First trimester prediction of gestational diabetes mellitus: A clinical model based on maternal demographic parameters

Sweeting, Arianne; Appelblom, Heidi; Ross, Glynis P.; Wong, Jencia; Kouru, Heikki; Williams, Paul F.; Sairanen, Mikko; Hyett, Jon

doi:10.1016/j.diabres.2017.02.036

Cited by 43 publications

(46 citation statements)

References 22 publications

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“…Cohort ( n = 980) clinical characteristics and first-trimester aneuploidy and pre-eclampsia screening markers according to the presence or absence of GDM and timing of GDM diagnosis have been reported previously [6, 7]. Overall, women with GDM ( n = 248) were diagnosed at a mean of 22.7 ± 7.9 weeks’ gestation.…”

Section: Resultsmentioning

confidence: 99%

“…Overall, women with GDM ( n = 248) were diagnosed at a mean of 22.7 ± 7.9 weeks’ gestation. GDM was associated with increased maternal age and first-trimester BMI, South/East Asian ethnicity, multiparity, previous history of GDM, and family history of diabetes (all p < 0.05) (Table 1) [6]. …”

Section: Resultsmentioning

confidence: 99%

“…This was a case-control study of 980 women, described previously [6], who attended the Royal Prince Alfred Hospital (RPAH), Sydney, Australia, for combined first-trimester aneuploidy and pre-eclampsia screening at 11–13 +6 weeks’ gestation between April 2011 and May 2013, using prospectively collected maternal data and serum samples. Ethics approval was granted by the local hospital ethics committee (HREC/11/RPAH/472).…”

Section: Methodsmentioning

confidence: 99%

“…Maternal clinical parameters and first-trimester aneuploidy and pre-eclampsia screening markers were prospectively obtained at 11–13 + 6 weeks’ gestation, and methodology for data collection and measurement has been previously described [6, 7]. These included maternal body mass index (BMI), MAP, UtA PI, age, ethnicity, and parity (classified as multiparous or nulliparous if no previous pregnancies ≥24 weeks’ gestation), family history of diabetes (defined as type 2 diabetes in a first- or second-degree relative and/or sibling with GDM), previous history of GDM or macrosomia (defined as birth weight > 4,000 g) and polycystic ovarian syndrome.…”

Section: Methodsmentioning

confidence: 99%

“…We have previously demonstrated that a clinical GDM risk prediction model can accurately identify GDM in early pregnancy, with an area under the curve (AUC) of 0.88 (95% confidence interval [CI] 0.85–0.92), outperforming several other published risk prediction models and clinical risk scoring approaches [6]. Further, the addition of biomarkers routinely measured during first-trimester screening for aneuploidy and pre-eclampsia (i.e., pregnancy-associated plasma protein A [PAPP-A], free β-human chorionic gonadotropin [free hCGβ], mean arterial pressure (MAP), and uterine artery pulsatility index [UtA PI]) provided an AUC of 0.90 (95% CI 0.87–0.92) [7].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Early Pregnancy Risk Prediction Model for Gestational Diabetes Mellitus

et al. 2018

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Introduction: Accurate early risk prediction for gestational diabetes mellitus (GDM) would target intervention and prevention in women at the highest risk. We evaluated novel biomarker predictors to develop a first-trimester risk prediction model in a large multiethnic cohort. Methods: Maternal clinical, aneuploidy and pre-eclampsia screening markers (PAPP-A, free hCGβ, mean arterial pressure, uterine artery pulsatility index) were measured prospectively at 11–13⁺⁶ weeks’ gestation in 980 women (248 with GDM; 732 controls). Nonfasting glucose, lipids, adiponectin, leptin, lipocalin-2, and plasminogen activator inhibitor-2 were measured on banked serum. The relationship between marker multiples-of-the-median and GDM was examined with multivariate regression. Model predictive performance for early (< 24 weeks’ gestation) and overall GDM diagnosis was evaluated by receiver operating characteristic curves. Results: Glucose, triglycerides, leptin, and lipocalin-2 were higher, while adiponectin was lower, in GDM (p < 0.05). Lipocalin-2 performed best in Caucasians, and triglycerides in South Asians with GDM. Family history of diabetes, previous GDM, South/East Asian ethnicity, parity, BMI, PAPP-A, triglycerides, and lipocalin-2 were significant independent GDM predictors (all p < 0.01), achieving an area under the curve of 0.91 (95% confidence interval [CI] 0.89–0.94) overall, and 0.93 (95% CI 0.89–0.96) for early GDM, in a combined multivariate prediction model. Conclusions: A first-trimester risk prediction model, which incorporates novel maternal lipid markers, accurately identifies women at high risk of GDM, including early GDM.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Novel Early Pregnancy Risk Prediction Model for Gestational Diabetes Mellitus

et al. 2018

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Maternal metabolic factors and the association with gestational diabetes: A systematic review and meta‐analysis

Habibi

Mousa

Tay

et al. 2022

Diabetes Metabolism Res

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Gestational diabetes (GDM) is associated with several adverse outcomes for the mother and child. Higher levels of individual lipids are associated with risk of GDM and metabolic syndrome (MetS), a clustering of risk factors also increases risk for GDM. Metabolic factors can be modified by diet and lifestyle. This review comprehensively evaluates the association between MetS and its components, measured in early pregnancy, and risk for GDM. Databases (Cumulative Index to Nursing and Allied Health Literature, PubMed, Embase, and Cochrane Library) were searched from inception to 5 May 2021. Eligible studies included ≥1 metabolic factor (waist circumference, blood pressure, fasting plasma glucose (FPG), triglycerides, and high-density lipoprotein cholesterol), measured at <16 weeks' gestation. At least two authors independently screened potentially eligible studies. Heterogeneity was quantified using I 2 . Data were pooled by random-effects models and expressed as odds ratio and 95% confidence intervals (CIs). Of 7213 articles identified, 40 unique articles were included in meta-analysis. In analyses adjusting for maternal age and body mass index, GDM was increased with increasing FPG (odds ratios [OR] 1.92; 95% CI 1.39-2.64, k = 7 studies) or having MetS (OR 2.52; 1.65, 3.84, k = 3). Women with overweight (OR 2.17; 95% CI 1.89, 2.50, k = 12) or obesity (OR 4.34; 95% CI 2.79-6.74, k = 9) also were at increased risk for GDM.Early pregnancy assessment of glucose or the MetS, offers a potential opportunity to detect and treat individual risk factors as an approach towards GDM prevention; weight loss for pregnant women with overweight or obesity is not recommended. Systematic review registration: PROSPERO CRD42020199225.

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Trends and predictors of gestational diabetes mellitus in Chile

Garmendia

Mondschein

Montiel

et al. 2019

Intl J Gynecology & Obste

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ObjectiveTo examine the temporal trends in gestational diabetes mellitus (GDM) prevalence in Chile, and to determine the main predictors of GDM.MethodsA secondary analysis was conducted of all birth records at Hospital Dr. Sótero del Río, Chile, from January 1, 2002, to December 31, 2015. We excluded those women with pre‐existing type 2 diabetes, those with missing data, and those with unlikely data. GDM was defined as fasting glucose levels >5.55 mmol/L [>100 mg/dL] or >7.77 mmol/L [>140 mg/dL] 2 hours after glucose load in the oral glucose tolerance test. Potential predictors were selected based on prior research and ease of evaluation.ResultsFrom the original database of 100 758 records, 86 362 women were included in the final cohort. The mean GDM prevalence was 7.6% (95% CI [confidence interval] 7.5%–7.8%), increasing from 4.4% (95% CI 4.0%–4.9%) in 2002 to 13.0% (95% CI 12.0%–13.9%) in 2015. Age, education, marital status, parity, family history of type 2 diabetes, personal history of GDM, hypertension and pre‐eclampsia, alcohol consumption, smoking, and pre‐gestational nutritional status performed well in the prediction of GDM.ConclusionOne out of eight Chilean pregnant women of medium‐ to low socio‐economic status were found to develop GDM. We identified a set of easy‐to‐capture predictors in the primary health care system that may allow for the early identification of women at high‐risk for the development of GDM.

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First trimester prediction of gestational diabetes mellitus: A clinical model based on maternal demographic parameters

Cited by 43 publications

References 22 publications

A Novel Early Pregnancy Risk Prediction Model for Gestational Diabetes Mellitus

A Novel Early Pregnancy Risk Prediction Model for Gestational Diabetes Mellitus

Maternal metabolic factors and the association with gestational diabetes: A systematic review and meta‐analysis

Trends and predictors of gestational diabetes mellitus in Chile

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