Adrenal suppression and Cushing's syndrome secondary to an interaction between ritonavir and fluticasone: a review of the literature
Bibliographic record
Abstract
OBJECTIVE: The purpose of this article is to provide a systematic overview of the literature on adrenal suppression and Cushing's syndrome secondary to an interaction between inhaled/intranasal fluticasone and ritonavir. The clinical presentation, diagnosis and management will be discussed. METHODS: A literature search using Medline and EMBASE and a search of abstracts of the three previous years of major HIV-related conferences were carried out. RESULTS: There were 25 cases (15 adult and 10 paediatric) of significant adrenal suppression secondary to an interaction between ritonavir and inhaled fluticasone, and three cases involving ritonavir and intranasal fluticasone. Cases with other steroids were not reported; however, there were cases of adrenal suppression with itraconazole [also a potent cytochrome p (CYP) 3A4 inhibitor] and inhaled budesonide. Clinicians need to differentiate between antiretroviral-induced lipodystrophy syndrome and iatrogenic Cushing's syndrome secondary to glucocorticoid use. Long-term fluticasone and ritonavir should be avoided. If ritonavir is required, another inhaled steroid such as low-dose budesonide or beclomethasone can be used cautiously. Upon discontinuation of inhaled corticosteroids, close monitoring for symptoms of adrenal insufficiency is warranted. The need for steroid replacement therapy at physiological doses should be assessed. CONCLUSIONS: The combination of ritonavir and fluticasone should be avoided. Budesonide, beclomethasone, triamcinolone and flunisolide appear to be safer options.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".