Treatment‐induced cerebral sinus venous thrombosis in childhood acute lymphoblastic malignancies: New risk factors to consider
Bibliographic record
Abstract
BACKGROUND: Cerebral sinus venous thrombosis (CSVT) is one of the many side effects encountered during acute lymphoblastic leukemia (ALL) therapy. Due to the rarity of cases, lack of data, and consensus management, no recommendations exist to target the population at risk. METHODS: This is a retrospective chart review of 229 consecutive patients diagnosed with ALL with an age range of 1-21 years, treated at the Children's Cancer Center of Lebanon between October 2007 and February 2018. RESULTS: The incidence of CSVT was 10.5%. Using univariate analysis, increased risk of CSVT was observed with male gender, age >10 years, T-cell immunophenotype, intermediate/high-risk disease, maximum triglyceride (TG) level of >615 mg/dl, presence of mediastinal mass, and larger body surface area (BSA). With multivariate analysis, the only statistically significant risk factors were maximum TG level, BSA, presence of mediastinal mass, and risk stratification (intermediate/high risk). CONCLUSION: Our study was able to unveil TG level of >615 mg/dl, mediastinal mass, and a larger BSA as novel risk factors that have not been previously discussed in the literature.
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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 | 0.001 | 0.001 |
| 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".