Time-varying comparative effectiveness of surgical or percutaneous revascularization on patient-centred outcomes
Bibliographic record
Abstract
BACKGROUND: Little is known about the comparative risks and timing of patient-defined adverse cardiovascular and noncardiovascular events (PACE) after coronary artery revascularization. We investigated comparative risks of PACEs after coronary artery bypass grafting (CABG) or percutaneous coronary intervention (PCI). METHODS: We conducted a retrospective cohort study of patients who underwent isolated index myocardial revascularization procedures between Oct. 1, 2008, and Dec. 31, 2018, in Ontario, Canada. The primary exposure was revascularization by CABG or PCI. The primary outcome was PACE, a composite of postoperative severe stroke, ventilator dependence, new-onset or worsening heart failure, long-term care admission, and new-onset dialysis. We modelled the association of revascularization strategy and PACE using an overlap-weighted, cause-specific hazard model, with death as a competing risk. RESULTS: Of 140 519 patients included in the analysis, 54 018 (38.4%) underwent CABG and 86 501 (61.6%) underwent PCI. The groups were well balanced after overlap weighting. During a median follow-up duration of 4.8 (interquartile range 2.5 to 7.6) years, a total of 22 926 (16.3%) patients experienced PACE, including 9725 (18.0%) in the CABG group and 13 201 (15.3%) in the PCI group. We found no significant between-group difference in the cumulative incidence of PACE over the entire study period (average hazard ratio [HR] 0.97, 95% confidence interval 0.94 to 1.01). However, the HR for PACE varied over time. The HR comparing CABG to PCI was elevated in the first year, reached a minimum of around 0.7 at years 3 and 4, and then rose, favouring PCI again after year 8. INTERPRETATION: The comparative risk of PACE after CABG versus PCI varied significantly over time. These findings provide granular data to support physicians and patients engaged in shared decision-making about revascularization strategies.
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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 | 0.030 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".