Prediction Of Gestational Diabetes Research Articles

Effectiveness of first trimester maternal fat tissue measurement in prediction of gestational diabetes: a prospective cohort study.

The aim was to find a cost-effective, more practical method to be used in the early gestational weeks as an alternative to the oral glucose tolerance test (OGTT) for predicting gestational diabetes mellitus (GDM). The method selected was adipose tissue measurements made in the first trimester. The study was designed as a prospective, cohort study. Ultrasound images were used to calculate abdominal visceral (VAT) and subcutaneous adipose tissue (SAT) thicknesses of the first trimester pregnant women. Two groups were formed: those who were diagnosed with GDM and those who were not, based on the results of the OGTT performed in the same patients at 24th-28th weeks of gestation. Ultrasonographic records were examined and compared between these two groups using received operator characteristic curves and logistic regression analyses. A total of 292 pregnant women were included, of whom 21.2% were diagnosed with GDM. In the group diagnosed with GDM, SAT, VAT and total adipose tissue (TAT) values were significantly higher than the women who did not have GDM. Threshold values for SAT, VAT and TAT were 18 mm, 55 mm and 55 mm. First trimester SAT, VAT and TAT measurements of pregnant women with GDM were significantly higher than those without GDM diagnosis. Although our results showed that adipose measurements cannot be an alternative to OGTT; they may be a powerful aid in identify at-risk pregnant women, suggesting early OGTT in the first trimester.

Prediction of Gestational Diabetes by Second Trimester Complete Blood Count Derived Inflammatory Markers

Abstract Aim: To investigate the predictive ability of routine complete blood count (CBC) derived inflammatory markers on gestational diabetes mellitus (GDM) in the second trimester. Methods: A total of 181 patients, whose routine complete blood count (CBC) was measured between 14 and 24 weeks of gestation, were divided into two groups according to a 75 g OGTT results. 99 women were GDM and 82 women had normal glucose tolerance (NGT). The groups were compared regarding mean platelet volume (MPV), platelet distribution width (PDW), plateletocrit (PCT), immature granulocyte count, delta neutrophil index (DNI), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR) and Systemic Immune-Inflammation Index (SII). Results: PDW, immature granulocyte count, NLR, PLR and SII were higher in the GDM group, but no statistically significant difference was observed. Mean values of DNI were lower in women with GDM than NGT, although not statistically significant (0.84 versus 0.99, p =0.742). Conclusion: Our findings revealed that using second trimester inflammatory CBC parameters prior to screening test is not an accurate method to predict GDM.

Overweight/obesity and other predictors of gestational diabetes among Aboriginal and non-Aboriginal women in Western Australia

This population-based study investigated the association of BMI and other predictors with gestational diabetes mellitus (GDM) among Australian Aboriginal and non-Aboriginal mothers. We conducted a state-wide retrospective cohort study that included all singleton births in Western Australia (n = 134,552) between 2012 and 2015 using population health datasets linked by the Western Australian Data Linkage Branch. Associations between GDM and its predictors were estimated as adjusted relative risks (aRRs) from multivariable generalised linear models. Adjusted ratio of relative risks (aRRRs) compared RRs in Aboriginal and non-Aboriginal mothers. Adjusted population attributable fractions estimated the contribution of overweight/obesity to GDM burden, and adjusted predicted probabilities for GDM were plotted against BMI levels. The following predictors had stronger associations with GDM in Aboriginal, compared to non-Aboriginal, mothers: maternal obesity (aRR [95% CI] 3.16 [2.54–3.93]; aRRR 1.57 [1.26–1.94]), previous LGA (aRR 1.70 [1.37–2.12]; aRRR 1.41 [1.13–1.76]) and previous macrosomia (birthweight ≥ 4 kg) (aRR 1.55 [1.24–1.94]; aRRR 1.53 [1.22–1.91]). 46.1% (95% CI: 36.6–54.1) of GDM cases in Aboriginal women (23.3% in non-Aboriginal mothers, 95% CI: 21.6–25.1) were attributed to overweight/obesity. Compared to non-Aboriginal mothers, adjusted GDM probabilities were higher at all BMI levels and showed greater increase with BMI. Overweight/obesity is a key driver of GDM among Aboriginal women. Association between BMI and GDM is stronger in Aboriginal, compared to non-Aboriginal, women especially at higher BMI.

Prediction of gestational diabetes using deep learning and Bayesian optimization and traditional machine learning techniques.

The study aimed to develop a clinical diagnosis system to identify patients in the GD risk group and reduce unnecessary oral glucose tolerance test (OGTT) applications for pregnant women who are not in the GD risk group using deep learning algorithms. With this aim, a prospective study was designed and the data was taken from 489 patients between the years 2019 and 2021, and informed consent was obtained. The clinical decision support system for the diagnosis of GD was developed using the generated dataset with deep learning algorithms and Bayesian optimization. As a result, a novel successful decision support model was developed using RNN-LSTM with Bayesian optimization that gave 95% sensitivity and 99% specificity on the dataset for the diagnosis of patients in the GD risk group by obtaining 98% AUC (95% CI (0.95-1.00) and p < 0.001). Thus, with the clinical diagnosis system developed to assist physicians, it is planned to save both cost and time, and reduce possible adverse effects by preventing unnecessary OGTT for patients who are not in the GD risk group.

First-trimester glycaemic markers as predictors of gestational diabetes and its associated adverse outcomes: A prospective cohort study.

Gestational diabetes mellitus (GDM) is associated with excessive fetal growth in later gestation. Recent data suggest accelerated growth may begin before 28 weeks' gestation when GDM is typically diagnosed. The identification of pregnancies at risk of early fetal growth would enable early intervention. We assessed the use of early pregnancy HbA1c in predicting excessive fetal growth. Women were recruited at antenatal booking from a major maternity unit in the UK. HbA1c was measured at <14 weeks gestation in 1243 women at risk of GDM as defined by UK NICE risk factors of whom 1115 underwent OGTT. Women with previous GDM were excluded. Comprehensive fetal ultrasound was performed at 28 weeks' gestation alongside 75 g OGTT in 976 of these women. GDM was defined using WHO criteria. Pregnancy outcomes were extracted from the regional maternity care database. Two hundred and thirty-six women screened positive for GDM. At diagnosis, GDM pregnancies demonstrated higher adjusted fetal weight percentile than non-GDM pregnancies: (51.8 vs. 46.3, p=0.008). This was driven by increases in the fetal abdominal circumference percentile in GDM compared with non-GDM pregnancies (55.3 vs. 46.2, p=<0.001). Early pregnancy HbA1c was higher in the GDM versus non-GDM group: (35.7 mmol/mol vs. 32.9 mmol/mol p=<0.01). A threshold for predicting excessive fetal growth was not identified in this cohort. Accelerated fetal growth is evident prior to the diagnosis of GDM. There remains a need for suitable methods of early identification of pregnancies at high risk for early accelerated fetal growth due to GDM. First-trimester HbA1c was not useful in identifying these pregnancies. WHAT IS ALREADY KNOWN?: Recent research suggests excessive growth associated with GDM may begin prior to 28 weeks' gestation, when GDM is typically tested for WHAT THIS STUDY HAS FOUND?: Pregnancies affected by GDM are already subject to accelerated fetal growth in comparison to non-GDM pregnancies by way of higher estimated fetal weight and fetal abdominal circumference Neither first-trimester HbA1c nor plasma glucose was useful predictors of these outcomes WHAT ARE THE IMPLICATIONS OF THIS STUDY?: Highlights the emergence of excessive growth prior to detection of GDM Reinforces need for suitable methods of identifying such pregnancies in earlier gestation.

The role of fetal adipose tissue thicknesses measured ultrasonographically in the prediction of gestational diabetes

AIM&#x0D; This study aims to investigate whether second-trimester fetal adipose tissue components reflect glycemic control in diabetic pregnancies and their role as an auxiliary method in predicting gestational diabetes.&#x0D; MATERIALS AND METHODS&#x0D; This study was designed prospectively, cross-sectionally in 300 pregnant women 24-28 weeks of gestation between April 2020 and July 2020. The adipose tissue thickness of the humerus, femur, scapula, and abdominal circumference was examined by transabdominal ultrasound. The age, body mass index, family history of diabetes, and diabetes history in previous pregnancies of the groups were questioned.&#x0D; RESULTS&#x0D; The anterior abdominal wall adipose tissue thickness of the fetuses we included in the study was 5 ± 0.8 mm, femur adipose tissue thickness was 4 ± 0.7 mm, humerus adipose tissue thickness was 3.7 ± 0.7 mm, scapula adipose tissue thickness was 4.1 ± 2,2 mm. The total adipose tissue thickness was 16.9 ± 2.9 mm.&#x0D; A statistically significant correlation was found between femoral adipose tissue thickness (p = 0.001) and humeral adipose tissue thickness (p = 0.023) in gestational diabetes groups.&#x0D; Patients with a diagnosis of Gestational Diabetes Mellitus (n = 60) constituted the first group, patients without GDM (n =240) constituted the second group. In our independent analysis of two groups, femur and humerus adipose tissue thickness were found to be statistically significantly different between both groups (p= 0.002, p = 0.043, respectively). Other parameters did not differ significantly between groups.&#x0D; Between three groups (healthy, impaired glucose tolerance, and gestational diabetes groups). Femoral adipose tissue thickness was statistically significant among the three groups (p = 0.005). As a result of binary logistic regression, if the femoral adipose tissue thickness was above 4.1 mm, the possibility of developing GDM was observed with 63.8% sensitivity and 65% specificity.&#x0D; CONCLUSION&#x0D; In the prediction of gestational diabetes, fetus femoral adipose tissue thickness may be significant

Neck circumference as a predictor of gestational diabetes and risk of adverse outcomes in pregnancy of Brazilian woman with overweight and obesity.

To evaluate the association of neck circumference (NC) with gestational diabetes (GDM) and adverse outcomes in women with overweight and obesity. This prospective study included 132 (BMI > 25 kg/m2) pregnant women without and with GDM. Standardized questionnaire and biochemical/physical evaluation were performed during the 1st to 3rd trimester. Fifth-five women were evaluated regarding hypertension in pregnancy, type of delivery and neonatal complications (death, intensive care unit admission and hypoglycemia). Women with (n = 61) and without (n = 71) GDM had similar mean (SD) pre-gestational BMI [30.3 (4.0) vs. 29.4 (3.5) kg/m2, p = 0.16]. Women with GDM were older [32 (6) vs. 28 (6) yrs, p < 0.001] and had greater NC [36.0 (2.7) vs. 34.5 (1.8) cm, p < 0.001]. NC was similar in women with GDM diagnosed in first or third trimester [p = 0.4] and was correlated with FPG [r 0.29, p = 0.01] and systolic [r 0.28, p = 0.001] and diastolic [r 0.25, p = 0.004] blood pressure. NC was associated with GDM [OR 1.25, 95%CI 1.03-1.52] adjusted for age, physical activity, education and familiar history of diabetes. In ROC analysis, the area under the curve was 0.655 and the cut-off value of 34.5 cm had 0.70 of sensitivity and 0.51 of specificity for GDM. Women who had NC ≥ 34.5 vs. < 34.5 cm had higher frequencies of hypertension [32.3 vs. 4.2%, p = 0.01]. In a group of pregnant women with overweight or obesity, NC can be a useful tool for identifying risk of GDM and obstetric adverse outcomes.

The relationship between neck circumference and gestational diabetes mellitus in Iranian women

BackgroundThe aim of the present study was to assess the relationship between neck circumference and gestational diabetes.MethodsThis prospective study was conducted on 372 Iranian pregnant women. The criteria set by the American Diabetes Association through 2 h was used to classify subjects with regard to their gestational diabetes. At the 14–16th weeks of pregnancy, the neck circumference was measured. The maternal and fetal outcomes were measured as well.ResultsThe adjusted logistic regression revealed that neck circumference was a predictor for gestational diabetes mellitus (OR = 1.20; 95% CI = 1.06, 1.34; P = 0.002). The ROC analysis depicted that the cut-off for neck circumference in indicating gestational diabetes was 34.3 cm, with the sensitivity of 53% and the specificity of 66%.ConclusionThe findings of the present study revealed that the neck circumference of ≥34.3 cm can be deemed as a predictor of gestational diabetes in the case of Iranian pregnant women.

Metabolites involved in purine degradation, insulin resistance, and fatty acid oxidation are associated with prediction of Gestational diabetes in plasma.

Gestational diabetes mellitus (GDM) significantly increases maternal and fetal health risks, but factors predictive of GDM are poorly understood. Plasma metabolomics analyses were conducted in early pregnancy to identify potential metabolites associated with prediction of GDM. Sixty-eight pregnant women with overweight/obesity from a clinical trial of a lifestyle intervention were included. Participants who developed GDM (n = 34; GDM group) were matched on treatment group, age, body mass index, and ethnicity with those who did not develop GDM (n = 34; Non-GDM group). Blood draws were completed early in pregnancy (10-16weeks). Plasma samples were analyzed by UPLC-MS using three metabolomics assays. One hundred thirty moieties were identified. Thirteen metabolites including pyrimidine/purine derivatives involved in uric acid metabolism, carboxylic acids, fatty acylcarnitines, and sphingomyelins (SM) were different when comparing the GDM vs. the Non-GDM groups (p < 0.05). The most significant differences were elevations in the metabolites' hypoxanthine, xanthine and alpha-hydroxybutyrate (p < 0.002, adjusted p < 0.02) in GDM patients. A panel consisting of four metabolites: SM 14:0, hypoxanthine, alpha-hydroxybutyrate, and xanthine presented the highest diagnostic accuracy with an AUC = 0.833 (95% CI: 0.572686-0.893946), classifying as a "very good panel". Plasma metabolites mainly involved in purine degradation, insulin resistance, and fatty acid oxidation, were altered in early pregnancy in connection with subsequent GDM development.

The role of the platelet profile in the prediction of gestational diabetes

Objective: In our study, the results of oral glucose tolerance test (OGTT) and other hemogram parameters of pregnant women with and without gestational diabetes mellitus (GDM) were compared. The aim of our study is to investigate the benefit of these parameters in predicting GDM risk. Material and Method: The study was planned as a descriptive, retrospective and cross-sectional study. It was included 218 pregnant women who applied to the Gynecology and Obstetrics Clinic of Amasya Sabuncuoğlu Şerefeddin Training and Research Hospital between January 01, 2019 and January 31, 2020. It was examined complete blood count parameters, ultrasound findings, complete urinalysis, first trimester blood glucose, body mass index, age, and gravide parameters the patients we included in the study. The results were analyzed retrospectively and was evaluated the statistical significance relationship with gestational diabetes. Results: There was no statistically significant difference in age, body mass index (BMI), obesity status and number of gravida between the pregnant women who were examined and those without GDM (p&gt; 0.05). The hemoglobin, platelet count, mean platelet volume (MPV), mean corpuscular volume (MCV), mean corpuscular hemoglobine (MCH), and mean corpuscular hemoglobin concentration (MCHC) values, and neutrophil, lymphocyte, monocyte and basophil counts, urine density and femur length were statistically significant. There was no difference (p&gt; 0.05). No statistically significant difference was found in terms of neutrophile lymphocyte ratio (NLR), neutrophile monocyte ratio (NMR), platelet lymphocyte ratio (PLR), monocyte eosinophil ratio (MER), platelet MPV ratio (PMPVR), and platelet neutrophile ratio (PNR) values (p&gt; 0.05) Conclusion: HbA1c, hematocrit and blood glucose in the first trimester may be predictors of GDM. In addition, we think that further studies are needed in a prospective design in more patients in terms of others parameters.

Prediction of Gestational diabetes: Role of neutrophil to lymphocyte ratio at booking visit

Introduction: Gestational Diabetes Mellitus (GDM) affect up to approximately 10% of all pregnancies. Various markers of inflammation have been shown to predict the future diabetes risk and Neutrophil Lymphocyte Ratio (NLR) level is significantly correlated with metabolic syndrome criteria. However, very few studies investigated any possible association between NLR and development of GDM. Objectives• To compare the NLR among GDM group and control group.• To identify an optimal cut-off value of NLR in predicting GDM. Methods: A longitudinal observational study in all pregnant women who are in their first trimester at antenatal clinic, Teaching Hospital, Kandy for six months was carried out with a Full Blood Count at the first trimester and Oral Glucose Tolerance Test (OGTT) at the 24-28 weeks of gestation. Sample size was 361 and non-probability convenient sampling technique was applied. Results: Mean NLR value was 3.16 (SD=1.84) and the difference between GDM and non GDM mothers was not significant. Left upper most value for NLR of the ROC curve is 1.32 and when it is used as the cut off value the sensitivity is 99.6% and the specificity is 21.2%. Conclusions and recommendations: NLR positively correlates with the OGTT values done at 24-28 weeks of gestation, which can be used as a predictor at early booking visit. There is no significant difference between the mean value of participants with or without GDM. Prediction of GDM by NLR should be further studied in a well-targeted study population with wide methodology.

Emerging Protein Biomarkers for the Diagnosis or Prediction of Gestational Diabetes-A Scoping Review.

Introduction: Gestational diabetes (GDM), defined as hyperglycemia with onset or initial recognition during pregnancy, has a rising prevalence paralleling the rise in type 2 diabetes (T2DM) and obesity. GDM is associated with short-term and long-term consequences for both mother and child. Therefore, it is crucial we efficiently identify all cases and initiate early treatment, reducing fetal exposure to hyperglycemia and reducing GDM-related adverse pregnancy outcomes. For this reason, GDM screening is recommended as part of routine pregnancy care. The current screening method, the oral glucose tolerance test (OGTT), is a lengthy, cumbersome and inconvenient test with poor reproducibility. Newer biomarkers that do not necessitate a fasting sample are needed for the prompt diagnosis of GDM. The aim of this scoping review is to highlight and describe emerging protein biomarkers that fulfill these requirements for the diagnosis of GDM. Materials and Methods: This scoping review was conducted according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines for scoping reviews using Cochrane Central Register of Controlled Trials (CENTRAL), the Cumulative Index to Nursing & Allied Health Literature (CINAHL), PubMed, Embase and Web of Science with a double screening and extraction process. The search included all articles published in the literature to July 2020. Results: Of the 3519 original database citations identified, 385 were eligible for full-text review. Of these, 332 (86.2%) were included in the scoping review providing a total of 589 biomarkers studied in relation to GDM diagnosis. Given the high number of biomarkers identified, three post hoc criteria were introduced to reduce the items set for discussion: we chose only protein biomarkers with at least five citations in the articles identified by our search and published in the years 2017–2020. When applied, these criteria identified a total of 15 biomarkers, which went forward for review and discussion. Conclusions: This review details protein biomarkers that have been studied to find a suitable test for GDM diagnosis with the potential to replace the OGTT used in current GDM screening protocols. Ongoing research efforts will continue to identify more accurate and practical biomarkers to take GDM screening and diagnosis into the 21st century.

Glycated hemoglobin as a predictor for gestational diabetes

Background Gestational diabetes mellitus (GDM) may cause fetomaternal complications. GDM can be diagnosed conventionally by an oral glucose tolerance test (OGTT). Glycated hemoglobin (HbA1c) is a marker for the blood glucose level in the previous 2–3 months. Objective The aim was to assess the role of using HbA1c as a predictor for developing gestational diabetes in the second trimester. Patients and methods Fifty pregnant women were investigated by ultrasound, and HbA1c and OGTT were performed for all cases at 18–22 weeks of gestation and repeated at 32–36 weeks of gestation. Results There were statistically significant differences between women with HbA1c value less than 5.7% and those with 5.7–6.4% according to BMI, parity, and maternal weight. A positive correlation was detected between HbA1c level and development of GDM according to OGTT, which was done in the third trimester, as women with HbA1c values less than 5.7% have decreased risks of developing GDM than women with higher levels of HbA1c. Follow-up of all cases detected significant relation between level of HbA1c and neonatal birth weight, neonatal ICU admission, and APGAR score, where the pregnant women whose HbA1c less than 5.7% got infant with less birth weight and better APGAR score and the incidence of neonatal ICU admission was less in their infants. Conclusion HbA1c can be used to predict the development of GDM in second trimester. Receiver operating characteristic curve identified that the best cutoff value of HbA1c was 5.2%, with sensitivity of 75%, specificity of 80%, positive predictive value of 71.4%, negative predictive value of 82.8%, with accuracy of 87.2% for diagnosing GDM.

Prediction of Gestational Diabetes by Machine Learning Algorithms

Diabetes is the most common noncommunicable disease among people in the world due to changes in food habits. Gestational diabetes mellitus (GDM) is most frequently found in women after the birth of a baby. This article describes the prediction of GDM with various machine learning (ML) algorithms demonstrated on the Polyisocyanurate Insulation Manufacturers Association (PIMA) data set. The accuracy of various ML algorithms is validated with metrics. The significance of ML algorithms is demonstrated using a confusion matrix as well as receiver operating characteristic (ROC) and area under the curve (AUC) scores in handling the diabetes PIMA data set.

Basit Bir Tam Kan Sayımı Gestastonel Diyabetes Mellitusu Öngörebilir Mi?

Aim: To assess the role of simple complete blood count (CBC) in prediction of gestational diabetes (GDM). Materials and Methods: Pregnant women screened for GDM in 24-28 gestational weeks with a 75g-OGTT between January 2018-January 2020 were retrospectively investigated. Patients with a known systemic disease, using aspirin, low-molecular-weight heparin and steroids excluded. The assessed parameters in CBC were hemoglobin, hematocrit, red blood cells, mean corpuscular volume, mean corpuscular hemoglobin concentration, white blood cells (including neutrophils, lymphocytes, monocytes, eosinophils, basophils), platelets, platelet distribution width (PDW), mean platelet volume (MPV), red cell distribution width (RDW), nucleated red blood cell (NRBC), NRBC percentage, plateletcrit (PCT), platelet large cell ratio (P-LCR), immature granulocytes (IG) and IG percentage. Platelet mass index (PMI), neutrophil-to-platelet ratios (NPR) and lymphocyte-to-platelet ratios (LPR) were calculated. These parameters were compared between GDM patients and controls. Regression analysis was performed with the parameters that were significantly correlated with GDM. ROC curve analysis was done in order to find cut-off values. Results: RBC, WBC (all subtypes including immature granulocytes), platelet indices including PMI, NPR and LPR were all similar. Only RDW and NRBC were found to be significantly increased in GDM patients and came out to be independent predictors of GDM with maternal age and screening week. Conclusion: These findings suggest women with GDM may be accompanied with increased RDW and NRBC levels which seem to be independent predictors of this disease and these parameters may be used to monitor and evaluate the development of GDM.

Fine-tuning of Genome-Wide Polygenic Risk Scores and Prediction of Gestational Diabetes in South Asian Women

Gestational diabetes Mellitus (GDM) affects 1 in 7 births and is associated with numerous adverse health outcomes for both mother and child. GDM is suspected to share a large common genetic background with type 2 diabetes (T2D). The aim of our study was to characterize different GDM polygenic risk scores (PRSs) and test their association with GDM using data from the South Asian Birth Cohort (START). PRSs were derived for 832 South Asian women from START using the pruning and thresholding (P + T), LDpred, and GraBLD methods. Weights were derived from a multi-ethnic and a white Caucasian study of the DIAGRAM consortium. GDM status was defined using South Asian-specific glucose values in response to an oral glucose tolerance test. Association with GDM was tested using logistic regression. Results were replicated in South Asian women from the UK Biobank (UKB) study. The top ranking P + T, LDpred and GraBLD PRSs were all based on DIAGRAM’s multi-ethnic study. The best PRS was highly associated with GDM in START (AUC = 0.62, OR = 1.60 [95% CI = 1.44–1.69]), and in South Asian women from UKB (AUC = 0.65, OR = 1.69 [95% CI = 1.28–2.24]). Our results highlight the importance of combining genome-wide genotypes and summary statistics from large multi-ethnic studies to optimize PRSs in South Asians.

Predictors of Gestational Diabetes Among Women Living in Food Deserts [30D

INTRODUCTION: Gestational diabetes mellitus (GDM) is associated with many adverse maternal and fetal outcomes. The aim of this study is to identify the relationship between GDM and access to affordable grocery stores. METHODS: This is a retrospective review of patients delivering at a single institution. Food insecurity was determined using patient address overlaid with USDA Food Access Research Atlas. Patients living &gt;0.5 miles from a supermarket were identified as living in a food desert (FD). GDM clinical data was compared to FD data using chi square, regression analyses. RESULTS: Of 744 patients meeting inclusion criteria, 74 (9.94%) were diagnosed with GDM during their current pregnancy with 2.55% having a previous history of GDM. 517 patients lived in FD and were more likely to be multiparous and of minority race. 60.8% (45/74) of patients diagnosed with GDM during the current pregnancy lived in a FD. The frequency of GDM in women living in FDs was lower than those in Food Secure (FS) tracts (0.09% vs 1.2%, P=.1). Women living in FDs with GDM experienced greater rates of chronic hypertension than those in FS areas (15.2% vs 10.3%, P=.002). Higher order multiple gestation, advanced maternal age, preeclampsia with severe features, and history of GDM were significant predictors for GDM in women living in FD (P&lt;.05). CONCLUSION: Women living in food deserts are not at an increased risk for GDM but are for having chronic hypertension if they have GDM compared to those living in FS.

The value of mid-trimester fetal liver length measurement in prediction of gestational diabetes in Iraqi women

Background. Gestational diabetes (GD) is a hyperglycaemic state specific to pregnancy. A well-tolerated, quick and minimally-invasive method for the early detection of GD in pregnancy is lacking. Objective. To evaluate the correlation between the mid-trimester length of the fetal liver and GD. Methods. A prospective study was conducted at the National Endocrine and Diabetic Center, College of Medicine, Al-Mustansiriya University, Iraq and the Obstetric and Gynecological Department at Al-Yarmouk Teaching Hospital, Iraq, from September 2016 to September 2018. One-hundred-and-twenty singleton pregnant women at high risk for gestational diabetes mellitus (GDM) were recruited. An ultrasound scan was performed at 23 weeks’ gestation followed by a 75 g oral glucose tolerance test (OGTT) at 24 weeks. A correlation was assessed between the mid-trimester fetal liver length (FLL) measurement and the OGTT. Results. Mean (SD) FLL values were significantly higher among GDM patients v. healthy pregnant females respectively: 37.2 (3.4) v. 33.1 (2.7); p &lt;0.001. Univariate analysis showed that FLL in GDM group was 1.6 times the non-GDM group (odds ratio (OR) 1.6; 95% confidence interval (CI) 1.31 - 1.96). There was no significant change after adjustment for parity and cumulative risk factors. Based on the above, FLL is an independent predictor for GDM (OR 1.6; 95% CI 1.30 - 1.96; p &lt;0.05). Conclusion. FLL measurement by ultrasound at 23 weeks’ gestation is a feasible alternative to OGGT for the early detection of GDM in high-risk patients

First-trimester fasting glycemia as a predictor of gestational diabetes (GDM) and adverse pregnancy outcomes.

Studies to prevent gestational diabetes (GDM) have shown the best results when lifestyle measures have been applied early in pregnancy. We aimed to investigate whether first-trimester fasting plasma glucose (FPG) could predict GDM risk and adverse pregnancy outcomes. A retrospective analysis of prospectively collected data from singleton pregnancies who were attended at our hospital between 2008 and 2018 (n = 27,198) was performed. We included patients with a recorded first-trimester FPG and complete pregnancy data (n = 6845). Patients under 18, with pregestational diabetes or reproductive techniques, were excluded. First-trimester FPG was evaluated as a continuous variable and divided into quartiles. GDM was diagnosed by NDDG criteria. The relationship between first- and second-trimester glucose > 92mg/dL was also investigated. The relationship between FPG and pregnancy outcomes was assessed in 6150 patients who did not have GDM. Maternal age was 34.2 ± 3.9years, BMI 23.1 ± 3.7kg/m2 and mean FPG 83.0 ± 7.3mg/dL. Glucose quartiles were: ≤ 78, 79-83, 84-87 and ≥ 88mg/dL. First-trimester FPG predicted the risk of GDM (7%, 8%, 10.2% and 16% in each quartile, p < 0.001) and the risk of second-trimester glucose > 92mg/dL (2.6%, 3.8%, 6.3% and 11.4% in each quartile, p < 0.001). FPG was significantly associated with LGA (8.2%, 9.3%, 10% and 11.7% in each quartile, p = 0.011) but not with other obstetrical outcomes. In a multivariate analysis including age, BMI, tobacco use, number of pregnancies and weight gained during pregnancy, first-trimester FPG was an independent predictor of LGA. First-trimester FPG is an early marker of GDM and LGA.

232: Utility of routine dipstick urinalysis for glucose screening as a predictor for gestational diabetes

232: Utility of routine dipstick urinalysis for glucose screening as a predictor for gestational diabetes