PI-42Methamphetamine detection in maternal and neonatal hair
Bibliographic record
Abstract
BACKGROUND Methamphetamine abuse has been gathering momentum as a serious public health problem. Evidence of chronic use, particularly during pregnancy, is hard to obtain. Methamphetamine accumulates in hair and can be detected several months after exposure. Drugs that cross the placenta can be detected in hair of newborns. METHODS We developed a hair immunoassay for methamphetamine at Motherisk laboratory in Toronto. The aim of the study was to find evidence of methamphetamine exposure during pregnancy using hair measurements of the drug. RESULTS Out of 1124 positive methamphetamine results, we identified 8 mother-child pairs who had methamphetamine positive hair. None of the pairs identified included mothers with negative results, but there were 2 (25%) of the neonates who had a negative methamphetamine result although the mother was positive. Mean methamphetamine values were 1.8 ng/mg of hair in the mothers and 1.08 ng/mg in the neonates. There was a trend towards correlation between maternal and fetal levels. CONCLUSION To our knowledge, this is the first report that shows transplacental passage of methamphetamine, with accumulation in the fetal hair. We believe this provides the basis for studies to define pharmacokinetics of this drug in the mother-child couple. We have also shown that hair measurement of methamphetamine in neonates is a useful screening method to detect intra-uterus exposure. As fetal hair grows in the last trimester of pregnancy, a positive result may indicate maternal addiction. Clinical Pharmacology & Therapeutics (2005) 79, P18–P18; doi: 10.1016/j.clpt.2005.12.063
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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) | 0.002 | 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".