Statin therapy in Canadian patients with hypercholesterolemia: the Canadian Lipid Study -- Observational (CALIPSO).
Bibliographic record
Abstract
BACKGROUND: Although statins are widely used to reduce low density lipoprotein cholesterol (LDL-C), there is little information about patient profiles, treatment patterns and goal achievement among statin-treated patients in Canada. OBJECTIVES: To assess the profile of statin-treated patients and to determine whether they are achieving recommended targets for LDL-C. METHODS: The Canadian Lipid Study -- Observational (CALIPSO) was a cross-sectional study involving Canadian physicians who were among the top statin prescribers. Each physician enrolled up to 15 patients who were at least 18 years of age with a diagnosis of hyper-cholesterolemia and who had been using a statin for at least eight weeks. Sociodemographics, coronary artery disease (CAD) risk factors, pretreatment and current lipid levels, and history of lipid-lowering therapy were reported for 3721 patients. RESULTS: Sixty-eight per cent of statin-treated patients were at high CAD risk according to the 2003 Canadian guidelines, 46.4% had established cardiovascular disease, 33.9% had diabetes and 59.5% had hypertension. Average LDL-C reductions of 32% (37% for high-risk patients) were initially required to reach goal. At the study visit, patients had been treated for an average of 4.3 years and 24.2% were using a high statin dose. Despite statin therapy, 27.2% of all patients and 36.4% of those at high CAD risk had not achieved LDL-C targets. For 67.4% of these patients, the current therapy was not modified at the study visit. CONCLUSIONS: Despite effective therapies, many treated patients are not achieving recommended LDL-C targets. Strategies should be implemented to promote achievement of lipid treatment goals for high-risk patients, thereby reducing the risk of cardiovascular events and their associated clinical and economic burdens.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".