Evidence map›Paper›PMID 40265162›Full record

ArticleFrontiers in endocrinology2025

Influence of maternal lipid levels on adverse pregnancy outcomes in women with gestational diabetes mellitus.

Ru Zhao, Jun Hu, Yuanqin Li, Xuetao Chen, Qian Wang, Tingting Wu, Weihong Zhou, Yan Bi, Shanmei Shen, Zhijuan Ge

Abstract read
In one paragraph

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 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
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.

Ru ZhaoDepartment of Endocrinology, Endocrine and Metabolic Disease Medical Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Jun HuDepartment of Health Management Centre, Huadong Sanatorium, Wuxi, China.
Yuanqin LiDepartment of Endocrinology, Endocrine and Metabolic Disease Medical Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Xuetao ChenDepartment of Endocrinology, Endocrine and Metabolic Disease Medical Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Qian WangDepartment of Endocrinology, Endocrine and Metabolic Disease Medical Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Tingting WuDepartment of Endocrinology, Endocrine and Metabolic Disease Medical Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Weihong ZhouDepartment of Health Management Centre, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
Yan BiDepartment of Endocrinology, Endocrine and Metabolic Disease Medical Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Shanmei ShenDepartment of Endocrinology, Endocrine and Metabolic Disease Medical Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Zhijuan GeDepartment of Endocrinology, Endocrine and Metabolic Disease Medical Center, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to investigate the effect of mid-pregnancy lipid levels on adverse outcomes in women with gestational diabetes mellitus (GDM) under adequate glycemic control. Whether this effect is independent of factors such as blood glucose was also analyzed. Methods: We retrospectively analyzed 1,001 women with normal glucose tolerance (NGT) and 1,078 women with GDM under adequate glycemic control from 2015 to 2024. Logistic regression analysis was used to explore the relationship between blood lipids and adverse outcomes. Those with GDM were further classified according to their pre-pregnancy body mass index (BMI), gestational weight gain, glycosylated hemoglobin A1c (HbA1c), and fasting blood glucose (FBG). An interaction model between triglyceride (TG) and pre-pregnancy BMI, gestational weight gain, HbA1c, and FBG on adverse outcomes was constructed. Results: In GDM, high levels of TG were independent risk factors for preeclampsia (OR = 1.51, 95%CI = 1.18-1.93), preterm birth (OR = 1.68, 95%CI = 1.30-2.18), macrosomia (OR = 1.48, 95%CI = 1.14-1.92), postpartum hemorrhage (OR = 1.33, 95%CI = 1.10-1.61), and intrauterine fetal distress (OR = 1.68, 95%CI = 1.13-2.51). Furthermore, TG had a greater impact on GDM women than on NGT women. In addition, in GDM, high levels of TG were independent risk factors for the above adverse outcomes in the subgroups of pre-pregnancy BMI, gestational weight gain, HbA1c, and FBG (interaction Conclusions: High levels of TG promoted the occurrence of preeclampsia, preterm birth, macrosomia, postpartum hemorrhage, and intrauterine fetal distress in women with GDM. Furthermore, TG had a greater effect on adverse outcomes in GDM than in NGT women.

Indexed as

Diabetes, GestationalLipidsPregnancy OutcomeTriglyceridesAdultBlood GlucoseBody Mass IndexFemaleFetal MacrosomiaGestational Weight GainGlycated HemoglobinHumansPre-EclampsiaPregnancyPremature BirthRetrospective StudiesBlood GlucoseGlycated HemoglobinLipidsTriglyceridesadverse outcomesgestational diabetes mellituslipidspregnancyrisk factors

Identifiers

PMID40265162
PMCPMC12011850

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.