No benefit of HDL mimetic CER-001 on carotid atherosclerosis in patients with genetically determined very low HDL levels
Bibliographic record
Abstract
Background and aims: Infusion of high-density lipoprotein (HDL) mimetics failed to induce regression of atherosclerosis in recent randomized clinical trials. However, patients in these previous trials had normal levels of HDL-cholesterol, which potentially limited efficacy. Patients with very low levels of HDL-cholesterol and impaired cholesterol efflux capacity can be expected to derive the most potential benefit from infusion of HDL mimetics. This randomized clinical trial evaluated the efficacy of infusions of the HDL mimetic CER-001 in patients with genetically determined very low levels of HDL cholesterol. Methods: In this multicenter, randomized clinical trial, we recruited patients with familial hypoalphalipoproteinemia (due to ABCA1 and/or APOA1 loss-of-function variants). Participants were randomized to intravenous infusions of 8 mg/kg CER-001 or placebo (2:1 ratio), comprising 9 weekly infusions followed by infusions every two weeks. Patients underwent repeated 3T-MRI to assess mean vessel wall area and 18 F-FDG PET/CT to quantify arterial wall inflammation. Results: A total of 30 patients with a mean age of 52.7 7.4 years and HDL-cholesterol of 0.35 0.25 mmol/L were recruited. After 24 weeks, the absolute change in mean vessel wall area was not significantly different in the CER-001 group compared with placebo (n = 27; treatment difference: 0.77 mm 2 , p = 0.21). Furthermore, there was no significant difference in carotid arterial wall inflammation (n = 24, treatment difference: 0.10 target-tobackground ratio of the most diseased segment, p = 0.33) after 24 weeks.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".