The Incidence of Prenatal Alcohol Exposure in Montevideo Uruguay As Determined by Meconium Analysis
Bibliographic record
Abstract
Prenatal alcohol exposure can lead to a wide range of deficits known as fetal alcohol spectrum disorder. Epidemiologic studies regarding alcohol consumption in pregnancy have concentrated on North America, but recent reports have suggested that consumption is significant in many parts of the world. In Uruguay, alcohol consumption has changed into more risky and dangerous patterns and thus has a theoretical risk of having a high rate of prenatal alcohol exposure. This study characterizes the incidence of prenatal alcohol exposure in Montevideo, Uruguay, using a novel biomarker, fatty acid ethyl esters, in meconium as well as a survey to mothers. Nine hundred five meconium samples were collected from Hospital Pereira Rossell and Hospital de Clínicas in Montevideo, Uruguay. A maternal questionnaire was also completed. Meconium was analyzed for fatty acid ethyl esters using liquid-liquid and solid phase extraction with gas chromatography-flame ionization detection. Meconium was also analyzed for other drugs of abuse using enzyme-linked immunosorbent assay. Forty-four percent of meconium samples were above the positive cutoff for fatty acid ethyl esters and represent those newborns with risky prenatal exposure during the final two trimesters of pregnancy. Infants with prenatal alcohol exposure were more likely to have prenatal exposure to tobacco (odds ratio, 1.56; 95% confidence interval, 1.11-2.20) or any illicit drug (odds ratio, 2.29; 95% confidence interval, 0.98-5.31). Ethyl linoleate was a significant predictor of infant birth weight along with prenatal tobacco exposure, maternal body mass index, and infant sex. This study highlights a 44% incidence of prenatal alcohol exposure.
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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 | 0.001 | 0.000 |
| 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) | 0.001 | 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".