P.092 Health inequity and time from stroke onset to arrival trends: a single-centre experience
Bibliographic record
Abstract
Background: Clinical outcomes following childhood arterial ischaemic stroke (AIS) depend on age at the time of stroke, infarct size and location. However, other important variables including health inequity and stroke onset to arrival times remain inadequately addressed. This study reported trends in health inequity and stroke onset to arrival times along with proximity to a stroke centre in Canada. Methods: Childhood AIS patients (N=234) with stroke onset between 2004-2019 at a Level 2 (comprehensive) stroke centre were included. Measures of material deprivation included household income, education, single-parent families, and housing quality. Patients were stratified into 3 cohorts (by date of stroke onset) and postal codes were categorized as minimal, moderate, or most deprived neighbourhoods. Results: Over the 16-year period, an increasing number of patients arrived from the most deprived neighbourhoods. Although, there was no significant association between material deprivation and stroke onset to arrival time, an increasing number of patients presented within 6 hours of stroke onset (χ2 = 13.8, p = 0.008). Furthermore, most patients arrived from urban neighbourhoods. Conclusions: The faster stroke onset to arrival trend is encouraging, however, material deprivation trends are concerning. Thus, future studies exploring post-stroke outcomes should consider material deprivation, stroke onset to arrival times, and geographical proximity.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".