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Selected Pregnancy and Delivery Outcomes After Exposure to Antidepressant Medication

2013· review· en· W2008972495 on OpenAlexafffund
Lori E. Ross, Sophie Grigoriadis, Lana Mamisashvili, Emily H. VonderPorten, Michael Roerecke, Jürgen Rehm, Cindy‐Lee Dennis, Gideon Koren, Meir Steiner, Patricia Mousmanis, Amy Cheung

Bibliographic record

VenueJAMA Psychiatry · 2013
Typereview
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersCanadian Institutes of Health Research
KeywordsMedicinePregnancyAntidepressantOdds ratioEdinburgh Postnatal Depression ScaleDepression (economics)PopulationCochrane LibraryConfoundingObstetricsMeta-analysisInternal medicinePsychiatryAnxiety

Abstract

fetched live from OpenAlex

IMPORTANCE: Untreated depression during pregnancy has been associated with increased morbidity and mortality for both mother and child and, as such, optimal treatment strategies are required for this population. CONTEXT: There are conflicting data regarding potential risks of prenatal antidepressant treatment. OBJECTIVE: To determine whether prenatal antidepressant exposure is associated with risk for selected adverse pregnancy or delivery outcomes. DATA SOURCES MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature, PsycINFO, and the Cochrane Library were searched from their start dates to June 30, 2010. STUDY SELECTION English-language studies reporting outcomes associated with pharmacologic treatment during pregnancy were included. We reviewed 3074 abstracts, retrieved 735 articles, and included 23 studies in this meta-analysis. DATA EXTRACTION: Study design, antidepressant exposure, adjustment for confounders, and study quality were extracted by 2 independent reviewers. RESULTS: There was no significant association between antidepressant medication exposure and spontaneous abortion (odds ratio [OR], 1.47; 95% CI, 0.99 to 2.17; P = .055). Gestational age and preterm delivery were statistically significantly associated with antidepressant exposure (mean difference [MD] [weeks], -0.45; 95% CI, -0.64 to -0.25; P < .001; and OR, 1.55; 95% CI, 1.38 to 1.74; P < .001, respectively), regardless of whether the comparison group consisted of all unexposed mothers or only depressed mothers without antidepressant exposure. Antidepressant exposure during pregnancy was significantly associated with lower birth weight (MD [grams], -74; 95% CI, -117 to -31; P = .001); when this comparison group was limited to depressed mothers without antidepressant exposure, there was no longer a significant association. Antidepressant exposure was significantly associated with lower Apgar scores at 1 and 5 minutes, regardless of whether the comparison group was all mothers or only those who were depressed during pregnancy but not exposed to antidepressants. CONCLUSIONS AND RELEVANCE: Although statistically significant associations between antidepressant exposure and pregnancy and delivery outcomes were identified, group differences were small and scores in the exposed group were typically within the normal ranges, indicating the importance of considering clinical significance. Treatment decisions must weigh the effect of untreated maternal depression against the potential adverse effects of antidepressant exposure.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.050
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.015
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.024
GPT teacher head0.322
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations265
Published2013
Admission routes2
Has abstractyes

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