Evidence map›Paper›PMID 39484218›Full record

ArticlePeerJ2024

The impact of maternal serum biomarkers on maternal and neonatal outcomes in twin pregnancies: a retrospective cohort study conducted at a tertiary hospital.

Hanglin Wu, Liming Yu, Zhen Xie, Hongxia Cai, Caihe Wen

Abstract read
In one paragraph

Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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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

5 authors.

Hanglin WuDepartment of Obstetrics and Gynecology, Hangzhou Women's Hospital, Hangzhou, Zhejiang, China.
Liming YuDepartment of Obstetrics and Gynecology, Hangzhou Women's Hospital, Hangzhou, Zhejiang, China.
Zhen XieDepartment of Obstetrics and Gynecology, Hangzhou Women's Hospital, Hangzhou, Zhejiang, China.
Hongxia CaiDepartment of Obstetrics and Gynecology, Hangzhou Women's Hospital, Hangzhou, Zhejiang, China.
Caihe WenDepartment of Obstetrics and Gynecology, Hangzhou Women's Hospital, Hangzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Prior prediction models used for screening preeclampsia (PE) in twin pregnancies were found to be inadequate. In singleton pregnancies, various maternal biomarkers have been shown to be correlated with negative pregnancy outcomes. However, the impact of these biomarkers in twin pregnancies remained uncertain. Methods: A retrospective cohort study was carried out on 736 twin pregnancies at a tertiary hospital in Hangzhou, China. Multivariable logistic models were employed to examine the association between levels of serological markers and the likelihood of adverse pregnancy outcomes. The final logistic model was formulated as a user-friendly nomogram. The primary outcome assessed was the occurrence of PE. Results were presented as odds ratios (ORs) with corresponding 95% confidence intervals (CIs). Results: The prevalence of PE in the study was 10.3%. When comparing women diagnosed with PE to those without, it was evident that the former group experienced a significantly higher risk of unfavorable maternal and neonatal outcomes. A multivariable logistic regression analysis revealed notable associations between various factors including maternal age, parity, gestational weight gain, a family history of hypertension, as well as levels of cholesterol, albumin, and creatinine and the risk of developing PE, with a significance level of Conclusions: In this study, we developed a user-friendly predictive model that achieves notable detection rates by incorporating maternal serum biomarker levels alongside maternal characteristics and medical history. Our findings indicate that the probability of adverse maternal outcomes increases with elevated levels of RBCs. Obstetricians should consider intensifying surveillance for these women in clinical practice.

Indexed as

BiomarkersPre-EclampsiaPregnancy OutcomePregnancy, TwinTertiary Care CentersAdultChinaFemaleHumansInfant, NewbornNomogramsPregnancyRetrospective StudiesBiomarkersMultivariable logistic modelPreeclampsiaRisk factorSerum biomarkerTwin pregnancies

Identifiers

PMID39484218
PMCPMC11526785

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.