Association of Endometriosis and Severe Maternal Morbidity
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association between endometriosis and risk of severe maternal morbidity (SMM). METHODS: We conducted a population-based retrospective cohort study of 2,412,823 deliveries at hospitals in Quebec, Canada, between 1989 and 2019. The exposure was surgically confirmed endometriosis. Patients were classified as having active endometriosis during pregnancy, inactive endometriosis during pregnancy, a diagnosis of endometriosis postpregnancy, or no endometriosis. The outcome was SMM, including by a range of life-threatening maternal conditions during pregnancy or up to 42 days postdelivery. We computed rates of SMM and used log binomial regression to assess the association with endometriosis (risk ratio [RR]; 95% CI), adjusted for maternal characteristics. RESULTS: Severe maternal morbidity occurred in 46.2 of 1,000 patients with endometriosis, compared with 30.7 of 1,000 patients without endometriosis. Relative to no exposure, endometriosis was associated with 1.43 times the risk of SMM (95% CI 1.36-1.51). Patients with endometriosis that was active during pregnancy had a greater risk of SMM (RR 1.93; 95% CI 1.76-2.11). Active endometriosis was associated with the risk of severe preeclampsia and eclampsia, severe hemorrhage, hysterectomy, cardiac complications, embolism, shock, sepsis, and intensive care unit admission. Inactive endometriosis was less strongly associated with these outcomes. CONCLUSION: Pregnant patients with endometriosis, especially active endometriosis, have a greater risk of SMM and may benefit from closer follow-up to prevent severe complications of pregnancy.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".