Evidence map›Paper›PMID 34938090›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2021

The Predictive Ability of Hepatic Steatosis Index for Gestational Diabetes Mellitus and Large for Gestational Age Infant Compared with Other Noninvasive Indices Among Chinese Pregnancies: A Preliminary Double-center Cohort Study.

Shuoning Song, Yanbei Duo, Yuemei Zhang, Xiaolin Qiao, Jiyu Xu, Jing Zhang, Zhenyao Peng, Yan Chen, Xiaorui Nie, Qiujin Sun and 8 more

2 registry-linked trialsAbstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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.

NCT05992974 unknown statusnot on this mapstarted 2023, after this paper: background citation

To Identify Urinary Biomarkers in the First Trimester Associated With Gestational Diabetes Mellitus [GDM] and Achieve Early Diagnosis of GDM Using Urinary Proteomic Analysis: An Observational Study

TypeobservationalSponsorPeking Union Medical College HospitalRan2023 to 2025Enrolled1,000ConditionsGestational Diabetes
NCT07682077 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Effects of a Kefir Intervention in Pregnancy on Glucose, Insulin, Gestational Diabetes Mellitus, and the Gut Microbiome and Metabolites: A Randomized Controlled Trial

TypeinterventionalSponsorUniversity of New BrunswickRan2026 to 2029Enrolled60ConditionsGestational Diabetes Mellitus (GDM), Blood Glucose, Insulin Resistance, Diabetes, Gut MicrobiomeArmsKefir
3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  12. Management of obesity across women's life course: FIGO Best Practice Advice.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2023
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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

18 authors.

Shuoning SongDepartment of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, People's Republic of China.ORCID 0000-0003-4810-4063
Yanbei DuoDepartment of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, People's Republic of China.
Yuemei ZhangDepartment of Obstetrics, Haidian District Maternal and Child Health Care Hospital, Beijing, People's Republic of China.
Xiaolin QiaoDepartment of Obstetrics, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing, People's Republic of China.
Jiyu XuCore Facility of Instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, People's Republic of China.
Jing ZhangDepartment of Laboratory, Haidian District Maternal and Child Health Care Hospital, Beijing, People's Republic of China.
Zhenyao PengDepartment of Dean's Office, Haidian District Maternal and Child Health Care Hospital, Beijing, People's Republic of China.
Yan ChenDepartment of Obstetrics, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing, People's Republic of China.
Xiaorui NieDepartment of Obstetrics, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing, People's Republic of China.
Qiujin SunDepartment of Clinical Laboratory, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing, People's Republic of China.
Xianchun YangDepartment of Clinical Laboratory, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing, People's Republic of China.
Ailing WangNational Center for Women and Children's Health, China CDC, Beijing, People's Republic of China.
Wei SunCore Facility of Instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, People's Republic of China.
Yong FuDepartment of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, People's Republic of China.
Yingyue DongDepartment of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, People's Republic of China.
Zechun LuNational Center for Women and Children's Health, China CDC, Beijing, People's Republic of China.
Tao YuanDepartment of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, People's Republic of China.
Weigang ZhaoDepartment of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the association of hepatic steatosis index (HSI) in the first trimester and the risk of gestational diabetes mellitus (GDM) as well as large for gestational age (LGA) infant in Chinese women.

methodsA total of 1082 pregnant women were included in this study. Maternal basic laboratory data, including ALT, AST, FBG, insulin, TG, and HDL-C, were tested during 6-12 weeks of gestation and anthropometric characteristics were monitored during gestation. A 75-g oral glucose tolerance test (OGTT) was conducted at 24-28 weeks of gestation. HSI, nonalcoholic fatty liver disease (NAFLD) liver fat score, triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) and triglyceride-glucose (TyG) index were calculated. Odds ratio with 95% confidence interval for subsequent risk of GDM and LGA by HSI quartiles were assessed by binary logistic regression model. The predictive ability of HSI for GDM and LGA was evaluated by the receiver operating characteristic (ROC) curve analysis and was compared with other indices.

resultsThe incidence of GDM and LGA were 22.09% (239/1082) and 10.53% (87/826). HSI was higher in GDM group than in NGT group (median, interquartile range: 30.67, 27.20-35.10 vs 27.98, 25.70-30.82,

conclusionHigher HSI was independently associated with higher risk of GDM and LGA in Chinese women. HSI in the first trimester can predict the risk of GDM and LGA.

Indexed as

gestational diabetes mellitushepatic steatosis indexlarge for gestational age infantnonalcoholic fatty liver disease

Identifiers

PMID34938090
PMCPMC8687517

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Registered trials

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.