Cross-Sectional Study of Patients With Onset of Acute Coronary Syndrome During Statin Therapy
Bibliographic record
Abstract
BACKGROUND: Although statin therapy significantly reduces cardiovascular morbidity and mortality, atherosclerotic plaque progresses in some patients taking statins. This study investigated the factors associated with onset of acute coronary syndrome (ACS) early after the initiation of statin therapy. METHODS: Consecutive patients taking statins who presented with ACS (n = 64) were divided into < 1-year and > 1-year groups based on the duration of statin therapy. Patient characteristics, coronary risk factors, lesion locations, and percutaneous intervention procedures were compared between groups. RESULTS: The < 1-year group was significantly younger (57.6 ± 11.9 years vs. 76.6 ± 9.1 years, P < 0.01), had significantly higher body mass index (27.22 ± 4.20 kg/m(2) vs. 24.60 ± 4.65 kg/m(2), P < 0.05), higher proportion of males (94% vs. 70%, P < 0.05), higher proportion of current smokers (61% vs. 17%, P < 0.01), and lower proportions taking aspirin and calcium antagonists (both 17% vs. 57%, P < 0.05) than the > 1-year group. In the < 1-year group, there were significant correlations between the low-density lipoprotein cholesterol (LDL-C) and triglyceride (TG) levels (r = 0.649, P = 0.004) and between the TG and hemoglobin (Hb)A1c levels (r = 0.552, P = 0.018), but these correlations were not observed a year before admission. TG level was the only parameter associated with LDL-C and HbA1c levels. CONCLUSIONS: A linear correlation between the LDL-C and TG levels, obesity, older age, male sex, and smoking may be associated with increased risk of onset of ACS early after the initiation of statin therapy. Prospective cohort studies are needed to further explore these interactions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".