Dyslipidemias and HMG-CoA Reductase Inhibitor Prescription in Heart Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: The treatment of dyslipidemias in orthotopic heart transplant (OHT) recipients is not highlighted in the National Cholesterol Education Program Adult Treatment Panel guidelines. Emerging data suggest that hydroxymethylglutaryl-coenzyme A reductase inhibitors (statins) safely reduce the risk of transplant rejection and coronary artery vasculopathy in OHT patients. OBJECTIVE: To assess the proportion of patients from our institution reaching the low-density lipoprotein cholesterol (LDL-C) target of <100 mg/dL, evaluate the impact of statins in reaching this goal, and evaluate the prescribing practice for statins in US OHT centers. METHODS: The management of dyslipidemia of OHT recipients followed at our institution was retrospectively evaluated. In addition, the use of statins in adult OHT centers in the US that performed >or=15 OHTs per year was assessed through a survey. RESULTS: Of the 328 patients from our institution, 58.5% achieved an LDL-C <100 mg/dL. Patients prescribed statins were more likely to reach this goal (p < 0.01). A total of 85.0% of centers responding to the survey use statins as a part of their post-OHT protocol, primarily to reduce coronary artery vasculopathy (70.6%). CONCLUSIONS: Due to the potential for improved outcomes, a large proportion of patients are prescribed a statin. Our results support previous findings that statins are safe and effective in reducing LDL-C in the management of dyslipidemias in OHT recipients. Nonetheless, dyslipidemias are suboptimally managed in many post-OHT patients.
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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".