Coronary revascularization and timing of treatment : comparative effectiveness of PCI and CABG in British Columbia
Bibliographic record
Abstract
Background: In Canada, clinical need, resource allocation, and variation in demand determine how soon diagnosed ischemic heart disease are treated. Therefore, patients who require non-emergency revascularization by coronary artery bypass graft (CABG) surgery or percutaneous coronary intervention (PCI) may find their procedures are delayed during periods of higher demand for cardiac care or reduced supply of hospital services. Research has shown that some patients who undergo CABG have health outcome benefits compared to those who have PCI and that some delays increase mortality. However, these studies did not account for PCI as an alternative treatment in the event of delay, nor did they consider disease progression or repeat revascularization as outcomes. Using health services research methods, I sought to establish if patients who had delayed CABG would have been better off instead undergoing timely PCI. Methods: I constructed a retrospective cohort consisting of 25,520 BC residents 60 years or older who underwent first-time non-emergency revascularization for angiographically-proven, stable left main or multi-vessel ischemic heart disease in British Columbia between January 1, 2001, and December 31, 2016. In three separate analyses, I compared patients who had delayed CABG with those who had timely PCI on the outcomes of 1) mortality, 2) cardiovascular disease progression, and 3) repeat revascularization. To adjust for between-group differences, I used inverse probability of treatment weights calculated from a propensity score model containing information on patient, structure, and process factors. Results: At three years follow-up, I found that patients who underwent delayed CABG had statistically better outcomes than timely PCI patients: lower mortality, slower cardiovascular disease progression, and fewer repeat revascularizations. Differences favouring delayed CABG were established early across all analyses and maintained throughout the study period. Conclusion: This work suggests that non-emergency patients who wish to receive CABG as their revascularization treatment will not see its benefits attenuated by delay and that PCI may not be suitable as an alternative treatment strategy. This dissertation adds to the knowledge of patients who receive revascularization care, physicians who deliver that care, and policymakers who plan for that care.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".