Une faible consommation d'alcool pendant la grossesse est-elle nuisible au fœtus ? Une revue critique de la littérature
Bibliographic record
Abstract
The dramatic consequences of heavy prenatal alcohol exposure are well known, but the effects of low levels of alcohol consumption during pregnancy are controversial and official recommendations thereon differ between countries. In France, 23% of women continue to drink alcohol during pregnancy. We have conducted a critical review of literature concerning the association of low level alcohol consumption during pregnancy and the effects on the fetus. A search was conducted from September 2012 to July 2013 in the main databases. The articles corresponding to the predefined inclusion criteria were retrieved and evaluated in terms of quality with the Newcastle Ottawa scale. Among 4655 titles resulting from the research, 11 publications met the inclusion criteria. There was no evidence of association between a maternal alcohol consumption inferior to 2 standard drinks per week and an increased risk of fetal death, growth disorder, prematurity or fetal malformations. However, there were important methodological weaknesses and a large heterogeneity among the studies in this review. In the current state of knowledge, the safest choice for pregnant women is to not consume alcohol. This message should be delivered by every health professional, along with information regarding the effects of alcohol on the child. High powered studies with a standardized protocol and an accurate assessment of the consumption model should examine implications of low prenatal exposure to short, medium and long term.
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 | 0.016 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".