The expanding role of lipoprotein apheresis in the treatment of raised lipoprotein(a) in ischaemic heart disease and refractory angina
Bibliographic record
Abstract
It is increasingly recognised that lipoprotein(a) [Lp(a)], an inherited, genetically-determined form of LDL-cholesterol, is an independent cardiovascular risk factor and predictor of adverse cardiovascular outcomes. Lp(a) is felt to increase cardiovascular risk via its pro-thrombotic effect and by enhancing intimal lipoprotein deposition. Lipoprotein apheresis is currently the most effective treatment for raised Lp(a). There is a growing body of evidence suggesting that aggressively lowering raised Lp(a) may improve cardiovascular and clinical outcomes, although much more research is required in this field. Angina which is refractory to conventional medical therapy and revascularisation, is extremely challenging to manage. Treatment options for such patients remain very limited. We describe the case of a patient with refractory angina and raised lipoprotein(a) in whom aggressive reduction of Lp(a) with lipoprotein apheresis successfully ameliorated the progression of coronary stenosis and provided effective and durable relief of angina symptoms. In our centre, we are currently conducting a prospective, randomised controlled cross-over study of patients with refractory angina and raised Lp(a), randomised to undergoing lipoprotein apheresis or 'sham' apheresis with assessment of myocardial perfusion, carotid atherosclerosis, endothelial vascular function, thrombogenesis, oxidised phospholipids and their antibodies, exercise capacity, angina symptoms and quality of life at the beginning and end of treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".