Is a glucocorticoid antagonist a potential treatment alternative for antipsychotic-induced weight gain?
Bibliographic record
Abstract
Objective: To evaluate the efficacy and safety of mifepristone as a new treatment modality for antipsychotic-induced weight gain. Methods: We searched databases up to March 2021, for the published English-language literature including a Medical Subject Heading “Mifepristone,” “Receptors, Glucocorticoid,” “Weight gain,” “Overweight,” “Obesity,” “Body Weight Change,” “Antipsychotics Agents,” “Glucocorticoid Receptor Blocker,” “Glucocorticoid Receptor antagonist.” We identified two clinical and four preclinical studies utilizing mifepristone as a treatment modality. Results: The results of the olanzapine clinical trial showed that mean increase in weight from baseline to day 14 was greater in the olanzapine with the placebo group (3.2 ± 0.9 kg) than the olanzapine with mifepristone group (2.0 ± 1.2 kg) and the mifepristone with placebo (2.0 ± 0.7 kg), and a similar effect was observed in the risperidone with mifepristone clinical trial. Conclusions: Mifepristone shows potential in the management of AIWG. Glucocorticoid antagonists can be a viable alternative to curb this side effect. Large-scale clinical studies are warranted to determine the medication's safety and efficacy based on this mechanism of 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".