Temporal Trends in the Use of Percutaneous Coronary Intervention and Coronary Artery Bypass Surgery in New York State and Ontario
Bibliographic record
Abstract
BACKGROUND: Healthcare reform initiatives in the United States have rekindled debate about the role of government regulation in the healthcare system. Although New York State (NYS) historically has had twice as many coronary revascularizations performed as Ontario, the relative evolution of coronary revascularization patterns in both jurisdictions over time is unknown. METHODS AND RESULTS: We conducted an observational study comparing the temporal trends of cardiac invasive procedures use in NYS and Ontario using population-based data from 1997 to 2006 stratified by procedure indication. For nonacute myocardial infarction patients, the age- and sex-adjusted rate of percutaneous coronary intervention (PCI) was 2.3 times (95% confidence interval, 2.2 to 2.5) greater in NYS than in Ontario in 2004 to 2006. In contrast, population-based rates of coronary artery bypass grafting among nonacute myocardial infarction patients were not significantly different. For acute myocardial infarction patients, differences in coronary revascularization rates between NYS and Ontario narrowed substantially over time. In 2004 to 2006, the relative ratio was 1.3 times higher for PCI (95% confidence interval, 1.2 to 1.5) and 1.4 times higher (95% confidence interval, 1.1 to 1.8) for coronary artery bypass grafting in NYS relative to Ontario. However, a larger relative gap (relative ratio, 2.0; 95% confidence interval, 1.7 to 2.3) was observed among acute myocardial infarction patients undergoing emergency PCIs in NYS compared with Ontario. CONCLUSIONS: The market-oriented financing approach in NYS is associated with markedly higher rates of PCI procedures for both discretionary indications (eg, PCI in nonacute myocardial infarction patients) and emergent indications (eg, primary PCI) compared with the government-funded single-payer system in Ontario.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.001 | 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".