Urgent Clinical Challenges in Children With Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Clinical trials are lacking in pediatric stroke. As a result, physicians caring for children with stroke face significant challenges. The patient characteristics and specific nature of clinical challenges facing practicing clinicians can inform the design of and priorities for developing relevant clinical trials. METHODS: Physicians consulted the 1-800-NOCLOTS toll-free pediatric stroke telephone consultation service on children (birth to 18 years) with ischemic stroke. Pediatric neurologist or hematologists provided telephone consultation and documented caller and patient characteristics, antithrombotic treatments and callers' questions for entry into a computerized database. Children referred from January 1, 1995 to January 1, 2004, comprised the study cohort. RESULTS: Stroke consults were completed on 1065 children located predominantly in the United States (76%). Children had arterial ischemic stroke (AIS; 679; 64%) or cerebral sinovenous thrombosis (CSVT; 386; 36%) and were 54% male and 16% neonates. Risk factors and antithrombotic agents (none, aspirin, warfarin, and heparins) differed by stroke type. In 60% of patients, callers had not initiated antithrombotic therapy. Callers' questions for both stroke types usually concerned treatment selection (83%), but for AIS, questions more frequently (P<0.0001) concerned the selection and interpretation of etiological investigations. CONCLUSIONS: Research is urgently needed in pediatric stroke to provide direction for management in "real-life" settings. Research efforts should address the unique challenges within different stroke types and include observational studies addressing investigation of the child with AIS. For AIS and CSVT, randomized controlled trials investigating the efficacy of antithrombotic treatment are urgently needed.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".