Extended-Release Niacin Versus Fenofibrate in HIV-Infected Participants With Low High-Density Lipoprotein Cholesterol: Effects on Endothelial Function, Lipoproteins, and Inflammation
Bibliographic record
Abstract
BACKGROUND: Low levels of high-density lipoprotein cholesterol (HDL-C) are common in individuals with human immunodeficiency virus (HIV) infection, persist during antiretroviral therapy (ART), and are associated with increased cardiovascular disease (CVD) risk. METHODS: Virologically controlled participants without CVD on stable ART with low HDL-C (men <40 mg/dL, women <50 mg/dL) and triglycerides >150 mg/dL were randomized to receive open-label extended-release niacin 1500 mg/day with aspirin 325 mg/day or fenofibrate 200 mg/day for 24 weeks. The primary endpoint was the week 24 within-arm change in brachial artery flow-mediated dilation (FMD) in participants with complete follow-up scans. RESULTS: Of 99 participants, 74 had complete data (35 niacin, 39 fenofibrate). Median age was 45 years, 77% were male, median CD4(+) count was 561 cells/µL, and brachial FMD was 4.2%. Median HDL-C was 32 mg/dL for men and 38 mg/dL for women, low-density lipoprotein cholesterol was 103 mg/dL, and triglycerides were 232 mg/dL. In men, HDL-C increased a median of 3 mg/dL with niacin and 6.5 mg/dL with fenofibrate (P < .001 for both). In women, HDL-C increased a median of 16 mg/dL with niacin and 8 mg/dL with fenofibrate (P = .08 for both). After 24 weeks, there was no significant change in FMD in either arm; the median (interquartile range) change was +0.6% (-1.6 to 2.3) with niacin (P = .28) and +0.5% (-1.0 to 3.0) with fenofibrate (P = .19). Neither treatment significantly affected C-reactive protein, interleukin 6, or D-dimer levels. CONCLUSIONS: Despite improvements in lipids, niacin or fenofibrate treatment for 24 weeks did not improve endothelial function or inflammatory markers in participants with well-controlled HIV infection and low HDL-C. CLINICAL TRIALS REGISTRATION: NCT01426438.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".