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Gestational Diabetes Research and Management / Diabetes, Cardiovascular Risks, and Lipoproteins · Journal article
BMC Pregnancy and Childbirth · September 10, 2026
Encouraging direction, but not yet definitive.
This retrospective cohort demonstrates that OGTT diagnostic patterns combined with prepregnancy BMI reveal heterogeneous macrosomia risk that a binary GDM label conceals. Combined fasting and post-load abnormality (F+P) was associated with higher risk (OR 1.64, 95% CI 1.15–2.33, P=0.006), and BMI-stratified risk persisted among women with normal OGTT (0.9% in underweight to 6.0% in obese). The authors explicitly state this framework is not yet supported for individual risk prediction or clinical management and requires external validation.
Single-centre retrospective cohort study. Term singleton live births delivered in 2023–2024 at a single centre; all underwent routine OGTT screening at 24–28 weeks. Inclusion and exclusion criteria not explicitly stated.. Intervention: OGTT diagnostic patterns and prepregnancy BMI classification. Compared with: Binary GDM label (normal OGTT vs any abnormal OGTT). n = 13,560. Single centre; location not specified.
Among 13,560 newborns, 394 had macrosomia (2.9%); normal OGTT accounted for 80.4% with 2.7% prevalence, GDM 19.6% with 3.8% prevalence F+P phenotype represented 4.8% of cohort with 6.1% macrosomia prevalence (OR 1.64, 95% CI 1.15–2.33, P=0.006) Within normal OGTT group, macrosomia prevalence increased from 0.9% (underweight) to 6.0% (obese) by prepregnancy BMI
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While the F+P OGTT pattern and BMI-stratified risk gradients are descriptively interesting, clinicians should note the authors' explicit statement that this framework is not yet supported for individual risk prediction or clinical management. External validation and prospective evaluation are required before adoption into routine practice.
A single-centre retrospective cohort study identifying clinically plausible risk stratification patterns using routine OGTT and BMI, but explicitly not yet validated for individual prediction or clinical management.
As stated by the source record.
Quoted from the source exactly as published.
While the F+P OGTT pattern and BMI-stratified risk gradients are descriptively interesting, clinicians should note the authors' explicit statement that this framework is not yet supported for individual risk prediction or clinical management. External validation and prospective evaluation are required before adoption into routine practice.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
Routine oral glucose tolerance testing (OGTT) provides metabolic information related to fetal overgrowth, but results are often collapsed into a binary gestational diabetes mellitus (GDM) label. This may obscure residual risk among women with normal OGTT results and heterogeneity among those with abnormal results. We evaluated whether OGTT diagnostic patterns combined with prepregnancy body mass index (BMI) could describe residual macrosomia risk under usual care. This single-centre retrospective cohort included 13,560 term singleton live births in 2023–2024. OGTT patterns were classified as normal, isolated post-load abnormality (P-only), isolated fasting abnormality (F-only), or combined fasting and post-load abnormality (F + P). Macrosomia was birthweight ≥ 4,000 g. Models adjusted for advanced maternal age, BMI category, and parity; large for gestational age (LGA) was a supplementary outcome. Among 13,560 newborns, 394 had macrosomia (2.9%). Normal OGTT accounted for 80.4% of the cohort and had a macrosomia prevalence of 2.7%, whereas GDM accounted for 19.6% and had a prevalence of 3.8%. P-only, F-only, and F + P represented 8.6%, 6.2%, and 4.8% of the cohort, with prevalences of 2.7%, 3.4%, and 6.1%, respectively. Among women with normal OGTT results, prevalence increased from 0.9% in underweight women to 6.0% in women with obesity, and this BMI-related gradient persisted after adjustment. Among abnormal OGTT phenotypes, F + P remained associated with macrosomia (OR 1.64, 95% CI 1.15–2.33; P = 0.006). The four-category view exposed heterogeneity hidden by the binary GDM label but added little to discrimination. Supplementary LGA analyses showed increased risk for F-only and F + P. A normal OGTT result did not indicate uniformly low macrosomia risk; within this group, prepregnancy BMI further differentiated risk. Among abnormal OGTT phenotypes, F + P was associated with higher macrosomia risk under usual care. Considering OGTT patterns together with prepregnancy BMI may serve as a simple descriptive framework for characterising mid-pregnancy risk differences and for evaluating staged reassessment later in pregnancy. This framework is not yet supported for individual risk prediction or direct clinical management and requires external validation and prospective evaluation.
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