Methylphenidate use in pregnancy and lactation: a systematic review of evidence
Bibliographic record
Abstract
AIMS: The aims of this review were to summarize the scientific evidence about the risks of using methylphenidate for ADHD in pregnancy and lactation, to present a case in which interruption of treatment after delivery and during breastfeeding was harmful and to discuss the implications of treating or not treating ADHD in pregnancy and lactation. METHODS: For the systematic review, databases searched included Pubmed, Psychinfo, Web of Science, Embase, Biosis and Medline. RESULTS: Three articles were found with a total sample of 41 children exposed to methylphenidate in pregnancy. Malformations reported included congenital heart defects (n = 2), finger abnormalities (syndactyly, adactyly and polydactyly n = 2) and limb malformations (n = 1). Other problems included premature birth, asphyxia and growth retardation. One case report (n = 1) and one case series (n = 3) were identified regarding exposure to methylphenidate through breast feeding. In all cases, children developed normally and no adverse effects were reported. In our case report we describe an infant exposed to methylphenidate during pregnancy and breast feeding, who developed normally having no detectable congenital abnormalities. CONCLUSIONS: The number and size of the studies found were small. Identified cases were not representative of the general adult ADHD population having methylphenidate as monotherapy during pregnancy as all the articles reported combinations of methylphenidate with either known teratogenic drugs or drugs of abuse. There is a paucity of data regarding the use of methylphenidate in pregnancy and further studies are required. Although the default medical position is to interrupt any non-essential pharmacological treatment during pregnancy and lactation, in ADHD this may present a significant risk. Doctors need to evaluate each case carefully before interrupting treatment.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".