A 12-year cohort study on adverse pregnancy outcomes in Eastern Townships of Canada: impact of endometriosis
Bibliographic record
Abstract
The aim of this study was to provide a temporal-spatial reference of adverse pregnancy outcomes (APO) and examine whether endometriosis promotes APO in the same population. Among the 31 068 women who had a pregnancy between 1997 and 2008 in Eastern Townships of Canada, 6749 (21.7%) had APO. These APO increased significantly with maternal age and over time (r(2 )= 0.522, p = 0.008); and were dominated by preterm birth (9.3%), pregnancy-induced hypertension (8.3%) including gestational hypertension (6.5%), low birth weight (6.3%), gestational diabetes (3.4%), pregnancy loss (2.2%) including spontaneous abortion (1.5%) and stillbirth (0.6%), intrauterine growth restriction (2.1%) and preeclampsia (1.8%). Among the 31 068 pregnancies, 784 (2.5%) had endometriosis and 183 (23.3%) had both endometriosis and APO. Endometriosis has been shown to increase the incidence of fetal loss (OR = 2.03; 95% CI = 1.42-2.90, p < 0.0001), including spontaneous abortion (OR = 1.89; 95% CI = 1.23-2.93, p = 0.005) and stillbirth (OR = 2.29; 95% CI = 1.24-5.22, p = 0.012). This study provides a temporal-spatial reference on APO, which is a valuable tool for monitoring, comparing and correcting. It is also the first study to highlight an impact of endometriosis on the incidence of spontaneous abortion and stillbirth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".