insulin response to glucose. We also examined effects on cortisol, prolactin, fasting free fatty acids (FFAs), insulin-mediated suppression of FFAs, and adipocytokines (leptin, adiponectin, C-reactive protein, interleukin 6, and tumor necrosis factor α). Complete data for both visits were analyzed for 12 subjects. Olanzapine treatment significantly decreased glucose effectiveness (P = 0.041) and raised fasting glucose over 4.25 hours (P = 0.03) as compared to placebo. Olanzapine was associated with lower serum cortisol (P = 0.003), lower fasting FFA (P = 0.042), and increased prolactin levels (P < 0.0001). We therefore suggest that a single dose of OLA may invoke early changes in some parameters of glucose and lipid metabolism, as well as endocrine indices.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".