Feasibility and safety of delivering full‐dose anticoagulation therapy in children treated according to Dana‐Farber Cancer Institute acute lymphoblastic leukemia consortium therapy protocols
Bibliographic record
Abstract
Abstract Background The literature is void of an evidence‐based anticoagulation therapy (ACT) management strategy in the context of thrombocytopenia. We examined the impact of thrombocytopenia on low‐molecular‐weight heparin (LMWH) dosing and incidence of bleeding in children with acute lymphoblastic leukemia (ALL) or lymphoblastic lymphoma (LL) who developed thromboembolism (TE) during therapy according to DFCI ALL protocols. Procedure Patient records from our tertiary care center were reviewed for demographics, details of diagnoses and therapy of ALL/LL and TE diagnoses, platelet counts during ACT, LMWH dosing, and bleeding episodes. Results Thirty‐nine TEs were diagnosed in 33 patients [mean age 9 years (range, 2.5–18); 16 males and 31 with ALL] during the study period. A majority (85%) of patients were diagnosed with TE in the consolidation phase with mean time to TE 5.75 months from ALL/LL diagnosis. All patients received LMWH, and the median duration of ACT was 5.9 months (range, 1–11 months). Platelets were measured weekly. On 29 occasions, platelet nadir was <50 × 109/L, and twice it was < 20 × 109/L. One (3%) patient had major bleeding episode while on ACT. Platelet count at the time of bleeding was 222 × 109/L. Ninety‐two procedures [83 lumbar punctures (LPs), 9 central venous line (CVL) insertion/revision] were completed without bleeding complications. Asparaginase was held temporarily with TE diagnosis in 48% of patients; most (88%) patients completed all scheduled doses as per protocol. Conclusions Ability to administer full‐dose LMWH, expected bleeding rate, and completion of asparaginase doses while on ACT suggest full‐dose ACT is feasible and safe in children with ALL/LL who develop TE during DFCI ALL consortium therapy protocols.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".