A multi-region assessment of population rates of cardiac catheterization and yield of high-risk coronary artery disease
Bibliographic record
Abstract
BACKGROUND: There is variation in cardiac catheterization utilization across jurisdictions. Previous work from Alberta, Canada, showed no evidence of a plateau in the yield of high-risk disease at cardiac catheterization rates as high as 600 per 100,000 population suggesting that the optimal rate is higher. This work aims 1) To determine if a previously demonstrated linear relationship between the yield of high-risk coronary disease and cardiac catheterization rates persists with contemporary data and 2) to explore whether the linear relationship exists in other jurisdictions. METHODS: Detailed clinical information on all patients undergoing cardiac catheterization in 3 Canadian provinces was available through the Alberta Provincial Project for Outcomes Assessment in Coronary Heart (APPROACH) disease and partner initiatives in British Columbia and Nova Scotia. Population rates of catheterization and high-risk coronary disease detection for each health region in these three provinces, and age-adjusted rates produced using direct standardization. A mixed effects regression analysis was performed to assess the relationship between catheterization rate and high-risk coronary disease detection. RESULTS: In the contemporary Alberta data, we found a linear relationship between the population catheterization rate and the high-risk yield. Although the yield was slightly less in time period 2 (2002-2006) than in time period 1(1995-2001), there was no statistical evidence of a plateau. The linear relationship between catheterization rate and high-risk yield was similarly demonstrated in British Columbia and Nova Scotia and appears to extend, without a plateau in yield, to rates over 800 procedures per 100,000 population. CONCLUSIONS: Our study demonstrates a consistent finding, over time and across jurisdictions, of linearly increasing detection of high-risk CAD as population rates of cardiac catheterization increase. This internationally-relevant finding can inform country-level planning of invasive cardiac care services.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| 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".