Revascularization for ischaemic cardiomyopathy
Bibliographic record
Abstract
PURPOSE OF REVIEW: Coronary artery disease is the most common cause of heart failure and is referred to as 'ischaemic cardiomyopathy'. There are no established guidelines for the role of revascularization in patients with heart failure in the absence of angina. This review evaluates the current state of knowledge on revascularization for the treatment of ischaemic cardiomyopathy. RECENT FINDINGS: A large body of literature has supported the theoretical benefit of revascularization in recruiting hibernating or stunned myocardium. This has been supported by recent registry and population-based studies demonstrating a survival benefit after revascularization in patients with heart failure and coronary artery disease independent of angina. Some studies have suggested that coronary artery bypass grafting may be superior to percutaneous coronary intervention in a select group of patients. To date no randomized clinical trials have addressed the role of revascularization in this patient population. The STICH trial is the first randomized study specifically to assign patients predominantly with heart failure symptoms to surgery versus medical management, and is expected to be completed in 2008. SUMMARY: Despite the lack of level 1 evidence, there is sufficient reasonable evidence lending credence to the concept that revascularization should be considered in patients with ischaemic cardiomyopathy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".