GR.3 Socioeconomical disparities in acute ischemic stroke revascularization interventions in Ontario, Canada
Bibliographic record
Abstract
Background: Lower socioeconomic status is associated with worse outcomes after stroke. We evaluated the differences in acute revascularization treatments in patients with acute ischemic stroke (AIS) who were materially deprived compared to those who were not. Methods: In a population-based cohort study, we used linked administrative data to identify community-dwelling adults hospitalized for AIS between 2017-2022 in Ontario, Canada. The main exposure was neighborhood-level material deprivation quintiles. Multivariable logistic regression was used to obtain the adjusted odds ratio (aOR) of receiving revascularization treatments (thrombolysis or thrombectomy) for patients in each deprivation quintile compared to the least deprived quintile. Results: We identified 57,709 patients (median age 74 years; 45.9% female). Compared to patients in the least deprived quintile, those with higher deprivation were younger and more likely to have hypertension and diabetes, but less likely to have atrial fibrillation. Compared to patients in the least deprived quintile, fewer patients in the very deprived quintile (17.9% vs 19.6%, aOR 0.88, 95%CI [0.82,0.95]) and in the most deprived quintile (16.6% vs 19.6%, 0.77 [0.71,0.83]) received revascularization treatments. Conclusions: Our results suggest disparities in the use of acute ischemic stroke revascularization treatments by socioeconomic status despite access to universal health care.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".