Comparison of the anticoagulant effect of a direct thrombin inhibitor and a low molecular weight heparin in an acquired antithrombin deficiency in children with acute lymphoblastic leukaemia treated with <scp>l</scp>‐asparaginase: an <i>in vitro</i> study
Bibliographic record
Abstract
Thrombosis occurs in 37% of children with acute lymphoblastic leukaemia (ALL) and is related to an L-asparaginase-induced acquired antithrombin (AT) deficiency. The incidence dictates the need for anticoagulant prophylaxis. Direct thrombin inhibitors (DTI) are independent of AT for effect and may thus have advantages in this population. The objective of this study was to determine the interaction of an AT deficiency with the anticoagulant effects of a DTI and a low molecular weight heparin (LMWH). Plasma samples from children with ALL were pooled (mean AT 0.53 U/ml). LMWH 0.3 and 0.7 U/ml or melagatran 0.3 and 0.5 micromol/l were added to the pools, then divided and AT was added back to one aliquot. In additional experiments, AT was added to AT immuno-depleted plasma. Endogenous thrombin generation capacity (ETGC) was assessed by the continuous method. In plasma with LMWH, there was a 66-88% decrease in ETGC in AT-normalised samples compared with neat. Conversely, no significant difference in ETGC with or without AT added for melagatran was seen. Experiments with AT-depleted plasma showed no effect of AT level on anticoagulant activity of DTI, but a significant relationship for LMWH. By contrast to LMWH, DTI provides a consistent anticoagulant response independent of AT levels in children with AT deficiency.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".