Effect of Socioeconomic Status on Treatment and Mortality After Stroke
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Socioeconomic status is associated with increased mortality from ischemic heart disease. We undertook a study to determine whether a similar association exists between socioeconomic status and stroke mortality. METHODS: We linked hospital discharge abstracts and vital-status data for all patients with acute stroke admitted to hospitals in Ontario between April 1994 and March 1997. Socioeconomic status for each patient was inferred on the basis of median neighborhood income. We determined the risk of death at 30 days and 1 year; secondary analyses compared the use of medications, inpatient rehabilitation services, and carotid endarterectomy by socioeconomic status. We used multivariate analyses to adjust for age, sex, stroke type, comorbid conditions, and hospital and physician characteristics. RESULTS: The study sample consisted of 38 945 patients. Each $10 000 increase in median neighborhood income was associated with a 9% reduction in the hazard of death at 30 days (adjusted hazard ratio 0.91, 95% CI 0.87 to 0.96) and a 5% reduction in the hazard of death at 1 year (adjusted hazard ratio 0.95, 95% CI 0.92 to 0.99). Patients in the lowest income quintile were less likely than those in the highest to receive in-hospital physiotherapy (58% versus 61%, P<0.001), occupational therapy (36% versus 47%, P<0.001), and speech pathology (21% versus 28%, P<0.001). There were no differences in the use of medications or carotid endarterectomy based on socioeconomic status. Waiting times for carotid surgery, however, were significantly longer in the lowest income quintile than the highest (90 days versus 60 days, P=0.002). CONCLUSIONS: Socioeconomic status affects mortality and access to some health services after stroke, even in a country with a universal health insurance program. Understanding and reducing these socioeconomic disparities should be a priority for future research.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it