Evidence map›Paper›PMID 37831174›Full record

ArticleActa diabetologica2024

Synergistic effect between pre-pregnancy smoking and assisted reproductive technology on gestational diabetes mellitus in twin pregnancies.

Lingyu Zhang, Yan Huang, Mingjin Zhang, Yanqi Jin

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

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 35% of its field
1 · What the graph read from it

What it found

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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.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Lingyu ZhangDepartment of Gynaecology and Obstetrics, Affiliated Matern & Child Care Hospital of Nantong University, No.399 Shiji Avenue, Chongchuan District, Nantong, 226018, Jiangsu, People's Republic of China.
Yan HuangDepartment of Gynaecology and Obstetrics, Affiliated Matern & Child Care Hospital of Nantong University, No.399 Shiji Avenue, Chongchuan District, Nantong, 226018, Jiangsu, People's Republic of China.
Mingjin ZhangDepartment of Gynaecology and Obstetrics, Affiliated Matern & Child Care Hospital of Nantong University, No.399 Shiji Avenue, Chongchuan District, Nantong, 226018, Jiangsu, People's Republic of China.
Yanqi JinDepartment of Gynaecology and Obstetrics, Affiliated Matern & Child Care Hospital of Nantong University, No.399 Shiji Avenue, Chongchuan District, Nantong, 226018, Jiangsu, People's Republic of China. yanqijindct@outlook.com.ORCID http://orcid.org/0009-0004-9512-6729
Nantong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimWomen with twin pregnancies have an increased risk of gestational diabetes mellitus (GDM). Assisted reproductive technology (ART) and pre-pregnancy smoking were both associated with GDM. However, the relationships between pre-pregnancy smoking and ART and GDM in twin pregnancies were unclear. Herein, this study aims to explore the roles of pre-pregnancy smoking and ART in GDM among women with twin pregnancies.

methodsData of women with twin pregnancies were extracted from the National Vital Statistics System (NVSS) database in 2016-2020 in this retrospective cohort study. Univariate and multivariate logistic regression analyses were used to explore the associations between pre-pregnancy smoking and ART and GDM in women with twin pregnancies. The evaluation index was odds ratios (ORs) with 95% confidence intervals (CIs). Subgroup analysis of age and BMI was also performed.

resultsA total of 19,860 (9.15%) women had GDM in our study. After adjusting for covariates, we found that receiving ART was associated with high odds of GDM [OR = 1.41, 95% CI (1.34-1.48)], while pre-pregnancy smoking combined with ART was associated with higher odds of GDM [OR = 1.66, 95% CI (1.14-2.42)]. In addition, these relationships were also found in women who aged ≥ 35 years old [OR = 1.98, 95% CI (1.14-3.44)] and with BMI ≥ 25 kg/m

conclusionPre-pregnancy smoking may further increase the risk of GDM from ART in women with twin pregnancies. In clinical, women who are ready to receive ART treatment are recommend to quit smoking, which may reduce the risk of GDM and prevent adverse pregnancy outcomes.

Indexed as

Diabetes, GestationalAdultFemaleHumansMalePregnancyPregnancy OutcomePregnancy, TwinReproductive Techniques, AssistedRetrospective StudiesRisk FactorsSmokingARTGDMNVSSPre-pregnancy smokingTwin pregnancies

Identifiers

PMID37831174
OpenAlexW4387598003

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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.