Abstract 18396: Low Rate of LDL-Goal-Attainment in 57,855 High-Risk-Patients in Europe, Canada, South-Africa, Middle East and China - Results of DYSIS
Bibliographic record
Abstract
Background: Statin treatment is routinely used for secondary prevention world-wide. Little is known about the prevalence of persistent lipid abnormalities under chronic statin treatment for secondary prevention and possible differences in LDL-Cholesterol (LDL-C) goal attainment in clinical practice between countries in different parts of the world. Methods: Between 2008 and 2012, consecutive statin-treated outpatients were enrolled in 26 countries worldwide, (DYSIS = Dyslipidemia International Study; list of countries in table) to assess LDL-C goal attainment for secondary prevention. European Society of Cardiology recommendations were used to classify patient risk, and to define LDL-cholesterol treatment goals. Data were collected under real life conditions in physicians’ offices and hospital outpatient wards. Results: Serum lipid values of 57,885 consecutive statin-treated outpatients were studied in the context of their cardiovascular risk factors, and the potency and composition of their lipid-lowering treatment. In the very-high risk patients only 21.7% did reach the currently recommended LDL-Chol target <70mg/dl with large differences between the countries varying from 9.2% to 44.3%. In the high-risk population the LDL-Chol target <100mg/dl was achieved in 38.0% oft he patients, varying between 16.6% and 66.7% between countries Conclusion: Despite chronic statin treatment, only 21.7% of the very-high-risk patients reached the current recommended LDL-Chol target <70mg/dl in this large multinational cross-sectional trial, highlighting the persistent large gap between guideline recommendations and clinical practice. Further treatment escalations are necessary to reduce the risk of subsequent cardiovascular events.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".