Obstetric Outcomes and Congenital Abnormalities After In Vitro Maturation, In Vitro Fertilization, and Intracytoplasmic Sperm Injection
Bibliographic record
Abstract
OBJECTIVE: To compare obstetric outcome and congenital abnormalities in pregnancies conceived after in vitro maturation (IVM), in vitro fertilization (IVF), and intracytoplasmic sperm injection (ICSI) with those in spontaneously conceived controls. METHODS: Data were collected from the McGill Obstetrics and Neonatal Database (MOND). All children were examined and classified in a standard manner. Final data were reviewed 12 months after delivery. Pregnancies by IVM, IVF, and ICSI were compared with those of age- and parity-matched controls. Congenital abnormality, gestational age, birth weight, Apgar scores, cord pH, growth restriction, pregnancy complications, mode of delivery, and multiple pregnancy were compared. RESULTS: A total of 432 children were born from 344 pregnancies after assisted reproductive technology (ART) during the study period (IVM 55, IVF 217, ICSI 160). The observed odds ratios (ORs) for any congenital abnormality were 1.42 (95% confidence interval [CI] 0.52-3.91) for IVM, 1.21 (95% CI 0.63-2.62) for IVF, and 1.69 (95% CI 0.88-3.26) for ICSI. Twin pregnancy (IVM 21%, IVF 20%, ICSI 17%) and triplet pregnancy (IVM 5%, IVF 3%, ICSI 3%) were higher than those in controls (1.7% twins and 0% triplets) (P<.001). Cesarean delivery rates were higher after ART, even in singleton pregnancies (IVM 39%, IVF 36%, ICSI 36%; controls: 26.3%) (P<.05). Apgar scores, cord pH, growth restriction, and pregnancy complications were comparable in all groups. CONCLUSION: All ART pregnancies are associated with an increased risk of multiple pregnancy, cesarean delivery, and congenital abnormality. Compared with IVF and ICSI, IVM is not associated with any additional risk.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".