Age and sex differences, and changing trends, in the use of evidence-based therapies in acute coronary syndromes: perspectives from a multinational registry
Bibliographic record
Abstract
BACKGROUND: A limited number of studies have examined the age and sex differences, and potentially changing trends, in cardiac medication and procedure use in patients hospitalized with an acute coronary syndrome (ACS). METHODS: Using data from a large multinational study, we examined the age and sex differences, and changing trends (1999-2007) therein, in the hospital use of evidence-based therapies in patients hospitalized with an ACS using data from the Global Registry of Acute Coronary Events (n=50 096). RESULTS: After adjustment for several variables, in comparison with men below 65 years, patients in other age-sex strata had a significantly lower odds of receiving aspirin [odds ratios (ORs) for men 65-74, 75-84, and >or=85 years, women <65, 65-74, 75-84, and >or=85 years were 0.86, 0.84, 0.72, 0.80, 0.86, 0.68 and 0.46, respectively], angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (ORs, 1.08, 1.01, 0,71, 0.83, 0.90, 0.89, and 0.63), beta blockers (ORs, 0.66, 0.52, 0.53, 0.67, 0.54, 0.53, and 0.52), statins (ORs, 0.72, 0.49, 0.29, 0.82, 0.68, 0.44, and 0.22), and undergoing coronary artery bypass graft surgery or a percutaneous coronary intervention (ORs, 0.79, 0.53, 0.21, 0.64, 0.57, 0.38, and 0.13) during their acute hospitalization. Age and sex differences in the receipt of these therapies remained relatively unchanged during the period under study. CONCLUSION: Although there were increasing trends in the use of evidence-based medications and cardiac procedures over time, important gaps in the utilization of effective cardiac treatment modalities persist in elderly patients and younger women.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".