Edinburgh Postnatal Depression Scale scores at 2‐week post‐partum may reflect those at 4‐week post‐partum: A single‐center retrospective observational study

Matsuoka, Hideki; Iwami, Shuichiro; Maeda, Marisa; Suizu, Ai; Fujii, Takaaki

doi:10.1111/jog.14540

Cited by 6 publications

(9 citation statements)

References 21 publications

(43 reference statements)

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“…This is an important study demonstrating the usefulness of the 2-week postpartum checkup in Japan from the viewpoint of PPD detection, consistent with a previous study. 12 Contrary to our expectations, our prediction models showed significantly lower predictive accuracy than previous models that used electronic health records or clinical data with additional psychological assessment (AUROC, 0.71-0.94). [18][19][20][21][22][23] Although model performance was superior to those of individual risk factors (parity: AUROC 0.588 [0.566-0.611], history of mental disorders: 0.527 [0.503-0.550], maternal age: 0.524 [0.501-0.547], and smoking status: 0.532 [0.508-0.556] in our dataset), the predictive performance was far from satisfactory for PPD prediction.…”

Section: Discussioncontrasting

confidence: 99%

“…As the importance of perinatal mental health care has become increasingly recognized, a 2-week postpartum checkup has been adopted in some parts of Japan since 2017, in addition to a 4-week postpartum regular checkup from the perspective of preventing PPD and abuse of newborns. 12 The initial assessment of maternal physical, social, and psychological wellbeing and infant nutritional status was conducted at the 2-week postpartum checkup, and women suspected of PPD were referred to psychiatrists if necessary. This is consistent with the American College of Obstetricians and Gynecologists (ACOG), which recommends an initial appointment within the first 3 weeks postpartum to address acute postpartum issues.…”

Section: Introductionmentioning

confidence: 99%

“…Traditionally, in Japan, postpartum checkups have been conducted to evaluate postpartum physical and mental states only once at 4 weeks postpartum. As the importance of perinatal mental health care has become increasingly recognized, a 2‐week postpartum checkup has been adopted in some parts of Japan since 2017, in addition to a 4‐week postpartum regular checkup from the perspective of preventing PPD and abuse of newborns 12 . The initial assessment of maternal physical, social, and psychological well‐being and infant nutritional status was conducted at the 2‐week postpartum checkup, and women suspected of PPD were referred to psychiatrists if necessary.…”

Section: Introductionmentioning

confidence: 99%

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Machine learning prediction models for postpartum depression: A multicenter study in Japan

Matsuo

Ushida

Emoto

et al. 2022

J of Obstet and Gynaecol

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Aim Postpartum depression (PPD) and perinatal mental health care are of growing importance worldwide. Here we aimed to develop and validate machine learning models for the prediction of PPD, and to evaluate the usefulness of the recently adopted 2‐week postpartum checkup in some parts of Japan for the identification of women at high risk of PPD. Methods A multicenter retrospective study was conducted using the clinical data of 10 013 women who delivered at ≥35 weeks of gestation at 12 maternity care hospitals in Japan. PPD was defined as an Edinburgh Postnatal Depression Scale score of ≥9 points at 4 weeks postpartum. We developed prediction models using conventional logistic regression and four machine learning algorithms based on the information that can be routinely collected in daily clinical practice. The model performance was evaluated using the area under the receiver operating characteristic curve (AUROC). Results In the machine learning models developed using clinical data before discharge, the AUROCs were similar to those in the conventional logistic regression models (AUROC, 0.569–0.630 vs. 0.626). The incorporation of additional 2‐week postpartum checkup data into the model significantly improved the predictive performance for PPD compared to that without in the Ridge regression and Elastic net (AUROC, 0.702 vs. 0.630 [p < 0.01] and 0.701 vs. 0.628 [p < 0.01], respectively). Conclusions Our machine learning models did not achieve better predictive performance for PPD than conventional logistic regression models. However, we demonstrated the usefulness of the 2‐week postpartum checkup for the identification of women at high risk of PPD.

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Section: Discussioncontrasting

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Machine learning prediction models for postpartum depression: A multicenter study in Japan

Matsuo

Ushida

Emoto

et al. 2022

J of Obstet and Gynaecol

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“…The scale was used to identify feelings during the past seven days to detect possible depression [13]. In addition to depression, we used the EPDS to evaluate anxiety symptoms [10,14,15].…”

Section: Questionnairesmentioning

confidence: 99%

Perinatal depression and anxiety among Chinese women during the outbreak of the COVID-19 Delta variant

Liu

Huang

et al. 2022

Preprint

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Background: This study aimed to assess the COVID-19 Delta variant impact on the incidence of depressive and anxiety symptoms in pregnant women in Guangdong Province, China, as well as to identify related risk factors.Methods: A three-week, multisite, cross-sectional study was conducted from June to July 2021 to evaluate the mental health status of pregnant women by the Edinburgh Postnatal Depression Scale. Approximately 1,450 women from 25 Guangdong hospitals were included in the study. We employed the Edinburgh Postnatal Depression Scale to assess symptoms of maternal depression and anxiety. Risk factors and relevance rates were analyzed.Results: Pregnant women who were determined to be underweight before pregnancy, primiparous, above 35 years of age, employed full-time, of middle income status, and had comfortable living arrangements were at higher risk of developing depression and anxiety during a COVID-19 outbreak.Conclusion: The occurrence of the COVID-19 Delta variant has increased the risk of mental disorders in pregnant women, which include thoughts of self-harm. Programs designed to address maternal stress as well as isolation such as constructive risk, communication, and providing psychological first aid may be particularly useful to avoid negative outcomes in pregnant women and their fetuses.

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“…It affects 10%-20% of women globally. [1][2][3] Physical, psychological, obstetric, pediatric, and socio-economic status, genetic factors, and hormonal changes are the risk factors of PPD. Especially, it is considered that hormonal changes play a role in the development of PPD.…”

Section: Introductionmentioning

confidence: 99%

Are pregnancy and postpartum oxytocin level a predictive biomarker for postpartum depression?

Çevik

Alan

2021

J of Obstet and Gynaecol

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Aim: This study aims to determine the relationship between the late pregnancy and postpartum oxytocin levels and postpartum depression (PPD) symptoms. Methods: This longitudinal study was conducted with 70 pregnant women. Data collection was performed through two interviews. While the first interview was conducted in the 30th to 38th gestational weeks, the second interview was conducted in the 4th to 12th weeks in the postpartum period. Oxytocin level measurement was performed with a saliva sample. Saliva samples were analyzed with enzyme-linked immunosorbent assay kits. Results: The prevalence of depressive symptoms in the postpartum period was found significantly higher than the prevalence in late pregnancy. Depression symptoms reached the highest level in the 12th week. The late pregnancy oxytocin level was significantly higher than the postpartum oxytocin level. A weak, negative correlation was found between PPD symptoms and the late pregnancy oxytocin level. However, when linear regression analysis was performed, it was concluded that there was a medium, negative relationship model between PPD symptoms and the late pregnancy oxytocin level. However, no relationships were found between PPD symptoms and oxytocin level. Conclusion:In conclusion, this study found that the late pregnancy oxytocin level could be a predictive biomarker for postpartum depression. Predicting the risk of PPD in the pregnancy period could provide an opportunity for early diagnosis and treatment.

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Edinburgh Postnatal Depression Scale scores at 2‐week post‐partum may reflect those at 4‐week post‐partum: A single‐center retrospective observational study

Cited by 6 publications

References 21 publications

Machine learning prediction models for postpartum depression: A multicenter study in Japan

Machine learning prediction models for postpartum depression: A multicenter study in Japan

Perinatal depression and anxiety among Chinese women during the outbreak of the COVID-19 Delta variant

Are pregnancy and postpartum oxytocin level a predictive biomarker for postpartum depression?

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