Selective serotonin reuptake inhibitors or serotonin-norepinephrine reuptake inhibitors in pregnancy: Infant and childhood outcomes
Bibliographic record
Abstract
This position statement provides guidance for the monitoring, care, and follow-up of newborns exposed to selective serotonin reuptake inhibitors (SSRIs) or serotonin-norepinephrine reuptake inhibitors (SNRIs) in utero. Depression and anxiety are common during pregnancy and postpartum. While there are risks to taking medications during pregnancy, untreated or incompletely managed depression and anxiety also carry risks for the newborn. Poor neonatal adaptation syndrome (PNAS) occurs in one-third of newborns exposed to SSRIs or SNRIs in utero, and is generally mild and self-limiting. The low levels of SSRIs and SNRIs excreted in breast milk are compatible with breastfeeding. Persistent pulmonary hypertension of the newborn and congenital heart defects are rare associations of exposure to SSRIs or SNRIs in utero. There are inconsistencies in the literature regarding neurodevelopmental outcomes, specifically autism spectrum disorder and attention-deficit hyperactivity disorder. The inconsistencies likely relate to other factors (i.e., genetics, maternal depression, lifestyle, and comorbidities), rather than exposure to SSRIs or SNRIs in utero. Health care providers and parents should be reassured that PNAS is generally treatable with nonpharmacological measures, and that the risk of serious adverse effects from exposure to SSRIs or SNRIs in utero is low.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".