Dose-finding and pharmacokinetics of therapeutic doses of tinzaparin in pediatric patients with thromboembolic events
Bibliographic record
Abstract
In children, there is an increasing off-label use of low molecular weight heparin (LMWH). However, there is an absence of information on dosing and pharmacokinetics of LMWH over all age groups. The objectives of the current study were to determine i) the once daily dose required to achieve anti-Xa levels of 0.5-1.0 IU/mL, ii) the pharmacokinetics and iii) preliminary safety data using tinzaparin. The study took the form of a single centre open-label Phase II study performed in 35 children requiring anticoagulation for treatment of thromboembolism. Age groups studied were: 0- < 2 months; 2 months- < 1 year; 1- < 5 years; 5- < 10 years; 10-16 years. Both population pharmacokinetic analysis using nonlinear mixed-effect modeling techniques and model-independent pharmacokinetic methods were employed. Results showed a relationship of age and dose requirements, clearance, time to peak anti-Xa level and volume of distribution. Younger children required an increased dose, cleared tinzaparin more rapidly, had anti-Xa levels peak earlier and had an increased volume of distribution. Younger children were more likely to be below target range than older children,with up to 75% of children < 1 year being below the target anti-Xa level. Four recurrences and one major bleed occurred. In conclusion, there is an inverse relationship of age on dose requirements related to volume of distribution, clearance and time to peak anti-Xa. Children < 5 years likely require dose adjustment samples to be drawn 2-3 hours post injection. Infants require anti-Xa levels to be monitored at least twice monthly.
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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 | 0.003 |
| 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 | 0.000 |
| 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".