Abstract 12363: Statin Use and Severity of First Manifestation of Coronary Heart Disease Across Age and Sex
Bibliographic record
Abstract
Introduction: We investigate whether treatment recommendations for statins in primary prevention of cardiovascular disease (CVD) based on sex, age and risk factors translate to better CV outcomes in current routine clinical care. Methods: We studied a propensity match-weighted cohort of 14,542 Caucasian patients presenting with a first manifestation of CVD from the International Survey of Acute Coronary Syndromes (ISACS) Archives databank (NCT04008173) . Main outcome measures were the incidence of ST segment elevation myocardial infarction (STEMI) and acute heart failure (HF) on hospital admission. Results: Prior statin use was associated with a significantly decreased rate of STEMI (absolute difference 10.2%; RR ratio, 0.64; 95%CI 0.58 to 0.71) and acute HF (absolute difference 4.3%; RR ratio 0.72, 95% CI 0.62 to 0.83). Benefits were not attenuated when controlling for age 75 years and older (RR ratios 0.59, 95% CI 0.46 to 0.75 for STEMI and 0.66, 95% CI 0.50 to 0.87 for HF). Statin therapy had no effect in patients with 10-year ASCVD risk threshold less than 10% (RR ratios:0.85,95%CI:0.66- 1.08 for STEMI and 0.85,95%CI:0.60-1.20 for HF). Reductions in major CV events with statins diminished with female sex (interaction p=0.0200 for STEMI, and 0.2180 for HF). Moreover, statin use determined a lower risk of 30-day mortality in patients presenting with HF on admission (5.2 % absolute risk reduction and a 29% relative risk reduction). Conclusions: Prevention statin therapy reduces the risk of STEMI and acute HF with benefit in mortality from HF. The most gain is attained in male sex and in subjects with 10-year ASCVD risk ≥10%
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".