Angina and left ventricular dysfunction: can we ‘reduce’ it?
Bibliographic record
Abstract
Despite the evolution in pharmacology and devices, recurrent and persistent angina still represent a frequent issue in clinical practice. A 69-year-old Caucasian female patient has history of surgical aortic valve replacement with a bioprosthesis for severe aortic stenosis with subsequent transcatheter valve-in-valve implantation for bioprosthesis degeneration and single coronary artery bypass graft with left internal mammary artery on left anterior descending (LAD). After transcatheter aortic valve implantation, she started to complain angina [Canadian Cardiovascular Society (CCS) Class III], effectively treated with bisoprolol uptitration and ivabradine 5 b.i.d. addition. After 6 months, she had a non-ST segment elevated myocardial infarction with evidence of left main occlusion and good functioning aortic bioprosthesis. A retrograde drug-eluting balloon percutaneous coronary intervention (PCI) on LAD (in-stent restenosis) was performed. However, the patient continued to complain angina (CCS Class II-III), even after further ivabradine increase to 7.5 mg b.i.d. After 4 months, the patient underwent Reducer implantation. After 2 months, angina started to improve and the patient is currently angina free. In the last decades, PCI materials and stents greatly improved. Medical therapy (such as β-blockers) has been shown not only to improve symptoms but also to add a prognostic benefit in patients with reduced ejection fraction (EF). Ivabradine showed additional benefits in patients with angina and reduced EF. However, still a relevant portion of patients complain refractory angina. The COSIRA trial showed that a coronary sinus Reducer was associated with greater angina relief than the sham procedure and could be a further step in angina treatment.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".