Comparison of Pregnancy Outcomes Using Different Gestational Diabetes Diagnostic Criteria and Treatment Thresholds in Multiethnic Communities between Two Tertiary Centres in Australian and New Zealand: Do They Make a Difference?

Yuen, Lili; Wong, Vincent W.; Wolmarans, Louise; Simmons, David

doi:10.3390/ijerph18094588

Cited by 4 publications

(2 citation statements)

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“…Studies evaluating the relationship between maternal BMI and adverse pregnancy outcomes tended to be retrospective hospital record cohort or case control studies relying on self-reported pre-pregnancy weight. Of the 68 studies, all but nine 10,13,20,23,30,49,50,53,[56][57][58][59] reported positive associations between maternal overweight and obesity and adverse perinatal outcomes.…”

Section: Body Mass Indexmentioning

confidence: 99%

“…Regarding maternal pre-pregnancy overweight and obesity as a precision factor, numerous studies showed associations with greater risk of cesarean delivery 56,[59][60][61][62][63][64][65][66][67][68][69] or preeclampsia/hypertensive disorders of pregnancy 16,61,63,64,67,[70][71][72][73][74][75] . Four studies reported an association with neonatal hypoglycemia [76][77][78][79] , two studies reported an association with a composite outcome of neonatal morbidity and/or admission to NICU 58,70 , and one study reported an increased risk of major congenital malformations 80 .…”

Section: Body Mass Indexmentioning

confidence: 99%

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Refining the diagnosis of Gestational Diabetes Mellitus: A systematic review to inform efforts in precision medicine

Francis

Powe

Lowe

et al. 2023

Preprint

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BackgroundAmong people with gestational diabetes mellitus (GDM), there is inter-individual variability in clinical outcomes that appears to be related to factors beyond glycemia. However, the precise factors (information on the unique pathophysiology within a person, environment, and/or context) that may help refine the diagnosis of GDM remain unclear. To determine if a precision medicine approach could refine the diagnosis of GDM, we conducted a systematic review of a variety of potential precision markers analyzed in studies among individuals with GDM.MethodsSystematic literature searches were performed in PubMed (https://pubmed.ncbi.nlm.nih.gov/) and EMBASE (https://www.embase.com) databases from inception to March 2022 for observational studies and controlled trials. Studies were included if they reported data on, and compared outcomes between, individuals with GDM. The following categories of precision markers were included in the current search: non-glycemic biochemical markers (cholesterol, insulin profiles); genetics/genomics or other -omics (proteomics, lipidomics, metabolomics, metagenomics); maternal/fetal anthropometric (eg., maternal BMI, gestational weight gain, fetal biometry ultra-sound measures); clinical risk factors (medical/familial history, prior delivery complicated by macrosomia or a large for gestational age [LGA] neonate); sociocultural or environmental modifiers (diet, smoking, race/ethnicity, socioeconomic status).ResultsWe focused on synthesizing the literature on genetics, -omics, non-glycemic biomarkers, maternal anthropometry/fetal biometry, and clinical/sociocultural risk factors. A total of 5,905 titles and abstracts were screened, 775 underwent full-text review, and 137 studies that included a total of 432,156 GDM cases were synthesized. Of the studies on non-glycemic biomarkers (n=33), lipids and insulin sensitivity/secretion indices were the two most common precision markers, with elevated maternal triglycerides and insulin resistance generally associated with greater risk of LGA and macrosomia. Studies of genetics or other -omics were scarce (n=5); however, differences in genetic variants in adiponectin or adiponutrient genes and non-coding RNAs accounted for variability in perinatal outcomes. The majority of studies (n=77) evaluated maternal anthropometry or fetal biometry as a precision marker, and these studies demonstrate that individuals with adiposity who develop GDM are at a substantially higher risk of LGA or macrosomia than those with GDM and lower adiposity. There were 49 studies evaluating GDM risk factors or sociocultural markers, with only six studies examining multiple risk factors as a composite marker. There were inconsistent findings that GDM risk factors, such as older maternal age, accounted for variation in adverse outcomes.ConclusionsOur review demonstrates that a major gap exists in studies examining non-glycemic biochemical, genetic, or other ‘omic precision markers among individuals with GDM. Given that people meeting current diagnostic criteria for GDM may have different risk profiles, our review identifies several factors (including obesity, insulin resistance, hypertriglyceridemia) that may be useful in risk stratification of GDM, setting the stage for a precision approach to its diagnosis.

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Section: Body Mass Indexmentioning

confidence: 99%

Section: Body Mass Indexmentioning

confidence: 99%

Refining the diagnosis of Gestational Diabetes Mellitus: A systematic review to inform efforts in precision medicine

Francis

Powe

Lowe

et al. 2023

Preprint

View full text Add to dashboard Cite

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

Francis,

Powe,

Lowe

et al. 2023

Commun Med

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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.

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Could different cut-off values be used for 50-gram glucose tolerance test in low and high risk groups?

Dinçgez,

Özgen,

Özgen

2024

The European Research Journal

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Objectives: There are controversies about screening strategy and cut-off levels for gestational diabetes mellitus (GDM). Here, we aimed to identify optimal cut-off values for 50-gram oral glucose tolerance testing (OGTT) in high and low risk pregnant women. Methods: A total of 500 patients who underwent two step OGTT were divided into two groups as GDM (n=31) and controls (n=469). Moreover, patients were grouped as high (n=114) and low risk (n=386) for GDM. Having≥2 risk factors such as family history of type-2 diabetes, obesity, glucosuria, previous history of GDM, macrosomia and diabetic complications were accepted as high risk. Demographic data, OGTT results, birth characteristics were recorded and compared between groups. A cut-off value for 50-gram OGTT was evaluated in low and high risk groups. Results: The 50-gram OGTT value above 140 mg/dL discriminated GDM with 100% sensitivity and 92.11% specificity in all patients (AUC=0.969, P<0.001). The prevalence of GDM was 19.3% in high and 2.3% in low risk group. The 50-gram OGTT value above 140 mg/dL discriminated GDM with 100% sensitivity and 94.57% specificity in high risk patients (AUC=0.992, P<0.001). Furthermore, 50-gram OGTT value above 149 mg/dL discriminated GDM with 100% sensitivity and 93.63% specificity in low risk patients (AUC=0.976, P<0.001). Conclusions: Although screening in low risk population is a debating issue worldwide, our local guidelines still recommend screening all pregnant women. We suggest that performing 100-gram OGTT only in patients who have higher values than 149 mg/dL in 50-gram OGTT can be an alternative screening strategy in low risk group.

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Comparison of Pregnancy Outcomes Using Different Gestational Diabetes Diagnostic Criteria and Treatment Thresholds in Multiethnic Communities between Two Tertiary Centres in Australian and New Zealand: Do They Make a Difference?

Cited by 4 publications

References 56 publications

Refining the diagnosis of Gestational Diabetes Mellitus: A systematic review to inform efforts in precision medicine

Refining the diagnosis of Gestational Diabetes Mellitus: A systematic review to inform efforts in precision medicine

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

Could different cut-off values be used for 50-gram glucose tolerance test in low and high risk groups?

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