Perinatal Stroke: A Practical Approach to Diagnosis and Management
Bibliographic record
Abstract
Perinatal stroke is a focal vascular brain injury that occurs from the fetal period to 28 days of postnatal age. With an overall incidence of up to 1 in 1,000 live births, the most focused lifetime risk for stroke occurs near birth. Perinatal stroke can be classified by the timing of diagnosis, vessel involvement, and type of injury. Timing of diagnosis may be in the acute neonatal period or retrospectively after a period of normal development, followed by abnormal neurologic findings, with the injury presumed to have occurred around the time of birth. Strokes may be arterial or venous, ischemic, and/or hemorrhagic. Within these classifications, 6 perinatal stroke diseases are recognizable, based on clinical and radiographic features. Morbidity is high in perinatal stroke, because it accounts for most cases of hemiparetic cerebral palsy, with disability lasting a lifetime. Additional complications include disorders of sensation and vision, language delays, cognitive and learning deficits, epilepsy, and mental health consequences that affect the entire family. Advances in neonatal neurocritical care may afford opportunity to minimize brain injury and improve outcomes. In the chronic timeframe, progress made in neuroimaging and brain mapping is revealing the developmental plasticity that occurs, informing new avenues for neurorehabilitation. This review will summarize the diagnosis and management of each perinatal stroke disease, highlighting their similarities and distinctions and emphasizing a patient- and family-centered approach to management.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".