Trend to efficacy and safety using antithrombin concentrate in prevention of thrombosis in children receiving l-asparaginase for acute lymphoblastic leukemia
Bibliographic record
Abstract
An association has been reported between thrombotic events and the use of L-asparaginase (ASP) in children with acute lymphoblastic leukaemia (ALL). The mechanism for thrombosis is likely related to an acquired antithrombin deficiency. Since a primary prophylaxis using antithrombin concentrates may prevent thrombosis, the PARKAA (Prophylactic Antithrombin replacement in kids with ALL treated with L-asparaginase) study was performed. The objectives of PARKAA were to determine if there was a trend to efficacy and safety of antithrombin treatment as assessed by 1) incidence of thrombosis 2) incidence of bleeding and 3) plasma markers of endogenous thrombin generation as surrogate outcomes for thrombosis. The study was not powered to answer the question of efficacy and safety, but rather to detect a trend. PARKAA was an open, randomised, controlled study in children with ALL being treated with ASP. Children were randomised to receive antithrombin infusions or no antithrombin treatment. All thrombotic events were confirmed using bilateral venography, ultrasound, echocardiography and MRI. The incidence of thrombosis in patients treated with antithrombin was 28% (95% CI 10-46%), compared to 37% (95% CI 24-49%) in the non treated arm. Two minor bleeds occurred in patients in the treated arm, but were not considered to be related to antithrombin. No significant differences were seen in plasma markers by the treatment group. In conclusion, treatment with antithrombin concentrate shows a trend to efficacy and safety. In contrast, there was no difference in surrogate markers for thrombosis. Carefully designed clinical trials are needed to test the efficacy and safety of antithrombin in this population.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".