Quality of Life After Percutaneous Coronary Intervention Versus Coronary Artery Bypass Grafting
Bibliographic record
Abstract
BACKGROUND: Differences in quality of life (QoL) after coronary artery bypass grafting (CABG) compared with percutaneous coronary intervention (PCI) are not well characterized. We aimed to compare the short- and long-term effects of CABG versus PCI on QoL. METHODS AND RESULTS: We performed a systematic review and meta-analysis of randomized controlled trials comparing CABG versus PCI using the Seattle Angina Questionnaire (SAQ)-Angina Frequency, SAQ-QoL, SAQ-Physical Limitations, EuroQoL-5D, and Short-Form Questionnaire. We calculated mean changes within each group from baseline to 1, 6, 12, and 36 to 60 months (latest follow-up) and the weighted mean differences between groups using inverse-variance methods. A total of 10 760 patients were enrolled in 5 trials. From baseline to 12 months and 36 to 60 months, the mean change in SAQ-Angina Frequency was >22 points (95% CI, 21.0-25.6) after both PCI and CABG. The mean difference in SAQ-Angina Frequency was similar between procedures at 1 month and at 36 to 60 months but favored CABG at 12 months (1.97 [95% CI, 0.68-3.26]). SAQ-QoL favored PCI at 1 month (-2.92 [95% CI, -4.66 to -1.18]) and CABG at 6 (2.50 [95% CI, 1.02-3.97]), 12 (3.30 [95% CI, 1.78-4.82]), and 36 to 60 months (3.17 [95% CI, 0.54 5.80). SAQ-Physical Limitations (-12.61 [95% CI, -16.16 to -9.06]) and EuroQoL-5D (-0.07 [95% CI, -0.08 to -0.07) favored PCI at 1 month. Short-Form Questionnaire-Physical Component favored CABG at 12 months (1.18 [95% CI, 0.46-1.90]). CONCLUSIONS: Both PCI and CABG improved long-term disease-specific and generic QoL.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".