Immigration status, ethnicity, and outcomes following ischemic stroke
Bibliographic record
Abstract
Objective: To assess the association between immigration status and ethnicity and the outcomes of mortality and vascular event recurrence following ischemic stroke in Ontario, Canada. Methods: We conducted a retrospective cohort study using linked administrative and clinical registry-based data from 2002 to 2018 and compared hazards of all-cause mortality and vascular event recurrence in immigrants and long-term residents using inverse probability of treatment weighting accounting for age, sex, income and comorbidities. We stratified analyses by age (≤ 75 and > 75 years) and used interaction terms to evaluate if the association between immigration status and outcomes varied with age or ethnicity. Results: We followed 31,918 adult patients, of whom 2740 (8.6%) were immigrants, for a median follow-up of 5 years. Immigrants had a lower mortality than long-term residents (46.1% vs. 64.5%) which was attenuated after adjustment (hazard ratio 0.94; 95% confidence interval 0.88-1.00), but persisted in those aged under 75 years (HR 0.82; 0.74-0.91). Compared to their respective ethnic long-term resident counterparts, the adjusted hazard of death was higher in South Asian immigrants, similar in Chinese immigrants, and lower in other immigrants (P value for interaction = 0.003). The adjusted hazard of vascular event recurrence (HR 1.01; 0.92-1.11) was similar in immigrants and long-term residents, and this observation persisted across all age and ethnic groups. Conclusions: Long-term mortality following ischemic stroke is lower in immigrants and long-term residents, but is similar after adjustment of baseline characteristics, and it is modified by age at the time of stroke and by ethnicity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".