Impact of Rural Residence on Warfarin Use and Clinical Events in Patients with Non-Valvular Atrial Fibrillation: A Canadian Population Based Study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: We studied whether anticoagulant use and outcomes differed between rural versus urban Canadian non-valvular atrial fibrillation (NVAF) patients prior to the introduction of direct oral anticoagulant drugs. METHODS: Retrospective cohort study of 25,284 adult Albertans with NVAF between April 1, 1999 and December 31, 2008. RESULTS: Compared to urban patients, rural patients were older (p = 0.0009) and had more comorbidities but lower bleeding risk at baseline. In the first year after NVAF diagnosis, urban patients were less likely to be hospitalized (aOR 0.82, 95%CI 0.77-0.89) or have an emergency department visit for any reason (aOR 0.61, 95%CI 0.56-0.66) but warfarin dispensation rates (72.2% vs 71.8% at 365 days, p = 0.98) and clinical outcomes were similar: 7.8% died in both groups, 3.2% rural vs. 2.8% urban had a stroke or systemic embolism (SSE) (aOR 0.92, 95%CI 0.77-1.11), and 6.6% vs. 5.7% (aOR 0.93, 95%CI 0.81-1.06) had a bleed. Baseline SSE risk did not impact warfarin dispensation (73.0% in those with high vs. 72.8% in those with low CHADS2 score, p = 0.85) but patients at higher baseline bleeding risk were less likely to be using warfarin (69.2% high vs. 73.6% low HASBLED score, p<0.0001) in the first 365 days after diagnosis. In warfarin users, bleeding was more frequent (7.5% vs 6.2%, aHR 1.51 [95%CI 1.33-1.72]) but death or SSE was less frequent (7.0% vs 18.1%, aHR 0.60 [0.54-0.66]). CONCLUSION: Warfarin use and clinical event rates did not differ between rural and urban NVAF patients in a universal access publically-funded healthcare system.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".