Prevalence of myocardial infarction over a 10–15-year period in the USA has decreased in midlife men but increased in women, with a decrease in the excess cardiovascular risk of men compared with women
Bibliographic record
Abstract
Commentary on: Towfighi A, Zheng L, Ovbiagele B. Sex-specific trends in midlife coronary heart disease risk and prevalence. Arch Intern Med 2009;169:1762–6.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Although initiatives such as the red dress campaign have substantially increased awareness of the mortality risk for women with coronary heart disease, the belief remains common that women in their midlife years are at an overall lower risk than men of the same age. Although much attention has been directed towards a better appreciation of the influence of sex on cardiovascular risk and management, important gaps in knowledge remain. Using the cross-sectional, nationally representative National Health and Nutrition Examination Surveys (NHANES), Towfighi and colleagues compared changes between two decade cohorts (1988–1994 and 1999–2004) in myocardial infarction (MI) prevalence and Framingham coronary risk scores (FCRSs) by sex. The study aimed to determine the sex-specific midlife … [1]: {openurl}?query=rft.jtitle%253DArchives%2Bof%2BInternal%2BMedicine%26rft.stitle%253DArch%2BIntern%2BMed%26rft.aulast%253DTowfighi%26rft.auinit1%253DA.%26rft.volume%253D169%26rft.issue%253D19%26rft.spage%253D1762%26rft.epage%253D1766%26rft.atitle%253DSex-Specific%2BTrends%2Bin%2BMidlife%2BCoronary%2BHeart%2BDisease%2BRisk%2Band%2BPrevalence%26rft_id%253Dinfo%253Adoi%252F10.1001%252Farchinternmed.2009.318%26rft_id%253Dinfo%253Apmid%252F19858433%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1001/archinternmed.2009.318&link_type=DOI [3]: /lookup/external-ref?access_num=19858433&link_type=MED&atom=%2Febnurs%2F13%2F3%2F78.atom [4]: /lookup/external-ref?access_num=000271163800007&link_type=ISI
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".