Epidemiology of neonatal stroke: A population-based study
Bibliographic record
Abstract
OBJECTIVE: The goal of this study was to obtain population-based data on the incidence, clinical presentation, management, imaging features, and long-term outcomes of patients with all types of neonatal stroke (NS). METHODS: Full-term neonates with NS born between January 2007 and December 2013 were identified through the Nova Scotia Provincial Perinatal Follow-up Program Database. Perinatal data and neonatal course were reviewed. Neurodevelopmental outcomes were assessed at 18 and 36 months of age using standardized testing. RESULTS: Twenty-nine neonates with NS were identified during the study period, giving an incidence of 47 per 100,000 live births in Nova Scotia. Arterial ischemic stroke was the most common stroke type (76%), followed by neonatal hemorrhagic stroke (17%), then cerebral sinovenous thrombosis (7%). The majority of neonates presented with seizures (86%) on the first day of life (76%). At 36 months of age, 23 (79%) of the children had a normal outcome, while 3 (10%) were diagnosed with cerebral palsy (2 with neonatal arterial stroke and one with neonatal hemorrhagic stroke) and 3 (10%) had recurrent seizures (1 patient from each stroke subtype group). CONCLUSION: The incidence of NS in Nova Scotia is higher than what has been reported internationally in the literature. However, the neurodevelopmental outcomes at 3 years of age are better. Further studies are required to better understand the reasons for these findings.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".