Impact of Repeated Glucocorticoid Oral Administration on the Urinary Steroid Profile
Bibliographic record
Abstract
The detection of endogenous anabolic androgenic steroids (EAAS) is performed with the Steroidal Module of the Athlete Biological Passport (ABP). Glucocorticoids (GC) could be a confounding factor to the ABP Steroidal Module because they inhibit the hypothalamic-pituitary-adrenal axis, and ABP metabolites have partial adrenal origin. In previous studies, single-dose systemic GC administrations have been shown to reduce the urinary ratios A/T and 5αdiol/E. In this work, the impact of repeated oral doses of GCs on the urinary steroid profile (SP) has been evaluated. The treatments administered consisted of multiple oral administrations of methylprednisolone (12 mg/24 h for 3 days, n = 8) and dexamethasone (2 mg/12 h for 5 days, n = 8). Urine samples were collected before, during, and after the GC treatments, and the SP was measured in all samples using gas chromatography-tandem mass spectrometry. The multiple-dose oral administration of GCs resulted in a treatment-dependent reduction of the excretion rates of some urinary metabolites (5αAdiol, A, and Etio) and the urinary SP ratios A/T and 5αAdiol/E. The T/E ratio was not significantly affected. Overall, although the consumption of GC could result in atypical profiles for A/T and 5αAdiol/E ratios, according to the cost/benefit assessment, GC should not be considered a confounding factor to the urinary SP because misunderstandings would only take place in very specific situations and, in those cases, the analysis by isotope ratio mass spectrometry of the urine triggering the atypical profile would demonstrate the endogenous origin of the SP metabolites.
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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) | 0.000 | 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".