Understanding severe maternal morbidity in women pregnant by in vitro fertilization: a population-based cohort study of the Better Outcomes Registry & Network (BORN) Ontario
Bibliographic record
Abstract
Background: The use of in vitro fertilization (IVF) contributes to an approximate 2-fold increase in the risk of severe maternal morbidity (SMM) – a composite outcome of severe “near miss” complications occurring at delivery – compared with unassisted pregnancy. Whether the elevated risk is due to infertility, maternal or paternal factors, or the treatment itself is less clear. It is plausible that the process of controlled ovarian stimulation (COS) used as part of fresh embryo transfers (ET) may contribute to this risk, mediated by high levels of estrogen and its possible impact on the endometrial lining and the vascular endothelium.Objectives and hypotheses: The primary objective of this thesis was to evaluate the association between fresh ETs, as compared with frozen ETs, and SMM during IVF pregnancy. The secondary objective was to assess whether one or more prior fresh cycles (i.e., cumulative dose of COS) is associated with SMM in women pregnant by IVF, compared with no prior fresh cycles. Methods: Using data from the Better Outcome Registry and Network (BORN) Information System, we carried out an Ontario-wide population-based retrospective conception cohort study including 13 929 women aged 18-55 years pregnant via IVF between January 1, 2012, and March 5, 2018. The primary outcome for both objectives was a composite of SMM captured at the time of the index birth hospitalization. Secondary outcomes consisted of the most common subtypes of SMM in our cohort, which were (1) hemorrhagic events and (2) severe preeclampsia and/or cardiovascular events. We used multiple imputation to account for data missing-at-random, and univariable and multivariable log binomial regression models to estimate crude and adjusted risk ratios (RR) for the primary outcome and secondary outcomes, comparing women who had fresh ETs with those who had frozen ETs. Furthermore, using univariable and multivariable ordinal logistic regression models, we estimated crude and adjusted RRs for primary and secondary outcomes according to one or more prior fresh cycles, compared with no prior fresh cycles. Results: There were 14 812 births over the study period; after exclusions, our cohort included 13 929 IVF pregnancies (n=5660 fresh ET and n=8269 frozen-thawed ET; mean age 35.1±4.5 and 35.2 ±4.6, respectively). Overall, 454 women had SMM (32.6 per 1000); among these, 174 conceived via fresh ETs (30.7 per 1000), and 280 conceived via frozen-thawed ETs (33.9 per 1000) (crude RR 0.91 [95% CI 0.75-1.09]). After adjustment for age at conception, nulliparity, pre-existing cardiometabolic diseases, PCOS, year of conception, and income quintile, the adjusted RR was 0.85 (95% CI 0.70-1.04). Fresh ET was associated with a significantly lower risk of hemorrhagic SMM events when compared with frozen-thawed ET (adjusted RR 0.63 [95% CI 0.48-0.82]). In contrast, fresh ET had a near-significant higher risk of severe preeclampsia when compared with frozen-thawed ET (adjusted RR 1.33 [95% CI 0.97-1.82]). In secondary analyses, there was no difference in the risk of a woman having SMM after having one cycle prior to index birth (adjusted RR 0.96 [95% CI 0.78-1.18]) or ≥2 cycles (adjusted RR 0.91 [95% CI 0.67-1.25]) when compared with no prior cycles.Conclusion: Results from this study provide evidence that fresh ETs is associated with lower risk of some SMM events in pregnancies conceived by IVF. However, some evidence suggests that fresh ETs may increase the risk of severe preeclampsia and cardiovascular events. As infertility treatments become more available in Canada, better understanding of the ways IVF is associated with maternal health challenges will vastly improve maternal healthcare. It may be that healthcare practitioners should overall favor fresh cycles when clinically indicated, except in instances where the patient is at increased risk for cardiac decompensation or severe preeclampsia
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".