Methamphetamine detection in maternal and neonatal hair: implications for fetal safety
Bibliographic record
Abstract
BACKGROUND: Methamphetamine misuse is a serious health problem of epidemic proportions. Use of this drug, particularly during pregnancy, is difficult to ascertain. Sparse information is available on gestational exposure. OBJECTIVES: To quantify methamphetamine accumulation in hair, identify the use of methamphetamine with other drugs of abuse and characterise correlations between concentrations of methamphetamine in maternal and neonatal hair. SUBJECTS AND METHODS: Motherisk laboratory at the Hospital for Sick Children routinely carries out analysis of methamphetamine in hair. Mothers and infants with positive results for methamphetamine in hair were identified. Drugs present in hair were analysed by ELISA and positive results were confirmed by gas chromatgraphy/mass spectrometry. RESULTS: 396 people positive for methamphetamine in their hair were identified from our database. Almost 85% of them were positive for at least one other drug of abuse, mostly cocaine. Eleven mother-baby pairs with hair positive for methamphetamine were identified. Methamphetamine levels in hair ranged between 0.13 and 51.97 ng/mg in the mothers and between 0 and 22.73 ng/mg in the neonates. Methamphetamine levels in mothers and neonates correlated significantly. One (9%) neonate was negative for methamphetamine even though the mother was positive. CONCLUSION: To our knowledge, this is the first report on fetal exposure to methamphetamine during pregnancy, showing transplacental transfer of the drug, with accumulation in fetal hair. Hair measurement for methamphetamine in neonates is a useful screening method to detect intra-uterine exposure to the drug. The data also indicate that positive exposure to methamphetamine strongly suggests that the person is a polydrug user, which may have important implications for fetal safety.
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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 | 0.002 | 0.006 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".