Persistent lipid abnormalities in statin‐treated patients with diabetes mellitus in Europe and Canada: results of the Dyslipidaemia International Study
Bibliographic record
Abstract
AIM: To assess the prevalence of persistent lipid abnormalities in statin-treated patients with diabetes with and without the metabolic syndrome. METHODS: This was a cross-sectional study of 22,063 statin-treated outpatients consecutively recruited by clinicians in Canada and 11 European countries. Patient cardiovascular risk factors, risk level, lipid measurements and lipid-modifying medication regimens were recorded. RESULTS: Of the 20,129 subjects who had documented diabetes and/or metabolic syndrome status, 41% had diabetes (of whom 86.8% also had the metabolic syndrome). Of those with diabetes, 48.1% were not at total cholesterol target compared with 58% of those without diabetes. Amongst those with diabetes, 41.6 and 41.3% of those with and without the metabolic syndrome, respectively, were not at their LDL cholesterol goal relative to 54.2% of those with metabolic syndrome and without diabetes, and 52% of those with neither condition. Twenty per cent of people with diabetes but without the metabolic syndrome were not at the optimal HDL cholesterol level compared with 9% of those with neither condition. Of people with diabetes and the metabolic syndrome, 49.9% were not at optimal triglyceride level relative to 13.5% of people with neither diabetes nor the metabolic syndrome. Simvastatin was the most commonly prescribed statin (>45%) and the most common statin potency was 20-40 mg/day (simvastatin equivalent). Approximately 14% of patients were taking ezetimibe alone or in combination with a statin. CONCLUSIONS: Despite evidence supporting the benefits of lipid modification and international guideline recommendations, statin-treated patients with diabetes had a high prevalence of persistent lipid abnormalities. There is frequently room to optimize therapy through statin dose up-titration and/or addition of other lipid-modifying therapies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".