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Cited by 336

The DOI matches its Crossref record; 78 of the 78 references it cites were found in a registry or an index.

Predictors of Postpartum Depression: A Comprehensive Review of the Last Decade of Evidence

Open access
GUINTIVANO, JERRY, MANUCK, TRACY, MELTZER-BRODY, SAMANTHA·2018·Clinical Obstetrics & Gynecology

Abstract

Postpartum depression (PPD) is one of the most frequent complications of childbirth affecting ~500,000 women annually (prevalence 10% to 15%). Despite the documented adverse outcomes for mother and child, there remains a great need to develop prospective approaches to identify women at risk. This review examines some of the best-characterized molecular and clinical risk factors for PPD. We illustrate that this is a growing literature but there remains a lack of reliable molecular predictors for PPD. Current best predictors are clinical assessments for psychiatric history and adverse life events, highlighting the need for increased depression screening across the perinatal period.

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Crossref · 10.1097/grf.0000000000000368

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Metadata

Authors
GUINTIVANO, J., MANUCK, T., & MELTZER-BRODY, S.
Venue
Clinical Obstetrics & Gynecology
Published
2018-09
Volume
61
Issue
3
Pages
591-603
ISSN
0009-9201 (ISSN-L)
OpenAlex
W2795018297
Cited by
336
References
78
FWCI
21.14
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Predictors of Postpartum Depression: A Comprehensive Review of the Last Decade of Evidence. https://app.cochat.ai/papers/10.1097/grf.0000000000000368
The paper
GUINTIVANO, J., MANUCK, T., & MELTZER-BRODY, S. (2018). Predictors of Postpartum Depression: A Comprehensive Review of the Last Decade of Evidence. Clinical Obstetrics & Gynecology. https://doi.org/10.1097/grf.0000000000000368

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.