Letter by Ahmed et al Regarding Article, “Low-Dose Aspirin for Primary Prevention of Cardiovascular Events in Patients With Type 2 Diabetes Mellitus: 10-Year Follow-Up of a Randomized Controlled Trial”
Bibliographic record
Abstract
We read with great interest the recent article by Saito and colleagues. 1 In their prospective observational cohort study after the conclusion of the Japanese Primary Prevention of Atherosclerosis With Aspirin for Diabetes randomized controlled trial, they found that after a median 10-year follow-up, low-dose aspirin did not affect the risk for cardiovascular events or hemorrhagic stroke but was associated with an increased risk for gastrointestinal bleeding.Use of aspirin in primary prevention is less clear in women compared with men.Previous trials have highlighted important sex differences in the effects of this therapy: In healthy women, low-dose aspirin for primary prevention resulted in a significantly decreased risk of stroke but demonstrated no significant effect on the risk of myocardial infarction, 2 whereas the opposite was found in men. 3 In both of these studies, aspirin increased the risk of gastrointestinal bleeding and the risk of hemorrhagic stroke; in women, however, this risk was strongly related to a woman's age.A subgroup analysis of participants >65 years of age in the Women's Health Study 2 showed a clear association of benefit for both stroke and myocardial infarction.These studies highlight not only the importance of sex-specific reporting of outcomes but also the need to take age into account as a marker of the effects of menopause on cardiovascular risk in women.In this era of precision medicine and the Choosing Wisely initiative, reporting of sex differences in outcomes in the scientific literature is critical to deliver effective healthcare interventions.With increasing evidence that aging and menopausal status increase many more cardiovascular risk factors in women than aging in men, 4 highlighting to whom the research results apply is an ethical obligation of the scientific community.Saito and colleagues 1 performed separate subgroup analyses stratified by sex and age that did not detect any differences between groups and concluded that the overall study results apply to women and men of all ages equally.However, the potential effects of menopause in women were not considered, which is important given their large, albeit not statistically significant, difference in outcome by age.As recently outlined by Clayton and Tannenbaum, 5 analysis by sex in addition to using age as a proxy of menopausal status would provide clinicians with important information on the potential benefits of aspirin for cardiovascular disease prevention in 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 | 0.012 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.035 | 0.031 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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".