Glycometabolic Profiles and Pregnancy Outcomes for 330 GDM Patients

330 women with gestational diabetes mellitus (GDM) and 330 healthy controls were enrolled in a 1:1 case-control study. The data characterizes four GDM subtypes defined by insulin resistance and β-cell function, comparing their clinical features and pregnancy outcomes. The dataset was authored by Junyou Su and last updated on 2026-05-19.

Use Cases

• Identify high-risk GDM subtypes for adverse pregnancy outcomes based on insulin resistance and β-cell function.
• Analyze associations between glycometabolic parameters (e.g., OGTT glucose, HbA1c) and maternal-neonatal events like cesarean delivery or preterm birth.
• Build risk prediction models for adverse outcomes using independent factors like age, pre-pregnancy BMI, and GDM subtype.
• Compare the severity of glycometabolic derangements and clinical outcomes across different GDM pathophysiological subtypes.

Strengths

• Includes data from 660 total participants (330 GDM cases and 330 healthy controls).
• Provides specific subtype distribution percentages (e.g., GDM-M subtype is 17.9% of the GDM cohort).
• Reports detailed outcome rates for the high-risk GDM-M subtype, such as an 18.6% insulin use rate and a 72.9% cesarean delivery rate.
• Contains results from multivariate logistic regression analysis, including odds ratios and confidence intervals for risk factors.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The observational, single-center design limits causal inference, as noted by the authors.

Provenance

Source

figshare, author Junyou Su.

Collection Method

Data likely originates from a 1:1 case-control clinical study.

Freshness

Last updated 2026-05-19 04:19:14; freshness should be verified.