Lp(a) apheresis for the treatment of severe CHD patients with Lp(a) hyperlipidemia
Bibliographic record
Abstract
Objectives. To demonstrate the effectiveness of the specific lipoprotein(a)[Lp(a)] removal with immunosorption columns for treatment of severe CHD patients with elevated (more than 30 mg/dL) Lp(a) level. Methods. The following inclusion criteria were used for the recruitment of patients: age – under 55; coronary atherosclerosis documented by angiography; Lp(a) greater than 60 mg/dl; normal total and LDL cholesterol; clinically apparent progression of the CHD. Specific removal of Lp(a) from plasma was carried out with immunosorbtion columns ‘Lp(a) Lipopak’ contained specific antibodies against human Lp(a). Results. During last 10 years more than 1200 Lp(a) apheresis procedures have been carried out for ten severe CHD patients with 2–3 vessels disease in Moscow, Russia and Ludenscheid, Germany with Lp(a) Lipopak columns (POCARD Ltd, Russia). The Lp(a) level was reduced on the average on 75–85%, other parameters are practically constant during one procedure and duting all period of treatment. Our experience with Lp(a) Lipopak columns has shown that the specific removal of Lp(a) from the patient's plasma to 30 mg/dL or lower by weekly Lp(a) apheresis resulted in a significant improvement in the patient's health status and quality of life. After numerous Lp(a) apheresis procedures the progression of atherosclerosis was stopped in all cases, while some segments of coronary arteries showed regression of atherosclerotic plaques. Conclusion. We conclude that Lp(a) apheresis could be a very effective therapy for severe CHD patients with elevated Lp(a), and/or Lp(a) and LDL but for whom LDL level could be effectively corrected by lipids lowering drugs.
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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 | 0.000 |
| 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) | 0.000 | 0.000 |
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 teacher head, 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".