Use of pharmacokinetics in the coagulation factor treatment of patients with haemophilia
Bibliographic record
Abstract
Dosing decisions for replacement coagulation factors in patients with haemophilia should be made on an individual patient basis, with the required dose dependent on factors including the clinical situation, the severity of the factor deficiency, and the location and extent of bleeding. Moreover, there is considerable variability in the pharmacokinetics of coagulation products that needs to be considered; in particular, with both factor (F) IX and FVIII products, there is considerable inter-patient variability in in vivo recovery and terminal half-life values. In the present report, we provide a practical guide to calculating and applying pharmacokinetic parameters relevant to the optimal dosing of coagulation products. We discuss the conduct of a pharmacokinetic study in an individual patient, how to calculate pharmacokinetic values from raw data and clinical situations where an individual pharmacokinetic study is helpful. We highlight the importance of considering an individual pharmacokinetic study in all patients starting a new coagulation product.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".