Recurrent Pediatric Stroke: The Role of Thrombophilia in a Large International Pediatric Stroke Population
Bibliographic record
Abstract
Objective: Risk factors for arterial ischemic stroke (AIS) in children are multiple and include cardiac disease, vasculopathy, and prothrombotic risk factors (PR). The relevance of these factors to a second AIS event is incompletely understood. Methods: We conducted a multicenter cohort study to assess the rate of symptomatic stroke recurrence following initial AIS, pooling data on recurrent AIS from the databases held in Canada, Germany, and UK. We followed 894 patients aged 1 month to 18 years (median 6 years) at initial AIS for median 35 months. Results: 160 of 894 patients (17.9%) had recurrence from 1 day to 136 months (median 3.1 months) after first AIS. Recurrence was significantly more common in children with (hazard ratio (HR) 2.5, 95% confidence intervals (CI) 1.92-3.5, p < 0.001) compared to children without vasculopathy. After adjusting for vasculopathy, antithrombin deficiency, elevated lipoprotein (a), and the presence of any combined PR were independently associated with recurrence. Recurrence rates calculated per 100 person-years were 10 (95%CI: 3-24) for antithrombin deficiency, 6 (95%CI 4-9) for elevated Lp(a), and 13 (95%CI 7-20) for combined PR. Conclusions: Identifying children at increased for recurrent AIS events is important in intensifying preventative measures. Among 894 Canadian, English and German pediatric stroke patients, 17.9% experienced recurrent AIS at a median of 3.1 months after the index stroke. The presence of more than one prothrombotic risk factor is associated with AIS recurrence in children
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".