Women with intellectual disability at risk of adverse pregnancy and birth outcomes
Bibliographic record
Abstract
BACKGROUND: An increasing number of women with intellectual disability (ID) have children. Cross-sectional, clinical population data suggest that these women face an increased risk of delivering preterm and/or low birthweight babies. The aim of this study was to explore the prevalence of poor pregnancy and birth outcomes in women with ID and/or self-reported learning difficulties in an antenatal population. METHODS: A total of 878 pregnant women attending their first antenatal clinic visit were 'screened' for ID. Pregnancy and birth outcomes data were extracted from medical records post-partum. These data included pregnancy-related health conditions, including pre-eclampsia and gestational diabetes, and birth outcomes, including gestational age, birthweight, Apgar score and admission to neonatal intensive care and/or special care nursery. RESULTS: A total of 57 (6.5%) pregnant women with ID and/or self-reported learning difficulties were identified. These women experienced an unusually high rate of pre-eclampsia (odds ratio = 2.85). Their children more often had low birthweights (odds ratio = 3.08), and they were more frequently admitted to neonatal intensive care or special care nursery (odds ratio = 2.51). CONCLUSION: Further research is needed to understand the reasons for the adverse findings of this study and identify potentially changeable factors contributing to adverse pregnancy and birth outcomes for women with ID and/or self-reported learning difficulties and their children. To ensure quality antenatal care, health professionals may need to consider innovations such as extended consultation times, communication aids and audio-taping consultations.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".