Impact of ezetimibe on cholesterol subfractions in dyslipidemic cardiac transplant recipients receiving statin therapy
Bibliographic record
Abstract
BACKGROUND: Ezetimibe decreases cholesterol in cardiac transplant recipients intolerant to statins therapy. The effects of ezetimibe in addition to statins therapy and its relationship with the magnitude of dyslipidemia and statins utilization have not been studied in cardiac transplant recipients. METHODS: The design of this investigation was a retrospective case control study. Twenty-two patients receiving the combination of therapy of statins plus ezetimibe were compared with 43 patients treated with statins only. The endpoints were assessed after three months of follow-up. RESULTS: The addition of ezetimibe decreased low density lipoprotein-cholesterol by 25% compared with a 4% increase in patients receiving statins only. The impact of ezetimibe was similar regardless of the magnitude of dyslipidemia or statins dosage. Ezetimibe increase high density lipoprotein (HDL)-cholesterol only in patients with baseline HDL-cholesterol above 1.3 mM/L (p < 0.05). There was an asymptomatic, but significant increase in creatinine kinase level [+31.4 +/- 8.1 (ezetimibe) vs. + 1.5 +/- 5.0 mM/L (placebo); p = 0.005]. CONCLUSION: Ezetimibe therapy provides a significant reduction in most cholesterol subfractions regardless of the magnitude of dyslipidemia and statins dosage.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".