Health-related quality of life outcomes of patients with coronary artery disease treated with cardiac surgery, percutaneous coronary intervention or medical management.
Bibliographic record
Abstract
BACKGROUND: Given the repeated findings of little or no difference in mortality outcomes between percutaneous coronary intervention (PCI) with or without stent and coronary artery bypass graft surgery (CABG), there is a need to assess the health-related quality of life (HRQOL) outcomes associated with revascularization decisions. OBJECTIVE: To compare risk-adjusted HRQOL outcomes by treatment strategy one year following cardiac catheterization. METHODS: Using an inception cohort study design, the sample included all Alberta residents, 18 years of age or older, referred for cardiac catheterization, from January 1, 1996, to December 31, 1998, with two or more diseased coronary vessels at catheterization. Patients received a follow-up questionnaire including the Seattle Angina Questionnaire (SAQ), one year following their index catheterization. The SAQ comprises five dimensional scales measuring exertional capacity, anginal stability, anginal frequency, treatment satisfaction and quality of life. RESULTS: Three thousand three hundred ninety-two (78.1%) patients responded to the follow-up survey. Responders who were revascularized consistently reported significantly better HRQOL compared with responders treated with medical management. Responders undergoing CABG reported significantly better HRQOL in all but one SAQ dimension compared with responders who had either a PCI with or without stent. Responders who had a PCI with stent reported better HRQOL compared with responders who underwent a PCI without a stent. CONCLUSION: The treatment decision to revascularize the coronary vessels, whether with PCI with or without a stent or with CABG, was consistently associated with significantly better HRQOL at one-year follow-up compared with patients treated with medical therapy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".