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Open Access 01-12-2022 | Mood Disorders | Research article

Development of multivariable models to predict perinatal depression before and after delivery using patient reported survey responses at weeks 4–10 of pregnancy

Authors: Jenna M. Reps, Marsha Wilcox, Beth Ann McGee, Marie Leonte, Lauren LaCross, Kevin Wildenhaus

Published in: BMC Pregnancy and Childbirth | Issue 1/2022

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Abstract

Background

Perinatal depression is estimated to affect ~ 12% of pregnancies and is linked to numerous negative outcomes. There is currently no model to predict perinatal depression at multiple time-points during and after pregnancy using variables ascertained early into pregnancy.

Methods

A prospective cohort design where 858 participants filled in a baseline self-reported survey at week 4–10 of pregnancy (that included social economics, health history, various psychiatric measures), with follow-up until 3 months after delivery. Our primary outcome was an Edinburgh Postnatal Depression Score (EPDS) score of 12 or more (a proxy for perinatal depression) assessed during each trimester and again at two time periods after delivery. Five gradient boosting machines were trained to predict the risk of having EPDS score >  = 12 at each of the five follow-up periods. The predictors consisted of 21 variables from 3 validated psychometric scales. As a sensitivity analysis, we also investigated different predictor sets that contained: i) 17 of the 21 variables predictors by only including two of the psychometric scales and ii) including 143 additional social economics and health history predictors, resulting in 164 predictors.

Results

We developed five prognostic models: PND-T1 (trimester 1), PND-T2 (trimester 2), PND-T3 (trimester 3), PND-A1 (after delivery 1) and PND-A2 (delayed onset after delivery) that calculate personalised risks while only requiring that women be asked 21 questions from 3 validated psychometric scales at weeks 4–10 of pregnancy. C-statistics (also known as AUC) ranged between 0.69 (95% CI 0.65–0.73) and 0.77 (95% CI 0.74–0.80). At 50% sensitivity the positive predictive value ranged between 30%-50% across the models, generally identifying groups of patients with double the average risk. Models trained using the 17 predictors and 164 predictors did not improve model performance compared to the models trained using 21 predictors.

Conclusions

The five models can predict risk of perinatal depression within each trimester and in two post-natal periods using survey responses as early as week 4 of pregnancy with modest performance. The models need to be externally validated and prospectively tested to ensure generalizability to any pregnant patient.
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Metadata
Title
Development of multivariable models to predict perinatal depression before and after delivery using patient reported survey responses at weeks 4–10 of pregnancy
Authors
Jenna M. Reps
Marsha Wilcox
Beth Ann McGee
Marie Leonte
Lauren LaCross
Kevin Wildenhaus
Publication date
01-12-2022
Publisher
BioMed Central
Published in
BMC Pregnancy and Childbirth / Issue 1/2022
Electronic ISSN: 1471-2393
DOI
https://doi.org/10.1186/s12884-022-04741-9

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