Bibliographic record
Abstract
Loss-of-function variants in PCSK9 (proprotein convertase subtilisin-kexin type 9) are associated with lower lifetime risk of atherosclerotic cardiovascular disease) events. Confirmation of these genetic observations in large, prospective clinical trials in participants with atherosclerotic cardiovascular disease has provided guidance on risk stratification and enhanced our knowledge on hitherto unresolved and contentious issues concerning the efficacy and safety of markedly lowering LDL-C (low-density lipoprotein cholesterol). PCSK9 has a broad repertoire of molecular effects. Furthermore, clinical trials with PCSK9 inhibitors demonstrate that reductions in atherosclerotic cardiovascular disease events are more effective in patients with recent myocardial infarction, multiple myocardial infarctions, multivessel coronary artery disease, and lower extremity arterial disease. The potent LDL-C lowering efficacy of PCSK9 inhibitors provides the opportunity for more aggressive LDL-lowering strategies in high-risk patients with atherosclerotic cardiovascular disease and supports the notion that there is no lower limit for LDL-C. Aggressive LDL-C lowering with fully human PCSK9 monoclonal antibodies has been associated by a safety profile superior to that of other classes of LDL-lowering agents. These clinical trials provide evidence that LDL lowering with PCSK9 inhibitors is an effective therapy for lowering cardiovascular events in high-risk patients with LDL-C levels ≥70 mg/dL on maximally tolerated oral therapies, including statins and ezetimibe.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.010 |
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".