Ethnicity based differences in statin use and hypercholesterolemia control among patients with premature coronary artery disease-results of I-PAD study
Bibliographic record
Abstract
Background: Statins use is the most important treatment for high LDL cholesterol in patients with premature coronary artery disease (CAD). Previous reports have shown racial and gender differences in statin use in the general population, but this wasn't studied in premature CAD based on different ethnicities. Methods and results: Our study includes 1917 men and women with confirmed diagnosis of premature CAD. Logistic regression model was used to evaluate the high LDL cholesterol control in the groups and the OR with 95% confidence interval (CI) was reported as the effect size. After adjustment for confounders, the odds of controlling LDL in women taking Lovastatin, Rosuvastatin, and Simvastatin were 0.27 (0.03, 0.45) lower in comparison with men. Also, in participant who took 3 types of statins, the odds of controlling LDL were significantly different between Lor and Arab compared with Fars ethnicity. After adjustment to all confounders (full model), the odds of controlling LDL were lower for Gilak in Lovastatin, Rosuvastatin, and Simvastatin by 0.64 (0.47, 0.75); 0.61 (0.43, 0.73); 0.63 (0.46, 0.74) respectively and higher for Arab in Lovastatin, Rosuvastatin, and Simvastatin by 4.63 (18.28, 0.73); 4.67 (17.47, 0.74); 4.55 (17.03, 0.71) respectively compared to Fars. Conclusions: Major differences in different gender and ethnicities may have had led to disparities in statin use and LDL control. Awareness of the statins impact on high LDL cholesterol based on different ethnicities can help health decision-makers to close the observed gaps in statin use and control LDL to prevent CAD problems.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".