Association Between Very Low Levels of High‐Density Lipoprotein Cholesterol and Long‐term Outcomes of Patients With Acute Coronary Syndrome Treated Without Revascularization: Insights From the <scp>TRILOGY ACS</scp> Trial
Bibliographic record
Abstract
BACKGROUND: Low levels of high-density lipoprotein cholesterol (HDL-C; <40 mg/dL) are associated with increased risk of cardiovascular events, but it is unclear whether lower thresholds (<30 mg/dL) are associated with increased hazard. HYPOTHESIS: Very low levels of HDL-C may provide prognostic information in acute coronary syndrome (ACS) patients treated medically without revascularization. METHODS: We examined data from 9064/9326 ACS patients enrolled in the TRILOGY ACS trial. Participants were randomized to clopidogrel or prasugrel plus aspirin. Study treatments continued for 6 to 30 months. Relationships between baseline HDL-C and the composite of cardiovascular death, myocardial infarction (MI), or stroke, and individual endpoints of death (cardiovascular and all-cause), MI, and stroke, adjusted for baseline characteristics through 30 months, were analyzed. The HDL-C was evaluated as a dichotomous variable-very low (<30 mg/dL) vs higher (≥30 mg/dL)-and continuously. RESULTS: Median baseline HDL-C was 42 mg/dL (interquartile range, 34-49 mg/dL) with little variation over time. Frequency of the composite endpoint was similar for very low vs higher baseline HDL-C, with no risk difference between groups (hazard ratio [HR]: 1.13, 95% confidence interval [CI]: 0.95-1.34). Similar findings were seen for MI and stroke. However, risks for cardiovascular (HR: 1.42, 95% CI: 1.13-1.78) and all-cause death (HR: 1.36, 95% CI: 1.11-1.67) were higher in patients with very low baseline HDL-C. CONCLUSIONS: Medically managed ACS patients with very low baseline HDL-C levels have higher risk of long-term cardiovascular and all-cause death but similar risks for nonfatal ischemic outcomes vs patients with higher baseline HDL-C.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".