Epidemiology and clinical risk factors predisposing to thromboembolism in children with cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: The prevalence and risk factors for thromboembolism (TE) in children with cancer are largely unknown. This retrospective cohort study aims to determine the epidemiology of TE and to identify potential risk factors for TE in children with cancer. METHODS: We used logistic regression to determine the association of age (<10 years vs. > or =10 years), gender, type of cancer, presence or absence of intra-thoracic disease (mediastinal mass or any primary or metastatic pulmonary disease), type of central venous line (CVL) and CVL-dysfunction (difficulty of blood draw, infusion or documented CVL infection) on the risk of developing TE. RESULTS: Fifty-seven of 726 patients [7.9%; 95% confidence intervals (CI); 6.0,10.0] developed TE; children with brain tumors (n = 201) had significantly lower prevalence of TE (0.5%; P < 0.001). Older patients had increased risk of developing TE compared to younger patients [Odds ratios (OR) 1.8; 95% CI; 1.0,3.2; P = 0.036]. Children with acute lymphoblastic leukemia (ALL) (OR 4.6; 95% CI; 1.8, 12.3; P = 0.002), lymphoma (OR 3.8; 95% CI; 1.3, 11.1; P = 0.016), and sarcoma (OR 4.3; 95% CI; 1.4, 13.3; P = 0.012) had an increased risk of TE. Subgroup analyses showed that patients with CVL-dysfunction and intra-thoracic disease had a higher prevalence of TE compared to those without CVL-dysfunction (22.8% vs. 8.8%; 95% CI; 4.0, 24.3; P = 0.006) and intra-thoracic disease (18.0% vs. 6.1%; 95% CI; 2.4, 21.4; P = 0.02). CONCLUSIONS: TE is common in children with cancer. Age and type of cancer are independent risk factors for TE in children with non-CNS cancers. CVL-dysfunction and intra-thoracic disease are significantly associated with the diagnosis of TE.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it