Common antiepileptic drugs in pregnancy in women with epilepsy
Bibliographic record
Abstract
Objective The aim of this study was to review systematically the available evidence on studies in humans on the effects of low-moderate levels of prenatal alcohol consumption (up to 10.4 UK units or 83 g/week) compared with consumption of no alcohol on pregnancy outcome.Design Systematic review.Population Pregnant women or women who are trying to become pregnant.Methods The search strategy included Medline, Embase, Cinahl and PsychInfo for the years 1970-2005. Titles and abstracts were read by two researchers and inclusion/exclusion being decided according to prespecified criteria. All the included articles were then obtained and read in full by the two researchers to decide on inclusion. The articles were assessed for quality using the Newcastle-Ottawa Quality Assessment Scales.Main outcome measures Outcomes considered were miscarriage, stillbirth, intrauterine growth restriction, prematurity, birthweight, small for gestational age at birth and birth defects including fetal alcohol syndrome.Results The search resulted in 3630 titles and abstracts, which were narrowed down to 46 relevant articles. At low-moderate levels of consumption, there were no consistently significant effects of alcohol on any of the outcomes considered. Many of the reported studies had methodological weaknesses.Conclusions This systematic review found no convincing evidence of adverse effects of prenatal alcohol exposure at low-moderate levels of exposure. However, weaknesses in the evidence preclude the conclusion that drinking at these levels during pregnancy is safe.
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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".