Is there a relationship between assisted reproductive technology and maternal outcomes? A systematic review of cohort studies
Bibliographic record
Abstract
Background: Pregnancy with assisted reproductive technology (ART) is accompanied by fetal and maternal outcomes. Objective: This systematic review aimed to assess the relationship between ART and maternal outcomes. Materials and Methods: In this systematic review, the electronic databases, including PubMed, MEDLINE, Web of Science, Scopus, Science Direct, Cochrane Library, Google Scholar, Magiran, Irandoc, and Scientific Information Database were searched for maternal outcomes reported from 2010-2021. The Newcastle-Ottawa Scale for cohort studies was used to assess the methodological quality of studies. Results: A total of 3362 studies were identified by searching the databases. After screening abstracts and full-text reviews, 19 studies assessing the singleton pregnancy-related complications of in vitro fertilization/intracytoplasmic sperm injection were included in the study. The results demonstrated that singleton pregnancies conceived through ART had higher risks of pregnancy-related complications and adverse maternal outcomes, such as vaginal bleeding, cesarean section, hypertension induced by pregnancy, pre-eclampsia, placenta previa, and premature membrane rupture than those conceived naturally. Conclusion: In conclusion, an increased risk of adverse obstetric outcomes was observed in singleton pregnancies conceived by ART. Therefore, obstetricians should consider these pregnancies as high-risk cases and should pay special attention to their pregnancy process. Key words: Assisted reproductive techniques, Maternal health, Pregnancy complications, In vitro fertilization.
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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 | 0.015 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".