Endometriosis and cardiovascular disease: a population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Endometriosis, a prevalent condition among females of reproductive age, may be associated with increased risk of cardiovascular disease (CVD) through chronic inflammation and early menopause. The objective of this study was to estimate the association between endometriosis and subsequent risk of CVD. METHODS: We conducted a population-based cohort study using administrative health data from Ontario residents from 1993 to 2015. We compared the incidence of CVD and cardiovascular health outcomes between females with endometriosis and 2 age-matched females without endometriosis. The primary outcome was hospital admission for CVD. Secondary outcomes included in-hospital CVD events of interest and emergency department visits for CVD. We used Cox proportional hazards models to estimate adjusted hazard ratios (HRs) between endometriosis and CVD events. RESULTS: We identified 166 835 eligible patients with endometriosis and matched 333 706 patients without endometriosis. The mean age of those with endometriosis was 36.4 years. Patients with endometriosis had a higher incidence of hospital admission for CVD (195 admissions/100 000 person-years) compared with those without endometriosis (163 admissions/100 000 person-years). Similarly, the incidence of secondary CVD events was slightly higher among patients with endometriosis (292 cases/100 000 person-years) than among those without endometriosis (224 cases/100 000 person-years). Females with endometriosis had an increased risk of hospital admission (adjusted HR 1.14, 95% confidence interval [CI] 1.10-1.19) and secondary CVD events (adjusted HR 1.26, 95% CI 1.23-1.30). INTERPRETATION: In this large, population-based study, endometriosis was associated with a small increased risk of CVD events. Future studies need to investigate potential etiological mechanisms and strategies to decrease long-term CVD risk in patients with endometriosis.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".