Beneficial effect of early initiation of lipid-lowering therapy following renal transplantation
Bibliographic record
Abstract
BACKGROUND: Renal transplant recipients have a significantly reduced life expectancy, largely due to premature cardiovascular disease. The aim of the current analysis was to investigate the importance of time of initiation of therapy after transplantation, on the benefits of statin therapy. METHODS: 2102 renal transplant recipients with total cholesterol levels of 4.0-9.0 mmol/l were randomly assigned to treatment with fluvastatin (n = 1050) or placebo (n = 1052) and followed for a mean time of 5.1 years. The end-points were major cardiac events. The average median time from transplantation to randomization was 4.5 years (range: 0.5-29 years). RESULTS: In patients starting treatment with fluvastatin <4.5 years after renal transplantation, the incidence of cardiac events was 4.6% over 5.1 years vs 9.2% in those on placebo (P = 0.007). Fluvastatin significantly reduced the risk of cardiac death and non-fatal myocardial infarction by 56% [risk ratio (RR): 0.44; 95% confidence interval (95% CI): 0.26-0.74; P = 0.002]. In a more detailed analysis patients were grouped into 2-year intervals (since the last transplantation). The frequency of cardiac death and non-fatal myocardial infarction was reduced by 3.2%, 5.1%, 9.6% and 8.2% with fluvastatin treatment as compared to 6%, 10.4%, 13.4% and 9.6% with placebo when treatment was initiated at 0-2, 2-4, 4-6 and >6 years, respectively. The risk reduction for patients initiating therapy with fluvastatin at years 0-2 (compared with >6 years) following transplantation was 59% (RR: 0.41; 95% CI: 0.18-0.92; P = 0.0328). This is also reflected in total time on renal replacement therapy: in patients in the first quartile (<47 months) fluvastatin use was associated with a risk reduction of 64% compared with 19% for patients in the fourth quartile (>120 months) (P = 0.033). CONCLUSIONS: Our data support an early introduction of fluvastatin therapy in a population of transplant recipients at high risk of premature coronary heart disease.
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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) | 0.001 | 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".