Anticoagulant Effects of Dabigatran on Coagulation Laboratory Parameters in Pediatric Patients: Combined Data from Five Pediatric Clinical Trials
Bibliographic record
Abstract
BACKGROUND: Dabigatran etexilate, a direct oral thrombin inhibitor, is approved to treat venous thromboembolism (VTE) in both adults and children. OBJECTIVES: This population analysis characterized relationships between dabigatran total plasma concentrations and coagulation laboratory parameters (activated partial thromboplastin time [aPTT]; diluted thrombin time [dTT]; ecarin clotting time [ECT]). METHODS: = 1,978). Population models were fitted using nonlinear mixed-effects modeling. Covariates (e.g., sex, age) were assessed on baseline and drug-effect parameters, using a stepwise covariate model-building procedure. RESULTS: Overall, relationships between dabigatran, aPTT, dTT, and ECT were similar in children and adults. For children aged <6 months, a higher proportion of baseline samples were outside or close to the upper aPTT and ECT adult ranges. No age-related differences were detected for dTT. With increasing dabigatran concentration, aPTT rose nonlinearly (half the maximum effect at 368 ng/mL dabigatran) while dTT and ECT increased linearly (0.37 and 0.73% change per ng/mL dabigatran, respectively). Mean baseline aPTT (45 vs. 36 seconds) and ECT (40 vs. 36 seconds) were slightly increased for those aged <6 months versus older children. CONCLUSION: The similar relationships of laboratory parameters observed across pediatric age groups suggests that developmental changes in the hemostatic system may have little effect on response to dabigatran.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".