Steroidogenesis inhibitors in the treatment of nonoperative Cushing’s syndrome – a literature review
Bibliographic record
Abstract
E -Manuscript Preparation, F -literature search, G -Funds CollectionBackground.Cushing's syndrome (Cs) is a disorder caused by excess cortisol production.it is three times more often seen in female than male patients, and overall, it is observed in 2-3 per million/year.in nearly 70% of cases, this is due to a pituitary tumour secreting adrenocorticotropic hormones.the first-line approach to treat these cases is the surgical removal of the tumour.however, in nearly a quarter of cases, this proves ineffective.these patients should be then treated with pharmacotherapy, while untreated Cs may be lethal.the most numerous groups of pharmaceutics in Cs treatment are steroidogenesis inhibitors.Objectives. the purpose of this article is to review the latest publications from 2015 to 2022, which state the medical approach with steroidogenesis inhibitors to inoperative Cs, the advantages, as well potential burdens and adverse effects of this pharmacological treatment.Material and methods.a review of literature regarding adrenal steroidogenesis inhibitors was performed using the PubMed database; the search terms Cushing's syndrome, inoperative, ketoconazole, levoketoconazole, metyrapone, mitotane, etomidate, and osilodrostat were applied. Results and conclusions.this review states the current data pertaining to the effectiveness of hypercortisolaemia treatment, as well as the potential adverse effects of ketoconazole, levoketoconazole, metyrapone, mitotane, etomidate, osilodrostat -steroidogenesis inhibitors currently used in the therapy of nonoperative Cushing's syndrome.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".