The need for national and international registries of patients with elevated lipoprotein(a)
Bibliographic record
Abstract
PURPOSE OF REVIEW: Elevated lipoprotein(a) [Lp(a)] is a genetically determined independent risk factor for atherosclerotic cardiovascular disease (ASCVD). Current guidelines recommend universal testing of Lp(a) once in an individual's lifetime, with risk factor management intensification for those with elevated levels. However, there is a paucity of real-world data about how patients with elevated Lp(a) are managed and about their associated cardiovascular risk. The purpose of this review is to discuss recent progress in the establishment of registries of patients with elevated Lp(a). RECENT FINDINGS: Multiple registries that include patients with elevated Lp(a) have been established in various countries. These studies will provide a snapshot of the global burden of this condition and the current patterns of treatment of this patient population. SUMMARY: Elevated Lp(a) is a common but underdiagnosed risk factor for ASCVD. National and international registries are needed to expand our understanding and improve the treatment of this condition.
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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".