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. 2023 Dec 18;3(1):185.
doi: 10.1038/s43856-023-00393-8.

Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis

Ellen C Francis  1 , Camille E Powe  2 , William L Lowe Jr  3 , Sara L White  4 , Denise M Scholtens  5 , Jiaxi Yang  6   7   8 , Yeyi Zhu  9 , Cuilin Zhang  6   7   8   10 , Marie-France Hivert  2   11 , Soo Heon Kwak  12 , Arianne Sweeting  13 ; ADA/EASD PMDI
Collaborators, Affiliations

Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis

Ellen C Francis et al. Commun Med (Lond). .

Abstract

Background: Perinatal outcomes vary for women with gestational diabetes mellitus (GDM). The precise factors beyond glycemic status that may refine GDM diagnosis remain unclear. We conducted a systematic review and meta-analysis of potential precision markers for GDM.

Methods: Systematic literature searches were performed in PubMed and EMBASE from inception to March 2022 for studies comparing perinatal outcomes among women with GDM. We searched for precision markers in the following categories: maternal anthropometrics, clinical/sociocultural factors, non-glycemic biochemical markers, genetics/genomics or other -omics, and fetal biometry. We conducted post-hoc meta-analyses of a subset of studies with data on the association of maternal body mass index (BMI, kg/m2) with offspring macrosomia or large-for-gestational age (LGA).

Results: A total of 5905 titles/abstracts were screened, 775 full-texts reviewed, and 137 studies synthesized. Maternal anthropometrics were the most frequent risk marker. Meta-analysis demonstrated that women with GDM and overweight/obesity vs. GDM with normal range BMI are at higher risk of offspring macrosomia (13 studies [n = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [n = 20,070]; OR 2.23; 95% CI 2.00, 2.49). Lipids and insulin resistance/secretion indices were the most studied non-glycemic biochemical markers, with increased triglycerides and insulin resistance generally associated with greater risk of offspring macrosomia or LGA. Studies evaluating other markers had inconsistent findings as to whether they could be used as precision markers.

Conclusions: Maternal overweight/obesity is associated with greater risk of offspring macrosomia or LGA in women with GDM. Pregnancy insulin resistance or hypertriglyceridemia may be useful in GDM risk stratification. Future studies examining non-glycemic biochemical, genetic, other -omic, or sociocultural precision markers among women with GDM are warranted.

Plain language summary

Gestational Diabetes (GDM) is high blood sugar that develops during pregnancy and may cause complications. GDM diagnosis is centered on blood sugar levels. Despite everyone receiving standard treatment, the clinical outcomes may vary from one individual to another. This indicates a need to identify factors that may help GDM diagnosis and result in improved classification of those at greatest risk for complications. Here, we systematically analyzed all published evidence for potential markers that could identify those with GDM who have greater risk of complications. We find that high maternal weight is a risk factor for offspring born larger for their gestational age. Other promising markers were identified, but further analysis is needed before they can be applied in the clinic.

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Conflict of interest statement

The authors declare the following competing interests: C.E.P. is an Associate Editor of Diabetes Care, receives payments from Wolters Kluwer for UpToDate chapters on diabetes in pregnancy, and has received payments for consulting and speaking from Mediflix Inc. All other authors declare no competing interests.

Figures

Fig. 1
Fig. 1. PRISMA systematic review attrition diagram.
This shows the flow diagram for the number of references that were identified, screened, and included.
Fig. 2
Fig. 2. Quality assessment of the included studies by critical appraisal domain.
The risk of bias and overall quality of each study was assessed independently or in duplicate using the Joanna Briggs Institute (JBI) Critical Appraisal Tool for cohort studies, which was modified specifically for the objectives of the current systematic review. For each question, a reviewer could indicate “not applicable” (blank filled bars), “yes” (blue filled bars), “unclear” (orange filled bars), “no” (red filled bars). An answer of “yes” indicates less risk of bias and greater quality, and answer of “no” indicates a higher risk of bias and lower quality.
Fig. 3
Fig. 3. Summary odds ratio (95% CI) of macrosomia for maternal body mass index overweight/obese vs. normal or continuously.
Square represents the odds ratio on the log scale; confidence interval (CI). a It shows the odds ratio (95% CI) for the association of maternal BMI categorized in overweight/obesity vs. normal range and offspring macrosomia among 13 studies that included a total 28,763 participants. b Odds ratio for the association of continuous maternal BMI (per kg/m2) and offspring macrosomia among three studies that included 2611 participants. Abbreviations: LGA large-for-gestational age.
Fig. 4
Fig. 4. Summary odds ratio (95% CI) of large-for-gestational age for maternal body mass index overweight/obese vs. normal or continuously.
Square represents the odds ratio on the log scale; confidence interval (CI). a Odds ratio (95% CI) for the association of maternal BMI categorized in overweight/obesity vs. normal range and offspring LGA among 10 studies that included a total 20,070 participants. b Odds ratio for the association of continuous maternal BMI (per kg/m2) and offspring LGA among 10 studies that included 6113 participants. Abbreviations: LGA: large-for-gestational age.
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