Retrospective assessment of prenatal alcohol exposure by detection of phosphatidylethanol in stored dried blood spot cards: An objective method for determining prevalence rates of alcohol consumption during pregnancy
Bibliographic record
Abstract
Baldwin, A., Jones, J., Jones, M., Plate, C., & Lewis, D. (2015). Retrospective assessment of prenatal alcohol exposure by detection of phosphatidylethanol in stored dried blood spot cards: An objective method for determining prevalence rates of alcohol consumption during pregnancy. The International Journal Of Alcohol And Drug Research, 4(2), 131-137. doi:http://dx.doi.org/10.7895/ijadr.v4i2.209Aims: To analyze the efficacy of screening banked newborn dried blood spots (DBS) for detection of phosphatidylethanol(PEth), a direct alcohol biomarker, with the purpose of performing a retrospective assessment of statewide prevalence rates ofalcohol consumption in late pregnancy that results in risky prenatal alcohol exposure.Design: Residual DBS samples collected for newborn screening and stored by a state department of public health wereexamined for concentrations of PEth. The prevalence of prenatal alcohol exposure, as determined by this direct alcoholbiomarker, was compared to prevalence rates of alcohol consumption during pregnancy that have been derived from multiplestate-based and national studies using maternal self-report surveys.Setting: DBS cards representative of the general newborn population were collected from multiple hospitals across a singlemidwestern state.Participants: Two hundred fifty anonymous newborn DBS collected for routine metabolic screening in a midwestern state wererequested through the Virtual Repository of Dried Blood Spots.Measures: Concentrations of PEth, a highly specific biomarker of alcohol consumption, were analyzed using a liquidchromatography–tandem mass spectrometry method validated by our laboratory.Findings: Of 2 50 D BS e xamined, 4 % w ere p ositive f or PEth ( PEth ≥ 8 n g/ml) which is indicative of exposure to maternalalcohol consumption during the last month of pregnancy.Conclusions: Detection of PEth from newborn DBS cards can identify prenatal alcohol exposure and also be used forretrospective surveillance of alcohol consumption during the last three to four weeks of pregnancy, using specimens that arecollected for routine metabolic screening and stored by many state health departments.
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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 | 0.003 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".