Retrospective Diagnosis of an Adverse Drug Reaction in a Breastfed Neonate: Liquid Chromatography-Tandem Mass Spectrometry Quantification of Dextropropoxyphene and Norpropoxyphene in Newborn and Maternal Hair
Bibliographic record
Abstract
Dextropropoxyphene (DP) and norpropoxyphene (NP) are commonly used in the treatment of postpartum pain. The drug is widely prescribed in Europe and Canada and has been recently approved for use in the U.S. Its safety during breastfeeding, however, has not been fully established. Very few reports on its effects on neonates have been published. We report here the case of a mother treated with DP (6 capsules a day for 10 days) while she was breastfeeding. On day 7, her baby was lethargic and had difficulties with breastfeeding, which led to early weaning. The correlation between side effects observed in the infant and DP was made retrospectively by measuring DP and NP hair concentrations in the mother-infant pair with liquid chromatography-tandem mass spectrometry. Breastfeeding mothers taking DP expose their infants to high doses of DP and NP. In agreement with previously published reports, these data indicate that acetaminophen and nonsteroidal antiinflammatories are preferable for analgesia during breastfeeding. Breastfeeding should be encouraged under most circumstances, and if the mother takes any treatment for pain, a commonly prescribed drug with pharmacologic data available must be used.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".