Polycystic Ovary Syndrome, Endometriosis, and Venous Thromboembolism: A Population-Based Study
Bibliographic record
Abstract
BACKGROUND: There is a paucity of studies on the association between polycystic ovary syndrome (PCOS) and endometriosis and the occurrence of venous thromboembolism (VTE). OBJECTIVE: Our study aimed to evaluate the association between PCOS, endometriosis, deep vein thrombosis (DVT), and pulmonary embolism (PE). METHODS: This was a retrospective study of prospectively collected data using the Healthcare Cost and Utilization Project databases. We examined the association between PCOS and endometriosis with DVT and PE from a cohort of 12,814,970 female patients, aged 18-49 years, who were hospitalized between 2007 and 2014. RESULTS: We observed increasing trends, with a relative increase of 140% (from 0.27% to 0.65%) for PCOS, 16% (from 0.43% to 0.50%) for DVT, and 39% (from 0.23% to 0.32%) for PE, whereas we observed a decline by 34% for endometriosis (from 0.85% to 0.56%). The unadjusted analysis showed an association between PCOS and VTE, which remained significant after adjustment for sociodemographic characteristics and comorbidities (OR = 2.16; 95% CI: 2.00-2.33 and OR = 2.44; 95% CI: 2.23-2.67 for DVT and PE, respectively). The association between endometriosis and VTE was age-dependent, with an increased risk of VTE among women 18-24 years whereas this risk was decreased among those 35 years and older. CONCLUSION: Our study indicates an association between PCOS and VTE and an age-dependent association between endometriosis and VTE.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".