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Record W3021533363 · doi:10.1210/jendso/bvaa046.442

SAT-014 Insulin Treatment in Human Pregnancy Mitigates an Increased Risk of Postpartum Psychological Distress with Maternal Obesity in the Absence of a Pre-Existing Mood and Anxiety Disorder

2020· article· en· W3021533363 on OpenAlexaffabout
Jessica S. Jarmasz, Alexandrea Anderson, Margaret E. Bock, Yan Jin, Peter A. Cattini, Chelsea Ruth

Bibliographic record

VenueJournal of the Endocrine Society · 2020
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineGestational diabetesObesityAnxietyPregnancyObstetricsMoodBirth weightInsulinDepression (economics)Diabetes mellitusEndocrinologyInternal medicineGestationPsychiatry

Abstract

fetched live from OpenAlex

Abstract BACKGROUND: Pregnant women with obesity are at increased risk for peripartum depression. Maternal obesity is also associated with reduced human placental lactogen (hPL) levels, and decreased hPL transcripts were reported in women with clinical depression. In addition, hPL production may be rescued in women with obesity that were subsequently diagnosed with gestational diabetes and treated with insulin (INS). Objective: Study the effect of INS treatment in pregnancy on the risk for postpartum psychological distress (PPD) in women with and without obesity. Study Design: Using data housed at the Manitoba Centre for Health Policy (2002–2017), cohorts of women (ages 15+) with a single live birth with and without obesity were developed using weight (≥85 and <65.6 kg, respectively) and an average (1.63 m) height. Pre-existing mood and anxiety disorders within 5 years preceding delivery as well as gestational hypertension were excluded. After randomly selecting 1 birth per mother, cohorts were stratified by INS treatment during the gestational period. The risk of PPD within 1 year of delivery was assessed by Poisson regression analysis. Models were adjusted for maternal age and area-level income at delivery. Results: The risk of PPD was 27% greater among women with obesity versus without (adjusted rate ratio (aRR)=1.27, 95% CI 1.16–1.4, p<0.0001). However, women with obesity treated with INS did not have a significantly different risk of PPD compared to women without obesity whether treated with INS (aRR=0.99, 95%CI 0.48–2.02, p=0.974) or not (aRR=1.16, 95%CI 0.86–1.56, p=0.328). This suggests that the risk of PPD among women with obesity may be reduced by INS treatment; however, our ability to detect a significant difference may be limited by small cohort numbers (46 women with obesity received INS in pregnancy) or confounders for receiving INS in pregnancy. Direct comparison of INS treatment within weight groups faced the same limitations but trended toward a reduction in women with obesity who received INS (aRR=0.91, 95%CI 0.68–1.22, p=0.531). The positive association between INS treatment in pregnancy and decreased risk of PPD in women with obesity was lost when pre-existing mood and anxiety disorder was not excluded. Inclusion of pre-existing diabetes in the adjusted models did not improve model fit or contribute significantly to the differences in PPD rates. Conclusions: Maternal obesity increases the risk for PPD but this risk may be reduced by gestational INS treatment in the absence of a pre-existing mood and anxiety disorders. This correlates with the decrease and increase in hPL levels reported previously with maternal obesity without and with INS treatment (for diabetes) in pregnancy, respectively. Thus, hPL levels may serve as a possible indicator of PPD risk and a potential target for gestational INS treatment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.313
Teacher spread0.294 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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