Effects of Fluvastatin on Cardiac Events in Renal Transplant Patients: ALERT (Assessment of Lescol(R) in Renal Transplantation) Study Design and Baseline Data
Bibliographic record
Abstract
BACKGROUND: Recent clinical trials of primary and secondary prevention of cardiovascular disease have demonstrated that lowering plasma cholesterol with 3-hydroxy-3-methylglutaryl coenzyme A (HMG CoA) reductase inhibitors ('statins') reduces morbidity and mortality from coronary heart disease in diverse patient populations. STUDY AIMS: The aim of the present ALERT (Assessment of Lescol in Renal Transplantation) study is to determine whether renal transplant recipients would also benefit from statin therapy. ALERT is a multicentre, randomized, double-blind, placebo-controlled trial to assess the effect of fluvastatin in renal transplant recipients with mild-to-moderate hypercholesterolaemia. The primary objective is to investigate the effects of fluvastatin on major adverse cardiac events (MACE). In addition, the effects on cardiovascular and all-cause mortality, as well as renal function, will be addressed. STUDY POPULATION: The study population contains patients with functioning renal allografts of more than 6 months' duration, recruited from 75 centres in Northern Europe and Canada. Patients of both sexes, aged 30-75 years, with a total cholesterol level of 4.0-9.0 mmol/l (155-348 mg/dl) were included, except for those with a history of myocardial infarction, where the upper limit for inclusion was 7.0 mmol/l (270 mg/dl). STUDY DESIGN: A total of 2100 patients were recruited by the end of October 1997 and will be followed for up to 6 years. This report presents the design features of the study (recruitment, follow-up, sample size, data analysis and study organization), along with baseline results. ALERT is the first large-scale prospective, randomized, double-blind study to address the prevention of cardiovascular mortality in renal transplant patients receiving an HMGCoA reductase inhibitor.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".