Time of coronary revascularization: methodology of a mediation analysis study
Bibliographic record
Abstract
BACKGROUND: The advantage of coronary artery bypass grafting (CABG) over percutaneous coronary intervention (PCI), established in trials, may not be generalizable to populations in which the method of treatment determines the time to treatment. We sought to describe the methodology of a population-based observational study for assessing how changes in time to treatment may affect the comparative effectiveness of these 2 methods of coronary revascularization. METHODS: We propose a framework of causal mediation analysis to compare the outcomes of choosing CABG over PCI, if patients selected for either method waited the same amount of time had they undergone a PCI. We will include patients who underwent a first-time, nonurgent isolated CABG or single-session PCI for multivessel or left main coronary artery disease from January 2001 to December 2016, in British Columbia. We will use absolute risk difference as a measure of the total effect of choosing CABG over PCI and partition it into the direct effect of the treatment choice and the effect mediated by the treatment-specific timing. INTERPRETATION: Understanding how time to treatment mediates the relation between method of revascularization and outcomes will have implications for treatment selection, resource allocation and planning benchmarks. Findings on the benefits and risks of performing PCI or CABG within a certain time will guide multidisciplinary teams in determining the appropriate revascularization method for individual patients.
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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 | 0.204 | 0.257 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".