The New Face of Hyperlipidemia Management: Proprotein Convertase Subtilisin/Kexin Inhibitors (PCSK-9) and Their Emergent Role As An Alternative To Statin Therapy
Bibliographic record
Abstract
This review analyzes Proprotein Convertase Subtilisin/Kexin 9 inhibitors (PCSK-9), a new medication class that has arisen in the last year to combat hypercholesterolemia. They are targeted towards patients who are unable to achieve acceptable low density lipoprotein (LDL) levels despite maximum statin therapy, as well as those who are unable to tolerate maximum statin therapy due to side effects such as myopathy or myalgia. Two of these medications have been released in the last year: alirocumab (Praluent) and evolocumab (Repatha). This article will overview this medication class, describe their pathophysiology, and analyze the clinical data from the numerous studies and trials done on both of these medications for their efficacy and safety outcomes. Data compiled on this new class of medications support the research that PCSK-9 inhibitors are both a safe and effective means of lowering the LDL levels of resistant or otherwise currently unmanaged hypercholesterolemia patients.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".