Neonatal Outcomes After Prenatal Exposure to Selective Serotonin Reuptake Inhibitor Antidepressants and Maternal Depression Using Population-Based Linked Health Data
Bibliographic record
Abstract
CONTEXT: Prenatal exposure to selective serotonin reuptake inhibitor (SSRI) antidepressants and maternal depression both alter neonatal health, and distinguishing the effects of each influence remains challenging. OBJECTIVE: To determine whether exposure to SSRIs and depression differs from exposure to maternal depression alone. DESIGN: Using population health data, records of neonatal birth outcomes were linked to records of maternal health and prenatal maternal prescriptions for SSRIs. SETTING: Population of British Columbia, Canada. PARTICIPANTS: Mothers and their infants, representing all live births during a 39-month period (N = 119,547) (1998-2001). MAIN OUTCOME MEASURES: Outcomes from infants of depressed mothers treated with SSRIs (SE-D) were compared with outcomes from infants of depressed mothers not treated with medication (DE) and nonexposed controls. To control for maternal mental illness severity, propensity score matching was used to identify a comparison group of DE mothers who were similar to the SE-D mothers in characteristics in the year preceding and during pregnancy. RESULTS: Fourteen percent of mothers were diagnosed as having depression during their pregnancy, and the incidence of prenatal SSRI exposure increased from 2.3% to 5.0% during a 39-month period. Birth weight and gestational age for SE-D infants were significantly less than for DE infants, as was the proportion of infants born at less than 37 weeks (95% confidence interval [CI], -1 to -64, -0.25 to -0.45, and -0.009 to -0.04, respectively), although differences in the incidence of birth weight less than the 10th percentile for gestational age were not significant. An increased proportion of SE-D infants had neonatal respiratory distress (13.9% vs 7.8%), jaundice (9.4% vs 7.5%), and feeding problems (3.9% vs 2.4%) compared with DE infants (95% CI of difference, 0.042-0.079, 0.003-0.334, and 0.005-0.025, respectively). When outcomes were compared between SE-D and propensity score-matched DE neonates, SE-D was associated with increased incidence of birth weight below the 10th percentile and rates of respiratory distress. CONCLUSION: With linked population health data and propensity score matching, prenatal SE-D exposure was associated with an increased risk of low birth weight and respiratory distress, even when maternal illness severity was accounted for.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".