Apheresis as novel treatment for refractory angina with raised lipoprotein(a): a randomized controlled cross-over trial
Bibliographic record
Abstract
AIMS: To determine the clinical impact of lipoprotein apheresis in patients with refractory angina and raised lipoprotein(a) > 500 mg/L on the primary end point of quantitative myocardial perfusion, as well as secondary end points including atheroma burden, exercise capacity, symptoms, and quality of life. METHODS: We conducted a single-blinded randomized controlled trial in 20 patients with refractory angina and raised lipoprotein(a) > 500 mg/L, with 3 months of blinded weekly lipoprotein apheresis or sham, followed by crossover. The primary endpoint was change in quantitative myocardial perfusion reserve (MPR) assessed by cardiovascular magnetic resonance. Secondary endpoints included measures of atheroma burden, exercise capacity, symptoms and quality of life. RESULTS: The primary endpoint, namely MPR, increased following apheresis (0.47; 95% CI 0.31-0.63) compared with sham (-0.16; 95% CI - 0.33-0.02) yielding a net treatment increase of 0.63 (95% CI 0.37-0.89; P < 0.001 between groups). Improvements with apheresis compared with sham also occurred in atherosclerotic burden as assessed by total carotid wall volume (P < 0.001), exercise capacity by the 6 min walk test (P = 0.001), 4 of 5 domains of the Seattle angina questionnaire (all P < 0.02) and quality of life physical component summary by the short form 36 survey (P = 0.001). CONCLUSION: Lipoprotein apheresis may represent an effective novel treatment for patients with refractory angina and raised lipoprotein(a) improving myocardial perfusion, atheroma burden, exercise capacity and symptoms.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".