Assisted reproductive technologies and the risk of birth defects—a systematic review
Bibliographic record
Abstract
BACKGROUND: The risk of birth defects in infants born following assisted reproductive technology (ART) treatment is a controversial question. Most publications examining the prevalence of birth defects in ICSI and IVF infants compared to spontaneously conceived infants have serious methodological limitations; despite this, most researchers have concluded that there is no increased risk. METHODS: We carried out a systematic review to identify all papers published by March 2003 with data relating to the prevalence of birth defects in infants conceived following IVF and/or ICSI compared with spontaneously conceived infants. Independent expert reviewers used criteria defined a priori to determine whether studies were suitable for inclusion in a meta-analysis. Fixed effects meta-analysis was performed for all studies and reviewer-selected studies. RESULTS: Twenty-five studies were identified for review. Two-thirds of these showed a 25% or greater increased risk of birth defects in ART infants. The results of meta-analyses of the seven reviewer-selected studies and of all 25 studies suggest a statistically significant 30-40% increased risk of birth defects associated with ART. CONCLUSIONS: Pooled results from all suitable published studies suggest that children born following ART are at increased risk of birth defects compared with spontaneous conceptions. This information should be made available to couples seeking ART treatment.
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 | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".