Neurodevelopment of Children Following Prenatal Exposure to Venlafaxine, Selective Serotonin Reuptake Inhibitors, or Untreated Maternal Depression
Bibliographic record
Abstract
OBJECTIVE: Effects on child neurodevelopment of neurotransmitter reuptake inhibitors used as antidepressants during pregnancy have not been adequately studied. The authors compared the effects of prenatal exposure to venlafaxine (serotonin-norepinephrine reuptake inhibitor), selective serotonin reuptake inhibitors (SSRIs), and maternal depression. METHOD: A cohort derived from a prospectively collected database included four groups of children born to 1) depressed women who took venlafaxine during pregnancy (N=62), 2) depressed women who took SSRIs during pregnancy (N=62), 3) depressed women who were untreated during pregnancy (N=54), and 4) nondepressed, healthy women (N=62). The children's intelligence and behavior outcomes were evaluated with standardized instruments at one time point between the ages of 3 years and 6 years, 11 months. RESULTS: The children exposed to venlafaxine, SSRIs, and maternal depression during pregnancy had similar full-scale IQs (105, 105, and 108, respectively). The IQs of the venlafaxine and SSRI groups were significantly lower than that of the children of nondepressed mothers (112). The three groups exposed to maternal depression had consistently, but nonsignificantly, higher rates of most problematic behaviors than the children of nondepressed mothers. Severity of maternal depression in pregnancy and at testing predicted child behavior. Maternal IQ and child sex predicted child IQ. Antidepressant dose and duration during pregnancy did not predict any cognitive or behavioral outcome. CONCLUSIONS: Factors other than antidepressant exposure during pregnancy strongly predict children's intellect and behavior. Depression during pregnancy is a significant risk factor for postpartum depression. Children of depressed mothers may be at risk of future psychopathology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".