Evidence map›Paper›PMID 39832960›Full record

ArticleBMJ open2025

Postpartum haemorrhage following vaginal delivery: a comprehensive analysis and development of predictive models for aetiological subgroups in Chinese women.

Jinke Li, Dandan Zhang, Hong Lin, Mengyuan Shao, Xiaoxue Wang, Xueting Chen, Yangzi Zhou, Zixuan Song

Abstract readMulticenter Study
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jinke Li *Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Dandan Zhang *Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.ORCID http://orcid.org/0000-0002-6584-5106
Hong LinDepartment of Obstetrics and Gynecology, Liaoning Maternal and Child Health Hospital, Shenyang, Liaoning, China.
Mengyuan ShaoDepartment of Obstetrics and Gynecology, Shenyang Women's and Children's Hospital, Shenyang, Liaoning, China.
Xiaoxue WangDepartment of Health Management, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Xueting ChenDepartment of Health Management, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Yangzi ZhouDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Zixuan SongDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China songzixuan666@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to dissect the aetiological subgroups of postpartum haemorrhage (PPH) that occur after vaginal delivery in women with full-term singleton pregnancies. Our goal was to craft and validate predictive models to guide clinical decision-making and optimise resource allocation.

designA retrospective cohort study.

settingShengjing Hospital of China Medical University, Liaoning Maternal and Child Health Hospital, and Shenyang Women's and Children's Hospital.

participants29 842 women who underwent vaginal delivery were enrolled in the study across three hospitals from 2016 to 2022. PRIMARY OUTCOME MEASURES: PPH, categorised into uterine atony (UA), placental factors (PF), cervical trauma (CT), and coagulation abnormalities (CA) by aetiology.

resultsThe logistic regression for overall PPH and UA-PPH showcased high discrimination (AUCs of 0.807 and 0.794, respectively), coupled with commendable calibration and DCA-assessed clinical utility, culminating in the development of a nomogram for risk prediction. The PF-PPH model exhibited a modest AUC of 0.739, while the CT-PPH and CA-PPH models demonstrated suboptimal clinical utility and calibration.

conclusionThe study identified factors associated with PPH and developed models with good performance for overall PPH and UA-PPH. The nomogram offers a valuable tool for risk prediction. However, models for PF-PPH, CT-PPH, and CA-PPH require further refinement. Future research should focus on larger samples and multicentre validation for enhanced model generalisability.

Indexed as

Delivery, ObstetricPostpartum HemorrhageAdultChinaFemaleHumansLogistic ModelsNomogramsPregnancyRetrospective StudiesRisk AssessmentRisk FactorsUterine InertiaMaternal medicinePERINATOLOGYPostpartum WomenPREVENTIVE MEDICINE

Identifiers

PMID39832960
PMCPMC11751844

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.