False‐Positive Meconium Test Results for Fatty Acid Ethyl Esters Secondary to Delayed Sample Collection
Bibliographic record
Abstract
BACKGROUND: Meconium analysis for fatty acid ethyl esters (FAEEs) is a validated method for identifying heavy prenatal ethanol (EtOH) exposure. This study investigated whether delayed sample collection can result in false-positive test results for FAEEs because of collection of samples potentially contaminated with postnatally produced stool. METHODS: Serial excretions were prospectively collected from neonates born to nondrinking mothers to capture the transition from meconium to postnatal stool. These were analyzed for FAEEs using headspace-solid phase microextraction and gas chromatography-mass spectrometry. Experiments involving incubation of samples with glucose or EtOH were performed to explore a potential mechanism of FAEE elevation. RESULTS: A total of 136 samples were collected from 30 neonates during their first few days of life (median of 4 samples/baby over a mean period of 68.5 hours postpartum). Although the first-collected meconium sample tested negative for FAEEs in all babies, later samples tested above the 2 nmol/g positive cutoff in 19 of 30 babies. Median time to appearance of FAEE-positive samples was 59.2 hours postpartum. In vitro experiments demonstrated that FAEE levels can be further increased in late samples (likely containing postnatal stool) after incubation with glucose, and that FAEEs are readily formed in meconium in the presence of EtOH. CONCLUSIONS: Collection of samples excreted later in the postpartum period can lead to false-positive test results for FAEEs, which could be because of contamination with dietary components of postnatally produced stool and EtOH-producing microorganisms. Clinically, it is critical to collect the earliest possible excretion for determination of FAEEs to ensure that the FAEE content is representative of in utero EtOH 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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".