Statin treatment and adherence to national cholesterol guidelines after ischemic stroke
Bibliographic record
Abstract
BACKGROUND: National cholesterol guidelines have defined high vascular risk individuals as those who could potentially benefit most from statin therapy. The authors aimed to determine the rate of statin use, its predictors, and the achievement of national guideline target lipid goals among ischemic stroke survivors. METHODS: The authors abstracted data from the Vitamin Intervention for Stroke Prevention (VISP) study database from the United States and Canada to incorporate into algorithms for initiating statin therapy according to the National Cholesterol Education Program (NCEP) guidelines for high-risk individuals. The authors applied these algorithms to all study subjects. Univariate as well as multivariate associations for target lipid levels and statin implementation were then evaluated utilizing pertinent demographic, clinical, and laboratory data. RESULTS: Of 2,894 subjects in the analysis dataset, 38% were women; 71% were recruited in the United States and 29% in Canada. Of 769 high-risk subjects, 262 (34%) had a low-density lipoprotein (LDL) level > or =130 mg/dL and 124 of these (47%) were not on statin. Among those high-risk persons on statin treatment, only 42% had an LDL < or =100 mg/dL. Subjects in the overall cohort were more likely to be on a statin if they were treated in the United States or had a history of hypertension or coronary artery disease. CONCLUSIONS: Approximately one out of three guideline-eligible high vascular risk ischemic stroke patients in this study had low-density lipoprotein cholesterol concentrations above qualifying levels for pharmacologic therapy, but half of these patients were not taking a statin, and of those receiving statin treatment, less than half were within recommended lipid goals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".