Thromboembolism in children with sarcoma
Bibliographic record
Abstract
BACKGROUND: Thromboembolism (TE) is a common complication and cause of death in adults with cancer. Cancer has been identified as a major risk factor in children with TE. However, the information regarding the epidemiology of TE in children with cancer, especially in association with childhood solid tumors, is scant. OBJECTIVE: To define the prevalence and epidemiology of TE in children with sarcoma. PROCEDURE: Hospital records of children </=18 years of age with sarcoma diagnosed and treated at McMaster Children's Hospital during January 1990 to December 2005 were reviewed for demographic details, details of diagnosis and therapy for sarcoma, and details of diagnosis and management of TE. Statistical analysis was performed using Fisher's exact t-test. RESULTS: Ten of 70 (14.3%; 95% CI; 7.1, 24.7) patients with sarcoma developed symptomatic TE. Patients with CVL-dysfunction (n = 9) were at significantly higher risk for symptomatic TE compared to those without CVL dysfunction (n = 61) (55.5 vs. 8.2%; P = 0.002, 95% CI; 14.2, 80.5). Patients with pulmonary disease (n = 23) had higher prevalence of TE compared to those without pulmonary disease (n = 47) (26 vs.8.5%; P = 0.07, 95% CI; -2.06, 37.2). Older patients, patients with metastatic disease and those with Ewing sarcoma had higher prevalence of TE. CONCLUSIONS: TE is a significant complication in children with sarcoma. Over 50% of patients with CVL dysfunction had symptomatic TE; such patients may warrant careful evaluation for associated TE. Large prospective studies are needed to define the epidemiology and identify risk factors predisposing to TE in children with sarcoma.
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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 | 0.003 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".