Guidelines in the USA, a viewpoint contrary to those guidelines in Europe, Canada, Britain and the International Atherosclerosis Society
Bibliographic record
Abstract
PURPOSE OF REVIEW: Management of dyslipidaemia is crucial for the reduction in the risk of atherosclerotic cardiovascular disease in the population. Optimum control of this risk factor in both primary and secondary care will not only help reduce cardiovascular disease, but also help reduce long-term healthcare costs for hospital stays, clinic visits and morbidity due to a chronic disease. The purpose of this review is to compare the recent American College of Cardiology/American Heart Association 2013 guidelines with those in Europe, Britain, Canada and the International Atherosclerosis Society position paper. RECENT FINDINGS: The American College of Cardiology/American Heart Association Task Force have published new guidelines on the management of LDL cholesterol for the reduction in atherosclerotic cardiovascular disease risk, which are in variance with the European Society of Cardiology/European Atherosclerosis Society and other country guidelines and have significant repercussions in different populations. SUMMARY: Significant variance between the guidelines can make it difficult for healthcare providers to provide standardized care in different countries, and their long-term implications are uncertain.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".