Comparison of Anatomic and Clinical Outcomes in Patients Undergoing Alternative Initial Noninvasive Testing Strategies for the Diagnosis of Stable Coronary Artery Disease
Bibliographic record
Abstract
BACKGROUND: The optimal initial noninvasive diagnostic testing strategy for stable coronary artery disease (CAD) is unknown. Although American guidelines recommend an exercise stress test as the first-line test, European guidelines suggest that stress imaging (myocardial perfusion imaging or stress echocardiography) or coronary computed tomography angiography may be preferable. Understanding the relationship between the initial strategy and downstream yield of obstructive CAD and major adverse cardiac events may provide insight as to the optimal strategy. METHODS AND RESULTS: We conducted a population-based retrospective cohort study of adults in Ontario, Canada, using health administrative and clinical data. The relationship between the initial testing strategy and obstructive CAD on invasive angiography was examined. Patients were then followed from their angiogram onward to determine whether they developed a composite end point of major adverse cardiac events. After adjusting for covariates, patients with initial myocardial perfusion imaging (odds ratio: 0.92; 95% confidence interval, 0.85, 1.00), coronary computed tomography angiography (odds ratio: 1.51; 95% confidence interval, 0.91, 2.49), or stress echo (odds ratio: 0.95; 95% confidence interval, 0.84, 1.08) did not a have significantly different yield of obstructive CAD compared with those with an initial exercise stress test. Furthermore, there was no significant difference in downstream major adverse cardiac events after invasive angiography among the 4 initial testing strategies after adjusting for clinically relevant covariates. CONCLUSIONS: Our study found no evidence to suggest significant differences in either yield of obstructive CAD or downstream major adverse cardiac events in patients undergoing an initial noninvasive testing strategy with stress or anatomical imaging compared with those undergoing an initial exercise stress test.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".