Potential impact of oral contraceptive choice on myocardial infarction mortality and deep vein thrombosis
Bibliographic record
Abstract
OBJECTIVES: To summarise the epidemiological evidence on the relationship between second- (OC2) and third-generation (OC3) oral contraceptives (OC) and the mortality associated with deep vein thrombosis (DVT) and myocardial infarction (MI), and to extrapolate and balance the evidence for these risks to the population of French OC users. METHODS: All studies published on the risk of MI during OC2 and OC3 use were analysed. For DVT the Committee for Proprietary Medicinal Products public assessment report published in 2001 and more recent studies published on this topic were used. The estimates of odds ratios (OR) for risk of death from DVT or MI were extracted from the published manuscripts. ORs were used to calculate the aetiological fraction of risk for death from DVT and MI in the population; the relative impact of OC3 compared to OC2 use was expressed as an excess risk of death overall and by age group for French women. RESULTS: Compared with OC2, the use of OC3 would prevent a maximum of 24 deaths from MI per year and induce a maximum of 16 deaths. Conversely, OC3 would induce 282-940 excess cases of DVT per year, resulting in 28-94 pulmonary embolisms and 3-19 deaths in the 4.7 million French OC users. CONCLUSION: Balancing the evidence, it is difficult to conclude that the overall cardiovascular risk is significantly lower for either of the two OC schemes.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".