A randomized placebo-controlled double-blind trial of lipid-lowering strategies in patients with renal insufficiency: diet modification with or without fenofibrate.
Bibliographic record
Abstract
BACKGROUND: Renal insufficiency is characterized by lipoprotein abnormalities including elevated triglyceride levels. PATIENTS AND METHODS: The safety and efficacy of micronized fenofibrate as a treatment for dyslipidemia in patients with progressive renal insufficiency was evaluated in a randomized, placebo-controlled double-blind study comparing fenofibrate and dietary modification to dietary modification alone. Patients were evaluated following a 3-month pre-randomization period of dietary counseling. Twenty-eight patients with moderate renal insufficiency and triglyceride levels 2.3 mmol/l or LDL/HDL ratio 5 were randomized to placebo (n = 12) or fenofibrate (n = 16) therapy. Treatment and dietary counseling continued for 6 months. RESULTS: Ten of 16 patients (63%) treated with fenofibrate achieved a 30% reduction in triglyceride levels or LDL/HDL ratio reduction < 5 compared to 2 of 17% in the placebo group (p = 0.015). Triglyceride levels were significantly reduced in the fenofibrate group (-31%) versus placebo (+1.3%, p = 0.003). In compliant patients (n = 25) there was also a significantly greater increase in HDL cholesterol levels in the fenofibrate group (+19.9%) compared to placebo (-4.7%, p = 0.001). Changes in measured creatinine clearance were not significantly different between the groups and there were no serious adverse effects of treatment. CONCLUSION: Fenofibrate therapy combined with dietary modification effectively reduced triglyceride levels in renal insufficiency patients without serious adverse effects.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".