Systemic thromboembolism in children
Bibliographic record
Abstract
Thromboembolism (TE) has recently been recognized as a clinical entity in children. Determining the clinical characteristics of pediatric TE is an important first step in dealing with this new disorder. The paper summarizes 1776 consecutive children with systemic TE referred to 1-800-NO-CLOTS telephone consultation service. 1-800-NO-CLOTS is a free consultation service for clinicians managing pediatric TE. Patient information was collected immediately using standardized forms. In children with systemic TE, infants under one year of age (47%) including neonates (26%) represented the largest distinct pediatric age group. Age-related differences were seen in TE locations, associated conditions, and risk factors. However, venous TE was the most frequent manifestation (74%). Neonates and children with cardiac disorders were more likely to have an arterial TE than a venous TE Beyond the neonatal period, venous TE associated with a central line is more likely to occur than arterial TE. Children with ALL were 5.7 times more likely to have a venous TE than an arterial TE. TE were infrequent in otherwise healthy children with 90% of children having at least one risk factor. Central catheters were the single most common risk factor associated with TE, present in 2/3 of children. Ultrasound was most frequently employed for diagnosis of TE. Finally, there was marked heterogeneity in treatment of children with TE. In children, neonates form the largest single group with TE. TE usually occur only in the presence of one or more risk factors with catheters being the single most important factor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 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".