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Record W6983221999

A longitudinal analysis of the predictors and consequences of prenatal antidepressant use among women requiring these medications before pregnancy

2015· dissertation· en· W6983221999 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2015
Typedissertation
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsPregnancyDiscontinuationMedical prescriptionAntidepressantDepression (economics)Cohort studyConfoundingDrugs in pregnancy
DOInot available

Abstract

fetched live from OpenAlex

Women with chronic conditions who become pregnant have a difficult choice to consider: continue pharmaceutical treatment, though it may have teratogenic risks for the fetus, or stop treatment, though the condition itself may harm both mother and baby. Unfortunately, very little is known about prescription medication use in pregnancy among women requiring treatment for chronic conditions prior to pregnancy to help guide their decisions. This is due, partly, to the scarcity of data from population-based studies assessing the consequences of medication use or discontinuation on pregnancy outcomes. It is also due to problems of confounding that complicate efforts to untangle the roles of medication and disease in pregnancy outcomes.In this study, we examined a series of questions to address these issues: Are pregnant women more likely to discontinue antidepressant use than are non-pregnant women, i.e. is pregnancy a major determinant of medication discontinuation? What are the maternal characteristics associated with antidepressant discontinuation in pregnancy? Finally, does maternal antidepressant use and discontinuation have consequences on maternal health? The answers may help us broaden our knowledge of an understudied area, as well as shape clinical guidelines.Our data derive from a large, population-based cohort of women identified through Quebec’s health administrative databases (RAMQ). We compared medication use in pregnancy among women using antidepressants before pregnancy to medication use in matched non-pregnant women, and determined the predictors of antidepressants discontinuation. We then assessed the risk of preeclampsia in women continuing use of antidepressants in pregnancy compared to (a) women who stopped all use in pregnancy; (b) women with a depression diagnosis and no antidepressant use; and (c) women with neither a depression diagnosis nor antidepressant use. Finally, we assessed the risk of miscarriage in women taking antidepressants in the first trimester compared to depressed and non-depressed unexposed women. To account for the risk of induced abortions, which may be high among antidepressant users, and may bias the miscarriage risk estimates, we employed an appropriate correction factor. We found that pregnant women are significantly more likely to discontinue antidepressants compared to non-pregnant women, with discontinuation rates differing within classes of antidepressants. The main predictors of continuing use in pregnancy were factors related to disease severity and overall health (e.g. duration of pre-pregnancy antidepressant use, being on welfare and older age). The risk of preeclampsia among women who continued antidepressants in the first 20 weeks of pregnancy was significantly higher than those who stopped use before pregnancy; discontinuers and depressed, unexposed women did not have a significantly elevated risk compared to non-depressed unexposed women. Women using antidepressants in the first trimester had an increased risk of miscarriage compared to either depressed or non-depressed unexposed women, and these findings persist even after accounting for induced abortions.The findings of this thesis research suggest that pre-pregnancy antidepressant users are likely to discontinue use in pregnancy, and the likelihood of discontinuation depends on disease severity and medication class. Our results support an association between antidepressant use itself and an increased risk of miscarriage and preeclampsia because of the persistent elevated findings in antidepressant users when compared to depressed women, and the higher risks associated with continuers compared to stoppers. While residual confounding by factors related to disease severity cannot be ruled out, our findings are nevertheless relevant to the clinical management of pregnant women requiring the use of antidepressants, and should be considered in physician-patient discussions and decision-making.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.253
Teacher spread0.229 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2015
Admission routes1
Has abstractyes

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