Early and surgical menopause associated with higher Framingham Risk Scores for cardiovascular disease in the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
OBJECTIVE: In women, the risk of cardiovascular disease (CVD) is higher in the postmenopausal period. The effect that menopausal type, natural versus surgical, or the age at natural menopause has on CVD needs further investigation. To this end, we assessed the association between menopausal type and timing and the 10-year office-based Framingham Risk Score (FRS) in women from the Canadian Longitudinal Study on Aging. METHODS: We included women aged 45 to 85 years from the Canadian Longitudinal Study on Aging Comprehensive cohort of seven Canadian provinces who were menopausal at the time of recruitment and had no prior CVD. Poisson regressions were used to evaluate the association between menopausal characteristics and the FRS. Natural menopause was defined as the cessation of menstrual periods for at least 1 year in women with no history of hysterectomy. Surgical menopause was defined as hysterectomy with or without oophorectomy prior to natural menopause. As main covariates, we examined age, education, province of residency, and hormone therapy. RESULTS: A total of 10,090 women (8,200 natural menopausal and 1,890 surgical menopausal) were eligible for the study. In the multivariable model, surgical menopause was associated with a higher mean FRS compared with natural menopause (CVD risk 12.4% vs 10.8%, P < 0.001). Compared with women with age at natural menopause from 50 to 54 years (CVD risk 10.2%), natural menopause before age 40, 40 to 44, or 45 to 49 had a higher CVD risk (12.2%, 11.4%, and 10.6%, respectively, P < 0.001). CONCLUSIONS: Our study supports an association between menopausal type and timing on CVD risk prediction and highlights the need to be judicious about surgical menopause. Preventative interventions for CVD should be considered in surgical menopausal women and women with an age at natural menopause less than 45 years.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".