Assisted reproductive technology and the risk of preeclampsia: an updated systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The objective of this systematic review and meta-analyses was to assess the risk of preeclampsia among women who conceived with assisted reproductive technology (ART). METHODS: We searched the ISI Web of Knowledge, Medline/PubMed, Scopus, and Embase (from inception to May 2017) for English language articles using a list of key words. In addition, reference lists from identified studies and relevant review articles were also searched. Data extraction was performed by two authors, and the study quality was assessed using the Newcastle-Ottawa Scale. Random-effects model meta-analysis was applied to pool the relative risks (RR) across studies. RESULTS: = 99.8%). Meta-analysis showed a significant increase in preeclampsia in women who conceived by ART compared with those who conceived spontaneously (RR = 1.71, 95% CI = 1.11-2.62, p = 0.015). CONCLUSIONS: The findings of this systematic review indicate that the use of ART treatment is associated with a 1.71-fold increase in preeclampsia.
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 | 0.012 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.028 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".