Socioeconomic status and risk of hemorrhage during warfarin therapy for atrial fibrillation: A population-based study
Bibliographic record
Abstract
BACKGROUND: Among patients taking warfarin, lower socioeconomic status is associated with poorer control of anticoagulation. However, the extent to which socioeconomic status influences the risk of hemorrhage is unknown. We examined the extent to which socioeconomic status influences the risk of hemorrhage in older individuals newly commencing warfarin therapy for atrial fibrillation. METHODS: We conducted a population-based cohort study of individuals 66 years or older with atrial fibrillation who commenced warfarin therapy between April 1, 1997, and November 30th 2011, in Ontario, Canada. We used neighborhood-level income quintiles as a measure of socioeconomic status. The primary outcome was an emergency department visit or hospitalization for hemorrhage, and the secondary outcome was fatal hemorrhage. RESULTS: We studied 166,742 older patients with atrial fibrillation who commenced warfarin therapy. Of these, 16,371 (9.8%) were hospitalized for hemorrhage during a median follow-up of 369 (interquartile range 102-865) days. After multivariable adjustment using Cox proportional hazards regression, we found that those in the lowest-income quintile faced an increased risk of hospitalization for hemorrhage relative to those in the highest quintile (adjusted hazard ratio 1.18, 95% CI 1.12-1.23). Similarly, the risk of fatal hemorrhage (n = 1,802) was increased in the lowest-income relative to the highest-income quintile (adjusted hazard ratio 1.28, 95% CI 1.11-1.48). CONCLUSIONS: Among older individuals receiving warfarin therapy for atrial fibrillation, lower socioeconomic status is a risk factor for hemorrhage and hemorrhage-related mortality. This factor should be carefully considered when initiating and monitoring warfarin therapy.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".