Abstract 51: The Incidence of Perinatal Stroke is 1:1200 Live Births: A Population-Based Study in Alberta Canada
Bibliographic record
Abstract
Introduction: Perinatal stroke encompasses six cerebrovascular syndromes which occur between the 20 th week of gestation and the 28 th post-natal day. Morbidity is significant including motor, language, behavioral, and cognitive challenges, as well as epilepsy. Acute presentations include neonatal arterial ischemic stroke (NAIS), neonatal cerebral sinovenous thrombosis (CSVT), and neonatal hemorrhagic stroke (NHS). Delayed presentations include arterial presumed perinatal ischemic stroke (APPIS), periventricular venous infarction (PVI), and presumed perinatal hemorrhagic stroke (PPHS). Inconsistent terminology and lack of population-based cohorts has limited accurate measurement of disease-specific perinatal stroke incidence. Our objective was to define the incidence of the subtypes of perinatal stroke using a population-based cohort. Methods: The Alberta Perinatal Stroke Project is a research cohort established in 2008 in Southern Alberta, Canada (population ~2.1 million). Leveraging universal health care at a single tertiary care pediatric center facilitated true population-based epidemiology. Patients included had neuroimaging-confirmed perinatal stroke. Case acquisition included exhaustive retrospective hospital and ICD code searches (1990-2008) and prospective enrollment from all NICU and neurology/stroke clinics (2008-2018). Live birth rate denominators were determined from the provincial census. Results: The overall incidence of perinatal stroke in Southern Alberta from 2008-2018 was 81 cases per 100,000 live births, or 1 case per approximately 1200 live births. The incidence of NAIS was 31 per 100,000 (~1/3000), APPIS was 11 per 100,000 (~1/9000), PVI was 18 per 100,000 (~1/5500), and CSVT was 10 per 100,000 (~1/9800). The incidence of NAIS increased after implementing prospective case identification, from 8.5 (95% CI 5.3-11.6) per 100,000 to 31 per 100,000 (95% CI 24.4-38.2), p<0.00001, the remainder of stroke subtypes were stable over time. Conclusions: The overall incidence of perinatal stroke in Southern Alberta is 1:1200 live births. Population-based sampling of disease-specific states may explain why this rate is much higher than previous estimates.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".