Fluvastatin Prevents Cardiac Death and Myocardial Infarction in Renal Transplant Recipients: Post-Hoc Subgroup Analyses of the ALERT Study
Bibliographic record
Abstract
Renal transplant recipients have a greatly increased risk of premature cardiovascular disease. The ALERT study was a multicenter, randomized, double-blind, placebo-controlled trial of fluvastatin (40-80 mg/day) in 2102 renal transplant recipients followed for 5-6 years. The main study used a composite cardiac end-point including myocardial infarction, cardiac death and cardiac interventions. Although reduced by fluvastatin, this primary end-point failed to achieve statistical significance thus precluding analysis of predefined subgroups. Therefore, in the present survival analysis, we used an alternative primary end-point of cardiac death or definite nonfatal myocardial infarction (as used in other cardiac outcome trials) which was significantly reduced by Fluvastatin therapy and permits subgroup analysis. Fluvastatin reduced LDL-cholesterol by 1 mmol/L compared with placebo, and the incidence of cardiac death or definite myocardial infarction was reduced from 104 to 70 events (RR 0.65; 95% CI 0.48, 0.88; p = 0.005). Fluvastatin use was associated with reduction in cardiac death or nonfatal myocardial infarction, which achieved statistical significance in many subgroups. The subgroups included patients at lower cardiovascular risk, who were younger, nondiabetic, nonsmokers and without pre-existing CVD. These data support the early introduction of statins following renal transplantation.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".