Sex differences in the effectiveness of statins after myocardial infarction
Bibliographic record
Abstract
BACKGROUND: We sought to investigate the sex differences in the effectiveness of statins in patients with acute myocardial infarction (AMI). METHODS: Linking hospital discharge and drug claims databases from Quebec, Canada (1998-2004), we identified statin users (n = 14 710) and non-users (n = 23 833) discharged from hospital after an AMI-related hospital stay and followed up for as long as 7 years. RESULTS: All-cause death rates were 4.1 and 14.6 per 100 person-years among users and non-users, respectively, whereas cardiac death rates were 2.2 and 7.4 per 100 person-years. For death from any cause, the adjusted hazard ratios associated with statin use in women were 0.61 (95% confidence interval [CI], 0.54-0.69) within 1 year of follow-up, 0.55 (0.48-0.63) at 1-3 years and 0.38 (0.31-0.49) at > 3 years; in men, the corresponding estimates were 0.54 (0.48-0.60), 0.48 (0.42-0.55) and 0.34 (0.30-0.39). For cardiac-related death, the adjusted hazard ratios associated with statin use in women were 0.70 (0.60-0.81) within 1 year, 0.56 (0.46-0.68) at 1-3 years and 0.44 (0.31-0.62) at > 3 years of follow-up, whereas in men, the estimates were 0.59 (0.51-0.69), 0.47 (0.39-0.58) and 0.37 (0.30-0.45), respectively. INTERPRETATION: Statin therapy after an AMI was associated with reduced rates of all-cause and cardiac mortality. The effect increased with time in both sexes, but the degree of risk reduction was less for women than for men.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".