Abstract 14016: Marked Geographic Variation in Atrial Fibrillation Ablation Rates in a Universal Single Payer Health Care System
Bibliographic record
Abstract
Introduction: Atrial fibrillation (AF) ablation is increasingly commonly performed for patients with symptomatic AF. In Canada, AF ablation occurs at specialized electrophysiology centers (“EP centers”), which are clustered in major urban centers. Hypothesis: People with AF who live closer to an EP center are more likely to undergo an AF ablation. Methods: Data was compiled from Ontario Health datasets (e.g. emergency department (ED) visits, hospital discharges, physician billing) and Canadian census data for people presenting to an ED in Ontario, Canada with a new diagnosis of AF between 2007-16. The primary outcome was ablation within one year of the index ED visit. Secondary outcomes include ablation at two years. Multivariate logistic regression was conducted to assess the relationship between distance to EP centers and likelihood of ablation. We also studied ablation frequency in relation to material deprivation (e.g. income, housing quality and education). Geospatial analyses were performed using QGIS. Results: Of the 135,681 people with newly diagnosed AF, 3911 (2.9%) had an ablation within one year of AF diagnosis and 5827 (4.3%) within two. There was a significant inverse relationship between a doubling of distance to the closest EP center and ablation within one year (OR: 0.93, 95% CI: 0.91-0.94), and two years (OR: 0.95, 95% CI: 0.94-0.97). Higher deprivation (measured in standard deviations from the mean) was associated with significantly less ablation at one year (OR: 0.89, 95% CI: 0.85-0.92). There was wide regional variation with relatively low rates near the largest urban center (Figure 1). Conclusions: Living further from an EP center and greater material deprivation are associated with lower AF ablation rates. Ablation rates vary by region, with the highest rates not consistently observed in areas most concentrated with EP centers. Figure 1. Age and sex adjusted AF ablation rates per 100,000 patients within a year of AF diagnosis in Ontario, Canada
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".