Effect of hyperhydration on the pharmacokinetics and detection of orally administered budesonide in doping control analysis
Bibliographic record
Abstract
The aim of the present study was to investigate if hyperhydration could influence the excretion and subsequent detection of budesonide (BDS) and its main metabolites (6β-hydroxy-budesonide and 16α-hydroxy-prednisolone) during doping control analysis by leading to concentrations below the WADA reporting level (30 ng/mL). The influence of hyperhydration on the plasma and urinary pharmacokinetic (PK) profiles of BDS and metabolites was also examined. Seven healthy physically active non-smoking Caucasian males participated in a 15-day clinical study. BDS was administered orally at a single dose of 9 mg on Days 1, 7, and 13. Hyperhydration was applied in the morning on two consecutive days, that is, 0 and 24 hours after first fluid ingestion. Water and a commercial sports drink were used as hyperhydration agents (20 mL/kg body weight). Results showed no significant difference (P > 0.05, 95% CI) on plasma or urinary PK parameters under hyperhydration conditions for all the analytes. However, significant differences (P < 0.05, 95% CI) due to hyperhydration were observed on the urinary concentrations of BDS and metabolites. To compensate the dilution effect due to hyperhydration, different adjustment methods were applied based on specific gravity, urinary flow rate, and creatinine. All the applied methods were able to adjust the concentration values close to the baseline ones for each analyte; however, specific gravity was the optimum method in terms of effectiveness and practicability. Furthermore, no masking of the detection sensitivity of BDS or its metabolites was observed due to hyperhydration either in plasma or urine samples.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".