Cerebral sinus venous thrombosis during childhood acute lymphoblastic leukemia therapy: Risk factors and management
Bibliographic record
Abstract
BACKGROUND: Cerebral sinus venous thrombosis (CSVT) is a rare but serious complication of childhood acute lymphoblastic leukemia (ALL) therapy. No available consensus exists regarding its risk factors and appropriate management due to the rarity of cases. PROCEDURES: Out of 209 ALL patients aged 1-21 years treated at the Children's Cancer Center of Lebanon between May 2002 and May 2015, 13 developed CSVT during therapy. Patient characteristics, clinical management, and outcomes were studied. RESULTS: The incidence of CSVT was 6.2% (95% confidence interval [CI]: 3.4-10.4). Using univariate analysis, increased risk of CSVT was observed with age >10 years (odds ratio [OR]: 3.56, 95% CI: 1.13-11.2), T-cell immunophenotype (OR: 4.14, 95% CI: 1.16-14.7), and intermediate/high risk disease (OR: 3.4, 95% CI: 1.03-11.7). The only statistically significant risk factor by multivariate analysis was the treatment as per the intermediate-/high-risk protocol (HR: 15.6, 95% CI: 1.43-171.3). Most cases (77%) occurred in the postinduction phases of treatment while receiving a combination of asparaginase and dexamethasone rather than prednisone. Treatment with low molecular weight heparin (LMWH) for a minimum of 3 months and until significant radiological improvement is observed resulted in 100% survival rate. All but one patient had complete neurological recovery. CONCLUSIONS: CSVT is an important complication of childhood ALL therapy. Postinduction combined asparaginase and dexamethasone intensive treatment for intermediate-/high-risk patients was the most important risk factor. Treatment with LMWH for a minimum of 3 months, and until asparginase therapy is over, with major radiological improvement seems to be effective and feasible.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".