An Approach to Minimising Risk of Adrenal Insufficiency When Discontinuing Oral Glucocorticoids
Bibliographic record
Abstract
Oral glucocorticoids are commonly used across every field of medicine; however, discontinuing them in patients can be challenging. The risk of acute adrenal crises secondary to glucocorticoid withdrawal can be fatal and arises from chronic suppression of the adrenal glands. Identifying risk factors for adrenal suppression in dermatological patients, such as doses greater than 5 to 7.5 mg of prednisone equivalent, duration of glucocorticoid use greater than 3 weeks, certain medications, and comorbidities, can help risk-stratify patients. The use of adrenal gland testing such as basal cortisol levels and adrenocorticotropic hormone stimulation tests can confirm adrenal suppression in patients. This review article provides an approach that dermatologists can use to minimise the risk of adrenal insufficiency in patients discontinuing glucocorticoids and when it may be appropriate to use adrenal gland testing.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".