Use of non‐LDL‐C lipid‐lowering medications in patients with type 2 diabetes
Bibliographic record
Abstract
BACKGROUND: A number of non-low-density lipoprotein cholesterol lipid abnormalities are associated with type 2 diabetes and insulin resistance, which may lead practitioners to use medications targeting these abnormal lipid fractions despite a lack of evidence or guideline recommendations. METHODS AND RESULTS: Among 382 921 US patients with type 2 diabetes (69% with cardiovascular disease, 76% on a statin), 95 995 (26%) were on some nonstatin lipid-lowering medication-19 265 (5%) on niacin, 32 919 (9%) on a fibrate and 69 513 (18%) on fish oil. Use of all three medications was stable over time and higher in patients with cardiovascular disease and with higher triglyceride levels, although even among patients with triglyceride levels <2.3 mmol/L, 6% were on a fibrate and 17% were on fish oil. CONCLUSION: As clinical trials demonstrate little to no cardiovascular benefit from taking these medications, greater attention is needed to focus the use of lipid-lowering medications to those with proven benefit.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".