Evidence map›Paper›PMID 42453500›Full record

ArticleFrontiers in endocrinology2026

Trimester-specific gestational weight gain and adverse outcomes in GDM women: a retrospective cohort study.

Pei Yuan, Jing Huang, Jiangfan Wan, Lili Yu, Jialin Li, Bin Huang, Na Li, Hongwei Wei, Lin Kong, Jie Qin

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Associations ofBiomolecules · 2026
    Article
  2. Article
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

10 authors.

Pei Yuan *Network and Information Center, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Jing Huang *Department of Obstetrics, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Jiangfan Wan *Department of Reproductive Medicine, The Reproductive Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Lili YuDepartment of Obstetrics, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Jialin LiNetwork and Information Center, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Bin HuangNetwork and Information Center, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Na LiBirth Defects Prevention and Control Institute, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Hongwei WeiDepartment of Obstetrics, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Lin KongDepartment of Obstetrics, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Jie QinBirth Defects Prevention and Control Institute, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders during pregnancy and is associated with an increased risk of multiple adverse pregnancy outcomes (APOs). Gestational weight gain (GWG) is an important indicator for disease monitoring and intervention; however, evidence regarding the associations between trimester-specific GWG patterns stratified by pre-pregnancy body mass index (BMI) and APOs among Chinese women with GDM remains limited. Materials and methods: Retrospective cohort study of 8, 562 singleton GDM pregnancies delivered at Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region (Feb 2021-Sep 2025). Women were classified into underweight, normal-weight, overweight, and obesity groups by pre-pregnancy BMI. GWG in early pregnancy, before Oral Glucose Tolerance Test (OGTT), and after OGTT was categorized as inadequate, adequate, or excessive per National Health Commission guidelines for GDM. Multivariable logistic regression with Benjamini-Hochberg false discovery rate (FDR) correction and generalized additive models (GAM) were used to assess associations and nonlinear relationships with APOs. Results: The associations between GWG and APOs differed significantly across pre-pregnancy BMI categories. Specifically, excessive GWG before OGTT diagnosis was associated with an increased risk of LGA among normal-weight and overweight women (aOR 1.71, 95% CI 1.38-2.13; and aOR 1.72, 95% CI 1.26-2.37, respectively). Excessive GWG after OGTT diagnosis was associated with an increased risk of preeclampsia (aOR 4.06, 95% CI 2.69-6.12; and aOR 2.49, 95% CI 1.46-4.24, respectively). In addition, excessive GWG before OGTT diagnosis was associated with a lower risk of SGA (aOR 0.39, 95% CI 0.25-0.62) in women with underweight. In women with obesity, no significant associations were observed between GWG and APOs, although the directional trends were generally consistent with those in the overweight group. GAM analyses further supported nonlinear associations between GWG and several APOs. Conclusion: Stage-specific GWG patterns in GDM pregnancies showed heterogeneous associations with APOs across pre-pregnancy BMI categories. These findings suggest that weight management strategies tailored to both pre-pregnancy BMI and gestational stage may help optimize pregnancy outcomes in women with GDM.

Indexed as

Diabetes, GestationalGestational Weight GainPregnancy OutcomePregnancy TrimestersAdultBody Mass IndexChinaFemaleGlucose Tolerance TestHumansInfant, Large for Gestational AgeObesityOverweightPregnancyRetrospective Studiesadverse pregnancy outcomesgeneralized additive model (GAM)gestational diabetes mellitusgestational weight gainpre-pregnancy body mass index

Identifiers

PMID42453500
PMCPMC13364531

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.