Obstetric and Perinatal Outcomes following Ovulation Induction and Unassisted Pregnancies in the Same Mother
Bibliographic record
Abstract
Objective We aimed to assess whether ovulation induction treatments affect obstetric and neonatal outcomes. Study Design This was a historic cohort study of deliveries in a single university-affiliated medical center between November 2008 and January 2020. We included women who had one pregnancy following ovulation induction and one unassisted pregnancy. The obstetric and perinatal outcomes were compared between pregnancies following ovulation induction and unassisted pregnancies, so that each woman served as her own control. The primary outcome measure was birth weight. Results A total of 193 deliveries following ovulation induction and 193 deliveries after unassisted conception by the same women were compared. Ovulation induction pregnancies were characterized by a significantly younger maternal age and a higher rate of nulliparity (62.7 vs. 8.3%, p < 0.001). In pregnancies achieved by ovulation induction, we found a higher rate of preterm birth (8.3 vs. 4.1%, p = 0.02) and instrumental deliveries (8.8 vs. 2.1%, p = 0.005), while cesarean delivery rates were higher following unassisted pregnancies. Birth weight was significantly lower in ovulation induction pregnancies (3,167 ± 436 vs. 3,251 ± 460 g, p = 0.009), although the rate of small for gestational age neonates was similar between the groups. On multivariate analysis, birth weight remained significantly associated with ovulation induction after adjustment for confounders, while preterm birth did not. Conclusion Pregnancies following ovulation induction treatments are associated with lower birth weight. This may be related to an altered placentation process following uterine exposure to supraphysiological hormonal levels. Key Points
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".