Evidence mapPaperPMID 39963281Full record

ArticleFrontiers in endocrinology2025

Gestational diabetes mellitus in previous pregnancy associated with the risk of large for gestational age and macrosomia in the second pregnancy.

Ying Wang, Juan Yang, Yuzhen Liu, Ao Yang, Yuqing Deng, Chang Xu, Shilin Zhong

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Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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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.

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ying Wang *Center of Obstetrics and Gynecology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Juan Yang *Center of Obstetrics and Gynecology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Yuzhen Liu *Center of Obstetrics and Gynecology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Ao YangCenter of Obstetrics and Gynecology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Yuqing DengCenter of Obstetrics and Gynecology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Chang XuIntelligent Hospital Research Academy, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Shilin ZhongCenter of Obstetrics and Gynecology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Since the implementation of China's new birth policy, the incidence of large for gestational age (LGA) and macrosomia associated with gestational diabetes mellitus (GDM) has increased. It remains unclear whether a history of GDM in a previous pregnancy raises the risk of LGA or macrosomia in Chinese women planning two or more pregnancies. Aim: To analyze the association between previous GDM and the risk of LGA and macrosomia in second pregnancy. Method: A retrospective study was conducted on a cohort of 3,131 women who had experienced two consecutive singleton births. The incidences of LGA and macrosomia in the second pregnancy were compared between women with and without previous GDM. The relationship between previous GDM and the occurrence of LGA and macrosomia was analyzed using multivariate logistic regression and stratified analysis. Results: The incidence of LGA and macrosomia during the second pregnancy was significantly higher in women with previous GDM (22.67% and 10.25%, respectively) compared to those without prior GDM (15.34% and 5.06%, respectively) (P < 0.05). After adjusting for potential confounders, previous GDM was significantly associated with LGA (aOR: 1.511, 95% CI: 1.066-2.143) and macrosomia (aOR: 1.854, 95% CI: 1.118-3.076) in the second pregnancy. Stratified analysis revealed that these associations were present only in women without previous LGA, those with GDM, appropriate gestational weight gain (AGWG), non-advanced maternal age, and male newborns during the second pregnancy ( Conclusion: Previous GDM is strongly linked to LGA and macrosomia in subsequent pregnancies. However, this relationship is influenced by GWG, prior LGA history, fetal sex, and maternal age. Managing weight alone may not sufficiently reduce the risk of LGA or macrosomia for women with a history of GDM.

Indexed as

Diabetes, GestationalFetal MacrosomiaAdultBirth WeightChinaFemaleGestational AgeHumansIncidenceInfant, NewbornPregnancyRetrospective StudiesRisk Factorsbody mass indexgestational diabetes mellitusgestational weight gainlarge for gestational agemacrosomiamultipara

Identifiers

PMID39963281
PMCPMC11830583

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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.