Estimating the Number of Hospital or Emergency Department Presentations for Stroke in Canada
Bibliographic record
Abstract
BACKGROUND: Although age-standardized stroke occurrence has been decreasing, the absolute number of stroke events globally, and in Canada, is increasing. Stroke surveillance is necessary for health services planning, informing research design, and public health messaging. We used administrative data to estimate the number of stroke events resulting in hospital or emergency department presentation across Canada in the 2017-18 fiscal year. METHODS: Hospitalization data were obtained from the Canadian Institute for Health Information (CIHI) Discharge Abstract Database and the Ministry of Health and Social Services in Quebec. Emergency department data were obtained from the CIHI National Ambulatory Care Reporting System (Alberta and Ontario). Stroke events were identified using ICD-10 coding. Data were linked into episodes of care to account for readmissions and interfacility transfers. Projections for emergency department visits for provinces/territories outside of Alberta and Ontario were generated based upon age and sex-standardized estimates from Alberta and Ontario. RESULTS: In the 2017-18 fiscal year, there were 108,707 stroke events resulting in hospital or emergency department presentation across the country. This was made up of 54,357 events resulting in hospital admission and 54,350 events resulting in only emergency department presentation. The events resulting in only emergency department presentation consisted of 25,941 events observed in Alberta and Ontario and a projection of 28,409 events across the rest of the country. CONCLUSIONS: We estimate a stroke event resulting in hospital or emergency department presentation occurs every 5 minutes in Canada.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".