Drowsiness and Poor Feeding in a Breast-Fed Infant: Association with Nefazodone and its Metabolites
Bibliographic record
Abstract
OBJECTIVE: To investigate whether adverse effects in a premature neonate could be attributed to nefazodone exposure via breast milk. CASE SUMMARY: The breast-fed white infant (female, 2.1 kg, 36 weeks corrected gestational age) of a 35-year-old woman (60 kg) taking nefazodone 300 mg/d was admitted to the hospital because she was drowsy, lethargic, unable to maintain normal body temperature, and was feeding poorly. A diagnosis of exposure to nefazodone via breast milk was considered only after other more likely diagnoses had been excluded. After breast feeding was discontinued, the infant's symptoms resolved slowly over a period of 72 hours. The maternal plasma and milk concentration-time profiles for nefazodone and its metabolites, triazoledione, HO-nefazodone, and m-chlorphenylpiperazine, were quantified by HPLC. The calculated infant dose for nefazodone and its active metabolites (as nefazodone equivalents) via the milk was only 0.45% of the weight-adjusted maternal nefazodone daily dose. DISCUSSION: Our data suggest a putative association between maternal nefazodone ingestion and adverse effects in a premature breast-fed neonate. The measured amount of drug exposure would normally be considered safe in a full-term infant. However, there was a temporal relationship between resolution of adverse effects in the infant and cessation of breastfeeding. CONCLUSIONS: This case highlights the importance of individualizing the risk-benefit analysis for exposure to antidepressants in breast milk, especially when dealing with premature neonates.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".