Evidence map›Paper›PMID 35321471›Full record

ArticleFrontiers in medicine2022

Development and Validation of Prognostic Nomogram for Postpartum Hemorrhage After Vaginal Delivery: A Retrospective Cohort Study in China.

Zixuan Song, Xiaoxue Wang, Yangzi Zhou, Yuting Wang, Dandan Zhang

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Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zixuan SongDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Xiaoxue WangDepartment of Health Management, Shengjing Hospital of China Medical University, Shenyang, China.
Yangzi ZhouDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Yuting WangDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Dandan ZhangDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Postpartum hemorrhage (PPH) is a common complication following vaginal delivery and in severe cases can lead to maternal death. A straightforward predictive model is required to enable prenatal evaluations by obstetricians to prevent PPH complications. Methods: Data of patients who delivered vaginally after 37 weeks of gestation were retrospectively collected from the medical database at Shengjing Hospital of China Medical University for the period 2016 to 2020. PPH was defined as blood loss of 500 mL or more within 24 h of delivery, and important independent prognostic factors were determined using univariate and multivariate logistic regression analyses to construct nomograms regarding PPH. Results: A total of 24,833 patients who delivered vaginally were included in this study. The training cohort included 22,302 patients who delivered between 2016 and 2019 and the external validation cohort included 2,531 patients who delivered during 2020. Nomogram was created using data such as age, race, occupation, parity, gestational weeks, labor time, neonatal weight, analgesic delivery, gestational diabetes mellitus, premature rupture of membranes, anemia, hypertension, adenomyosis, and placental adhesion. The nomogram has good predictive power and clinical practicality through the analysis of the area under the curve and decision curve analysis. Internal verification was performed on the nomogram for PPH, demonstrating consistency between the nomogram's predicted probability and actual probability. Conclusions: The developed and validatable nomogram is a good predictor of PPH in vaginal delivery and can be used in clinical practice to guide obstetricians to administer preventive therapies before delivery.

Indexed as

logistic regression analyses logitnomogrampostpartum hemorrhageprediction modelvaginal delivery

Identifiers

PMID35321471
PMCPMC8936128

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