Impact of Apolipoprotein A-I Infusions on Cardiovascular Events Post-MI by Neutrophil-Lymphocyte Ratio and LDL-Cholesterol Levels
Bibliographic record
Abstract
BACKGROUND: The AEGIS-II (ApoA-I Event Reducing in Ischemic Syndromes-II; NCT03473223) trial evaluated CSL112, a human plasma-derived apolipoprotein A-I therapy, for reducing cardiovascular events after acute myocardial infarction (AMI). Given CSL112's potential anti-inflammatory properties, we conducted an exploratory post hoc analysis to determine if its efficacy is influenced by baseline neutrophil-lymphocyte ratio (NLR), a marker of systemic inflammation, and low-density lipoprotein cholesterol (LDL-C). OBJECTIVES: The purpose of this study was to investigate the association of baseline NLR and cardiovascular events and explore whether NLR and LDL-C modify CSL112's efficacy in post-AMI patients. METHODS: A total of 18,219 participants with AMI, multivessel coronary artery disease, and additional cardiovascular risk factors were randomized to 4 weekly infusions of 6 g CSL112 or placebo. The primary endpoint was a composite of cardiovascular death, myocardial infarction, or stroke (major adverse cardiovascular events [MACE]). Cox proportional hazards models evaluated risk by dichotomized baseline NLR (>median vs ≤median). Treatment interactions with NLR and LDL-C (≥100 vs <100 mg/dL) were assessed. RESULTS: = 0.029). CONCLUSIONS: Baseline elevated NLR predicts MACE in post-AMI patients, and CSL112 showed an associated reduction in MACE in patients with elevated NLR and LDL-C ≥100 mg/dL.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".