Fetal Exposure to Alcohol as Evidenced by Fatty Acid Ethyl Esters in Meconium in the Absence of Maternal Drinking History in Pregnancy
Bibliographic record
Abstract
The detection of fatty acid ethyl esters (FAEE) in neonatal meconium has been proposed as a novel screening method for intrauterine exposure to alcohol. We investigated the potential use of meconium FAEE screening in a high-risk neonatal population in the absence of maternal drinking history. One hundred forty-two meconium samples of neonates suspected of intrauterine illicit substance exposure and referred to the Motherisk Laboratory were analyzed for the existence of drugs by enzyme-linked immunosorbent assay (ELISA) and FAEE by gas chromatography-flame ionization detection (GC-FID). A positive FAEE test was previously defined as a cumulative measurement of 7 individual FAEE > or = 2 nmol/g. Seventy-one percent of the samples tested positive for at least 1 illicit drug, with cannabis being the most prevalent (52.3%). Fourteen percent of all samples tested positive for prenatal alcohol exposure, as evidenced by cumulative meconium FAEE > or = 2 nmol/g. Ethyl oleate, linoleate, palmitate, and arachidonate were detected most often and at the highest levels. At least 3 individual FAEE were detected in 95% of all positive samples, and none could be identified by the use of 1 selected FAEE. Significantly elevated levels of FAEE above the baseline and the presence of multiple FAEE species in meconium are exclusive to neonates who have likely been exposed to excessive amounts of alcohol in utero. Babies born to mothers who are suspected to use illicit drugs in pregnancy are at elevated risk for exposure also to alcohol in utero. Meconium FAEE are emerging biologic markers that can potentially facilitate earlier diagnosis and intervention for less apparent forms of alcohol-related disabilities that cannot be confirmed in the absence of maternal drinking history.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".