Bibliographic record
Abstract
In patients with chronic stable angina, the factors influencing the choice of coronary revascularisation therapy (percutaneous coronary intervention or coronary artery bypass surgery) are varied and complex. The severity of symptoms, lifestyle, extent of objective ischaemia, and underlying risks must be weighed against the benefits of revascularisation and the patient's preference, as well as local availability and expertise. Evidence from randomised trials and large revascularisation registers can guide these decisions, but the past decade has seen rapid change in medical treatment, bypass surgery, and percutaneous intervention. Therefore, thought must be given to whether older data still apply to contemporary practice. View this table: Major factors influencing risks and benefits of coronary revascularisation Top: Diagrams of saphenous vein and left internal mammary artery grafts for coronary artery bypass surgery. Bottom: Three completed grafts—(1) left internal mammary artery (LIMA) to left anterior descending artery (LAD), and saphenous vein grafts (SVG) to (2) diagonal artery (DG) and (3) obtuse marginal artery (OM) Patients with chronic stable angina have an average annual mortality of 2-3%, only twice that of age matched controls, and this relatively benign prognosis is an important consideration when determining the merits of revascularisation treatment. Certain patients, however, are at much higher risk. Predictors include poor exercise capacity with easily inducible ischaemia or a poor haemodynamic response to exercise, angina of recent onset, previous myocardial infarction, impaired left ventricular function, and the number of coronary vessels with significant stenoses, especially when disease affects the left main stem or proximal left anterior descending artery. Although the potential benefits of revascularisation must be weighed against adverse factors, those most at risk may have the most to gain. ### Medical treatment Anti-ischaemic drugs improve symptoms and quality of life, but have not been shown to reduce mortality or myocardial infarction. βblockers may improve survival in hypertension, in heart failure, and …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".