Perinatal outcomes of human singletons conceived naturally versus assisted reproductive technologies: analysis of the effect of stimulated IVF, modified natural IVF, and frozen embryo transfer
Bibliographic record
Abstract
Abstract Background Obstetrical outcomes in assisted reproduction techniques (ART) were compared with naturally conceived pregnancies and among each other in multiple reports. However, many important changes in the practice of in vitro fertilization (IVF) over the years, including single embryo transfers (sET) and the introduction of modified natural IVF (mnIVF), and the advances in the frozen embryo transfer (FET) might have impacted the outcomes. Our study is the first to our knowledge to assess four different groups, including spontaneous pregnancies, mnIVF, stimulated IVF (sIVF), and FET altogether in a head-to-head comparison. This is a retrospective study on perinatal outcomes of singleton babies conceived naturally or using three different ART protocols between 2011 and 2014. The primary objective was the comparison of gestational age and birth weight between spontaneously conceived pregnancies (NAT, n= 15,770), mnIVF (n=235), sIVF (n=389), and FET (n=222). Results Our results show a significant difference in favor of naturally conceived pregnancies over ART in term of gestational age. In fact, the gestational age of babies in the NAT group was statistically higher compared to each one of the ART groups alone. Regarding the birth weight, the mean was significantly higher in the FET group compared to the other categories. Conclusion Differences in perinatal outcomes are still found among babies born after different modes of conception. However, there is still need for well-designed high-quality trials assessing perinatal outcomes between naturally conceived pregnancies and different ART protocols based on different maternal and treatment characteristics.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".