Weight‐related dosing, timing and monitoring hydrocortisone replacement therapy in patients with adrenal insufficiency
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to examine the variables determining hydrocortisone (HC) disposition in patients with adrenal insufficiency and to develop practical protocols for individualized prescribing and monitoring of HC treatment. DESIGN AND PATIENTS: Serum cortisol profiles were measured in 20 cortisol-insufficient patients (09.00 h cortisol < 50 nmol/l) given oral HC as either a fixed or 'body surface area-adjusted' dose in the fasted or fed state. Endogenous cortisol levels were measured in healthy subjects. Pharmacokinetic analysis was performed using P-Pharm software, and computer simulations were used to assess the likely population distribution of the data. RESULTS: Body weight was the most important predictor of HC clearance. A fixed 10-mg HC dose overexposed patients to cortisol by 6.3%, whereas weight-adjusted dosing decreased interpatient variability in maximum cortisol concentration from 31 to 7%, decreased area under the curve (AUC) from 50 to 22% (P < 0.05), and reduced overexposure to < 5%. Food taken before HC delayed its absorption. Serum cortisol measured 4 h after HC predicted cortisol AUC (r(2) = 0.78; P < 0.001). CONCLUSIONS: We recommend weight-adjusted HC dosing, thrice daily before food, monitored with a single serum cortisol measurement using a nomogram. This regimen was prospectively examined in 40 cortisol-insufficient patients, 85% of whom opted to remain on the new thrice-daily treatment regimen.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".