Rationale and design of ApoA-I Event Reducing in Ischemic Syndromes II (AEGIS-II): A phase 3, multicenter, double-blind, randomized, placebo-controlled, parallel-group study to investigate the efficacy and safety of CSL112 in subjects after acute myocardial infarction
Bibliographic record
Abstract
Acute myocardial infarction (MI) patients remain at high risk for recurrent events. Cholesterol efflux, mediated by apolipoprotein A-I, removes excess cholesterol from atherosclerotic plaque and transports it to the liver for excretion. Impaired cholesterol efflux is associated with higher cardiovascular (CV) event rates among both patients with stable coronary artery disease and recent MI. CSL112, a novel intravenous formulation of apolipoprotein A-I (human) derived from human plasma, increases cholesterol efflux capacity. AEGIS-II is a phase 3, multicenter, double-blind, randomized, placebo-controlled, parallel-group trial investigating the efficacy and safety of CSL112 compared to placebo among high-risk acute MI participants. Eligibility criteria include age ≥ 18 years with type 1 (spontaneous) MI, evidence of multivessel stable coronary artery disease, and presence of diabetes requiring pharmacotherapy, or ≥2 of the following: age ≥ 65 years, prior MI, or peripheral artery disease. A target sample of 17,400 participants will be randomized 1:1 to receive 4 weekly infusions of CSL112 6 g or placebo, initiated prior to or on the day of discharge and within 5 days of first medical contact. The primary outcome is the time to first occurrence of the composite of CV death, MI, or stroke through 90 days. Key secondary outcomes include the total number of hospitalizations for coronary, cerebral, or peripheral ischemia through 90 days and time to first occurrence of the composite primary outcome through 180 and 365 days. AEGIS-II will be the first trial to formally test whether enhancing cholesterol efflux can reduce the rate of recurrent major adverse CV events.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".