Detection Of Gestational Diabetes Mellitus Research Articles

Study on the predictive value of serum hypersensitive C-reactive protein, homocysteine, fibrinogen, and omentin-1 levels with gestational diabetes mellitus

Objective: To investigate whether hypersensitive C-reactive protein (Hs-CRP), homocysteine, fibrinogen, and omentin-1 could predict gestational diabetes mellitus (GDM) risk. Methods: Case–control study was conducted at Hengshui People’s Hospital. The GDM group included data about 150 patients aged between 22 and 35 years in 24–28 weeks. An equivalent comparative control group without GDM was composed of the same pool of patients. Body mass index (BMI), total cholesterol (TC), triglyceride, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), oral glucose tolerance test (OGTT) 0–2h, hs-CRP, homocysteine, fibrinogen, and omentin-1 levels were studied in the serum samples of research groups. Univariate logistic regression analysis was used to explore the risk factors of GDM. The area under the curve (AUC) was calculated by the receiver operating characteristic curve (ROC) to analyze the predictive values. Results: Hs-CRP, homocysteine, and fibrinogen in GDM group were significantly higher than those in non-GDM group. Omentin-1 were significantly lower than those in non-GDM group. Logistic regression showed that hs-CRP, homocysteine, fibrinogen, and omentin-1 were risk factors for GDM. The AUC of the established GDM risk prediction model was 0.977, and the sensitivity and specificity were 92.10% and 98.70%, respectively; which were greater than that of hs-CRP, homocysteine, fibrinogen, and omentin-1 alone. Conclusions: Hs-CRP, homocysteine, fibrinogen, and omentin-1 in pregnancy have important clinical value for the prediction of GDM. We used these laboratory indications to establish a GDM risk prediction model that allows for early detection and treatment of GDM, lowering the morbidity of maternal and infant complications.

Proteins and metabolites fingerprints of gestational diabetes mellitus forming protein-metabolite interactomes are its potential biomarkers.

Gestational diabetes mellitus (GDM) is a consequence of glucose intolerance with an inadequate production of insulin that happens during pregnancy and leads to adverse health consequences for both mother and fetus. GDM patients are at higher risk for preeclampsia, and developing diabetes mellitus type 2 in later life, while the child born to GDM mothers are more prone to macrosomia, and hypoglycemia. The universally accepted diagnostic criteria for GDM are lacking, therefore there is a need for a diagnosis of GDM that can identify GDM at its early stage (first trimester). We have reviewed the literature on proteins and metabolites fingerprints of GDM. Further, we have performed protein-protein, metabolite-metabolite, and protein-metabolite interaction network studies on GDM proteins and metabolites fingerprints. Notably, some proteins and metabolites fingerprints are forming strong interaction networks at high confidence scores. Therefore, we have suggested that those proteins and metabolites that are forming protein-metabolite interactomes are the potential biomarkers of GDM. The protein-metabolite biomarkers interactome may help in a deep understanding of the prognosis, pathogenesis of GDM, and also detection of GDM. The protein-metabolites interactome may be further applied in planning future therapeutic strategies to promote long-term health benefits in GDM mothers and their children.

The relationship between the two endocrine pathologies: subclinical gestational hypothyroidism and gestational diabetes mellitus

BACKGROUND: Over the past decade, gestational diabetes mellitus has become of increasing medical and social importance. It happens due to its increased prevalence and due to its negative impact on pregnancy and long-term metabolic disorders in the mother and fetus.
 AIM: The aim of this study was to assess the relationship between subclinical gestational hypothyroidism and gestational diabetes mellitus, the two most common endocrine pathologies in pregnancy.
 MATERIALS AND METHODS: We studied 200 medical records of pregnant women. The main group included 133 patients with subclinical gestational hypothyroidism, and the control group consisted of 67 women without endocrine pathology. The diagnosis of gestational diabetes mellitus was made based on the Ministry of Health of the Russian Federation clinical guidelines criteria. The diagnosis of subclinical hypothyroidism was made based on the thyroid-stimulating hormone level above 2.5 IU/ml in combination with an increased titer of antithyroid antibodies or above 4.0 IU/ml in the absence of any thyroid disorder. Statistical analysis was carried out using the StatTech v.2.1.0 program (Stattech Ltd, Russia).
 RESULTS: The prevalence of hypothyroidism was higher among women with family history of diabetes mellitus. The chances of developing gestational diabetes mellitus increased by 9.706 times in the presence of hypothyroidism, by 1.077 times with an increase in age by one full year at the time of seeing the doctor, and by 1.023 times with an increase in weight before pregnancy by one kilogram. The thyroid-stimulating hormone level of more than 2.7 IU/ml predicted the development of gestational diabetes mellitus with a sensitivity of 71.4% and a specificity of 63.1%.
 CONCLUSIONS: Subclinical gestational hypothyroidism and gestational diabetes mellitus are interrelated endocrine disorders with common pathophysiological predictors. Among women with a normal body mass index, subclinical gestational hypothyroidism is a more significant risk factor for gestational diabetes mellitus than an increase in age or body weight. A certain threshold level of thyroid-stimulating hormone (more than 2.7 IU/ml) in the first trimester increases the chances of developing gestational diabetes mellitus and should be considered as a signal for timely prevention and detection of gestational diabetes mellitus.

Risk factor-based screening compared to universal screening for gestational diabetes mellitus in marginalized Burman and Karen populations on the Thailand-Myanmar border: An observational cohort.

Background: Gestational diabetes mellitus (GDM) contributes to maternal and neonatal morbidity. As data from marginalized populations remains scarce, this study compares risk-factor-based to universal GDM screening in a low resource setting. Methods: This is a secondary analysis of data from a prospective preterm birth cohort. Pregnant women were enrolled in the first trimester and completed a 75g oral glucose tolerance test (OGTT) at 24-32 weeks' gestation. To define GDM cases, Hyperglycaemia and Adverse Pregnancy Outcomes (HAPO trial) criteria were used. All GDM positive cases were treated. Sensitivity and specificity of risk-factor-based selection for screening (criteria: age ≥30y, obesity (Body mass index (BMI) ≥27.5kg/m 2), previous GDM, 1 st degree relative with diabetes, previous macrosomia (≥4kg), previous stillbirth, or symphysis-fundal height ≥90th percentile) was compared to universal screening using the OGTT as the gold standard. Adverse maternal and neonatal outcomes were compared by GDM status. Results: GDM prevalence was 13.4% (50/374) (95% CI: 10.3-17.2). Three quarters of women had at least one risk factor (n=271 women), with 37/50 OGTT positive cases correctly identified: sensitivity 74.0% (59.7-85.4) and specificity 27.8% (3.0-33.0). Burman women (self-identified) accounted for 29.1% of the cohort population, but 38.0% of GDM cases. Percentiles for birthweight (p=0.004), head circumference (p=0.002), and weight-length ratio (p=0.030) were higher in newborns of GDM positive compared with non-GDM mothers. 21.7% (75/346) of newborns in the cohort were small-for-gestational age (≤10 th percentile). In Burman women, overweight/obese BMI was associated with a significantly increased adjusted odds ratio 5.03 (95% CI: 1.43-17.64) for GDM compared with normal weight, whereas in Karen women, the trend in association was similar but not significant (OR 2.36; 95% CI 0.95-5.89). Conclusions: Risk-factor-based screening missed one in four GDM positive women. Considering the benefits of early detection of GDM and the limited additional cost of universal screening, a two-step screening program was implemented.

Study of altered gut microbial dynamics and their association with gestational diabetes mellitus

The human gastrointestinal system is home to billions of different microbial species that coexist peacefully with the host. Age, diet, and environment affect gut microbial structure and diversity. Bacteroidetes and Firmicutes are the main gut microbial groups in humans. Human physiology is greatly affected by gut microbial metabolism and host–microbe interactions. Gestational diabetes mellitus (GDM) women have a different gut microbial makeup. However, whether these microbial changes in the stomach may be detected before the diagnosis of GDM remains unknown. This study aims to study the dynamics of gut microbe in healthy and GDM women and analyze the potential biomarkers for early detection of GDM in pregnant women. In this study, gut microbial variations have been characterized and their relationship is evaluated with GDM development. A large multi-taxon microbial shift between GDM and normal cases was evident, indicating that few microbial disruptions from early to mid-pregnancy were related to the later development of GDM. Results of linear discriminant analysis (LDA) show the variable relative abundance of 13 taxonomic groups (at the family level) between the GDM and normal groups. Moreover, 8 taxonomic groups (at the family level) were found to be present in the GDM group only. The results contribute to the gut microbiota’s potential relevance as a biomarker for the early detection of GDM.

PREDICTIVE VALUE OF NEUTROPHIL TO LYMPHOCYTE RATIO (NLR) IN EARLY DETECTION OF GESTATIONAL DIABETES MELLITUS (GDM) AMONG PREGNANT WOMEN IN FIRST TRIMESTER OF PREGNANCY

Background & Objective: A substantial number of pregnant women develop gestational diabetes mellitus (GDM). Various biomarkers are being used to diagnose gestational diabetes mellitus. Early detection of GDM can done by using inflammatory markers like neutrophil-to-lymphocyte ratio (NLR) and the platelet- to-lymphocyte ratio (PLR) that are rapid, inexpensive and easy to use in different clinical setting. The objective of this study was to evaluate diagnostic accuracy of raised neutrophil to lymphocyte ratio for detection of gestational diabetes mellitus taking OGTT as gold standard.
 Methods: This was a cross-sectional study held in Department of Obstetrics and Gynecology CMH Lahore from November, 2018 –May, 2020. After approval from hospital ethical review committee and taking an informed consent, 473 pregnant women enrolled in first trimester between age 18-35 years, fulfilling the inclusion criteria were included whereas known diabetics, patients with cardiovascular disorders, previous history of GDM were excluded. Blood samples in sterilized manner were drawn and sent to hospital laboratory for analysis of NLR. Then they were screened during 24-28 weeks of gestation for diagnosis of gestational diabetes mellitus on OGGT. The females were labelled for positive NLR and GDM as per operational definition. Diagnostic accuracy of NLR was calculated for development of gestational diabetes mellitus.
 Results: Mean age of females was 26.72 ± 4.90 years and mean gestational age was 15.50 ± 1.67 weeks. 94(19.9%) females who had raised neutrophil to lymphocyte ratio while 397(80.1%) females had normal neutrophil to lymphocyte ratio and there were 90(19%) females who had gestational diabetes mellitus while rests of 383(81%) did not have gestational diabetes mellitus. The sensitivity, specificity, positive predictive value, negative predictive value and overall diagnostic accuracy of NRL was 95.56%, 97.91%, 91.49%, 98.94% and 97.46%, respectively.
 Conclusion: The study concluded that raised neutrophil to lymphocyte ratio is significantly high among gestational diabetes mellitus and NLR has a high diagnostic accuracy for predicting gestational diabetes mellitus.

GDM-PREP: A Rule-Based Technique to Enhance Early Detection of Gestational Diabetes Mellitus

GDM-PREP: A Rule-Based Technique to Enhance Early Detection of Gestational Diabetes Mellitus

Evaluation of First Trimester Fasting Blood Glucose, HOMA-IR and HbA1c in Prediction of Gestational Diabetes Mellitus in Non-Obese Pregnant Women: A Retrospective Study

Aim: Gestational Diabetes Mellitus (GDM) is the most common endocrine complication in pregnancy with fetomaternal comorbidities. It is aimed to evaluate fasting blood glucose (FBG), homeostasis model assessment of insulin resistance (HOMA-IR), and hemoglobin A1c (HbA1c) values in the first trimester in non-obese pregnant women for early detection of GDM.
 Material and Methods: Pregnant women with first-trimester FBG, HOMA-IR, HbA1c values, and second-trimester OGTT results were scanned from the hospital database. First-trimester height, weight, age and gestational weeks were also recorded. The presence of Body Mass Index (BMI) over 30 kg/m2, chronic and systemic disease and history of G(DM) were not included in the study. ROC analysis was performed on FBG, HOMA-IR, and HbA1c.
 Results: This retrospective study was conducted between 01/01/2021, and 01/01/2022 in Tuzla State Hospital Gynecology and Obstetrics Clinic. 131 pregnant women who met the inclusion criteria were reached. Twenty of pregnant women were evaluated as GDM positive(+). Age, height, weight, BMI, gestational week, and nulliparity were observed to be similar between the groups. FBG, insulin, HOMA-IR, and HbA1c values were higher in the group with GDM. As a result of ROC analysis, those with an FBG value of 88,5 mg/dl (sensitivity 68.2%, specificity 68.2%), a HOMA-IR value of 2.24 (sensitivity 63.6%, specificity 64.5%), and a HbA1c (sensitivity 68.2%, specificity 66.7%) value of over 5.25% were observed to be at risk for GDM.
 Conclusion: It has shown that pregnant women with high first trimester FBG, HOMA-IR and HbA1c have a high risk for GDM and can be used as a predictor of GDM.

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.

Association of interpregnancy interval and gestational diabetes mellitus

Objective To evaluate the association between interpregnancy interval (IPI) and risk for gestational diabetes mellitus (GDM). Methods We conducted a retrospective cohort study among singleton, non-anomalous, live birth pregnancies of 5,705,812 pregnant individuals in the United States from 2016 to 2018. We examined IPI of 4–<6 months, 6–11 months, 12–17 months, 24–35 months, 36–47 months, 48–59 months, 60–71 months, and ≥72 months in comparison to the reference interval of 18–23 months in relation to risk for GDM. We used logistic regression to evaluate the association between IPI and risk for GDM. Results There is a significantly increased risk for GDM associated with IPIs of 6–11 months and 12–17 months compared to the reference of 18–23 months (adjusted Odds Ratio [aOR] 1.05, 95% CI: 1.03–1.07; aOR 1.02, 95% CI: 1.01–1.03). The risk for GDM is greater for longer IPIs (36–47 months aOR 1.10, 95% CI: 1.05–1.08; 48–59 months aOR 1.11, 95% CI: 1.09–1.13; 60–71 months aOR 1.14, 95% CI: 1.12–1.16; ≥72 months aOR 1.31, 95% CI: 1.30–1.33). Conclusion Our findings support the growing evidence that shorter and longer IPI increase the risk of GDM in pregnant individuals. Screening guidelines for detection of GDM may need to be re-evaluated and updated to include longer IPIs (≥36 months) as a risk factor for earlier screening prior to current recommendation of 24 weeks gestational age.

Association of Early Pregnancy Free and Total Triiodothyronine With the Subsequent Risk of Gestational Diabetes Mellitus

ObjectiveTo estimate the association of free triiodothyronine (FT3) and total triiodothyronine (TT3) in early pregnancy and subsequent gestational diabetes mellitus (GDM) risk and define appropriate TT3 thresholds for GDM screening. MethodsThis investigation is a hospital-based cohort study of pregnant women submitted to a universal thyroid function test before 24 weeks of gestation. GDM was diagnosed according to a 75-g oral glucose tolerance test. The association of maternal high FT3 and TT3 levels in early pregnancy with the risk of GDM was estimated using logistic regression. The potential nonlinear association was probed by the restricted cubic spline curve method. ResultsA total of 27 184 pregnant women and 3073 GDM cases were included in the analysis. FT3 and TT3 were associated with an increased subsequent risk of GDM in a nonlinear fashion. The adjusted odds ratios were 1.59 (95% confidence interval, 1.50-1.68) and 2.80 (95% confidence interval, 2.46-3.18) for FT3 and TT3 continuous levels, respectively. Associations were strong in euthyroid women, showed heterogeneity in women with mild thyroid dysfunction, and lacked in patients with overt hypothyroidism and hyperthyroidism. The TT3 thresholds of 1.5 and 2.0 ng/mL between 7 and 12 weeks of gestation and 1.6 and 2.1 ng/mL for 13 to 23 weeks of gestation effectively distinguished the subsequent risk of GDM. ConclusionThe increased FT3 and TT3 levels in early pregnancy were associated with a subsequent higher risk of GDM. These findings provide measures for early detection and potential prevention of GDM.

Perspectives from metabolomics in the early diagnosis and prognosis of gestational diabetes mellitus.

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnant women. The early detection of GDM provides an opportunity for the effective treatment of hyperglycemia in pregnancy, thus decreasing the risk of adverse perinatal outcomes for mothers and newborns. Metabolomics, an emerging technique, offers a novel point of view in understanding the onset and development of diseases and has been repeatedly used in various gestational periods in recent studies of GDM. Moreover, metabolomics provides varied opportunities in the different diagnoses of GDM from prediabetes or predisposition to diabetes, the diagnosis of GDM at a gestational age several weeks earlier than that used in the traditional method, and the assessment of prognosis considering the physiologic subtypes of GDM and clinical indexes. Longitudinal metabolomics truly facilitates the dynamic monitoring of metabolic alterations over the course of pregnancy. Herein, we review recent advancements in metabolomics and summarize evidence from studies on the application of metabolomics in GDM, highlighting the aspects of the diagnosis and differential diagnoses of GDM in an early stage. We also discuss future study directions concerning the physiologic subtypes, prognosis, and limitations of metabolomics.

The diagnostic model for early detection of gestational diabetes mellitus and gestational diabetic nephropathy.

BackgroundGestational diabetes mellitus (GDM) and gestational diabetic nephropathy (GDN) have become an increasingly serious problem worldwide, which can cause a large number of adverse pregnancy consequences for mothers and infants. However, the diagnosis of GDM and GDN remains a challenge due to the lack of optimal biomarkers, and the examination has high requirements for patient compliance. We aimed to establish a simple early diagnostic model for GDM and GDN.MethodsWe recruited 50 healthy pregnant (HP), 99 GDM patients, 99 GDN patients at Daping Hospital. Renal function indicators and blood cell indicators were collected for all patients.ResultsCompared with HP, GDM, and GDN patients exhibited significantly higher urea/creatinine ratio and NEU. The diagnostic model1 based on the combination of urea/creatinine ratio and NEU was built using logistic regression. Based on receiver operating characteristic curve analysis, the area under the curve (AUC) of the diagnostic model was 0.77 (0.7, 0.84) in distinguishing GDM from HP, and the AUC of the diagnostic model was 0.94 (0.9, 0.97) in distinguishing GDN from HP. Meanwhile, the diagnostic model2 based on the combination of β2‐mG, PLT, and NEU in GDM and GDN patients was built using logistic regression, and the area under the ROC curve (AUC ROC) was 0.79 (0.73, 0.85), which was larger than the individual biomarker AUC.ConclusionOur study demonstrated that the diagnostic model established by the combination of renal function indicators and blood cell indicators could facilitate the differential diagnosis of GDM and GDN patients.

Visfatin as a Biomarker for Early Detection of Gestational Diabetes Mellitus

Objective: The current study aims to determine whether an increase in visfatin level resulted in Gestational Diabetes Mellitus (GDM) in pregnant females. Study Design: Retrospective Study Place and Duration: Department of Medicine, Dr. Ziauddin Hospital, North Nazimabad, Karachi, From November 2021 to April 2022. Methods: In this study, 83 pregnant females aged 18-46 years were inducated. After obtaining informed written consent, detailed demographic data were recorded. Gestational age and gravidity among all females were recorded. Previous history and frequency of GDM were assessed. Blood samples were taken to determine the concentration of visfatin and glucose levels. SPSS 24.0 was used to analyze all data. Results: In this study, the mean age was 29.11±8.42 years, and the mean BMI was 26.2±3.32 kg/m2. The mean gestational age was 34.11±4.33 weeks. Most of the cases were from rural areas and had poor socio-economic status. We found that 44 (53.01%) subjects had gestational diabetes mellitus while 39 (46.9%) had no diabetes. The visfatin level in patients with gestational diabetes was higher, 4.2±7.124, compared to non-diabetes cases, 1.4±1.432, with a p-value&lt;0.003. Conclusion: Ultimately, we determined that visfatin levels were considerably elevated in gestational diabetes mellitus beginning in the first trimester of pregnancy. An innovative biomarker for GDM detection is increased visfatin levels during pregnancy. Keywords: Visfatin, Gestational Diabetes, Pregnant Females

Systematic Literature Review: Metode Deteksi Dini Diabetes Mellitus Gestasional

Gestational Diabetes Mellitus (GDM) is one of the medical complications of pregnancy that can cause short-term and long-term risks for the mother and fetus if not detected early and treated appropriately. This study aims to find, select, assess, extract, and synthesize data from several articles on the method of early detection of GDM that can be carried out by health workers. This study uses a systematic literature review method with the PICO framework. Search articles using PubMed and Science Direct databases with keywords and Boolean operators in this study are "early detection" or "screening" and "gestational diabetes mellitus" and "pregnant woman" or “pregnant mother”. Research articles published in 2016–2021, in English, research design: using a quantitative research design. The results of the study found that early detection of GDM can be done through a scoring system, identification of women's diet before pregnancy and optimization of early GDM screening before 24 weeks, monitoring growth and improving early detection services for gestational diabetes in basic health facilities. Health workers need to provide education to women of reproductive age about GDM, so that when they decide to get pregnant they can understand the importance of maintaining blood sugar levels.

Obstetric ultrasonography as a screening tool for the diagnosis of GDM: Detection of raised AFI and large for gestational age fetus

Objective: To establish the role of determining increased amniotic fluid index (AFI) and large for gestational age (LGA) fetus on ultrasound for the screening of gestational diabetes mellitus (GDM). Study Design: Descriptive Observational study. Place and Duration: Department of Gynaecology and Obstetrics, Pakistan Railway Hospital, Rawalpindi from 1st September 2021 till 28th February 2022. Methodology: The pregnant women, between 20-30 weeks of gestation, suspected of having excessive AFI or LGA fetuses on routine clinical examination, were advised to have an obstetric ultrasound scan. AFI &gt; 20 cm or LGA on ultrasound (&gt;90th percentile for that gestation) were considered abnormal. These participants were then subjected to 75-gram Oral Glucose Tolerance test (OGTT). Based on OGTT, the sample population was divided into two groups at the post-stratification stage: with and without Gestational Diabetes Mellitus (GDM). Chi-square test was applied to compare the frequency of increased AFI and LGA between patients having GDM or not having GDM. Results: The study population (n=75) showed the frequency of LGA as 37.3 % and increased AFI as 65.3%. Women with increased AFI were at a significantly greater risk of GDM (65%), as compared to those with normal AFI (27%) with p-value of 0.002. Also, patients having LGA fetuses (60.7%) were at a greater risk of having GDM, as compared to those with normal weight fetuses (34%) with p-value of 0.024. Conclusion: Women with Increased AFI and LGA fetuses between 20-30 weeks of gestation are at a greater risk to develop GDM. Hence these ultrasound parameters can be used as reliable screening tools for the detection of GDM. Keywords: Adverse pregnancy outcome, Fetal macrosomia, Gestational diabetes mellitus, Increased Fetal weight, Polyhydramnios

The Impact of Gestational Diabetes Mellitus on Maternal and Fetal Outcome

Objective: Gestational diabetes mellitus (GDM) is one of the major public health issues in developing countries. It occurs in 2-9 percent of all pregnancies [4-6]. The present study is aimed to determine whether maternal and neonatal outcomes in GDM women are different from those in the general obstetric population. Methods: This descriptive Observational study was conducted jointly in the departments of Obstetrics Gynecology and Medicine, Nightingale Medical College, Ashulia from 1st January 2014 to 31st December 2016 (3 years). Fifty pregnant woman diagnosed by OGTT as GDM and fifty healthy pregnant women were enrolled as study subjects. They were followed regularly at the outpatient departments until delivery for detection of maternal and fetal outcome. Results: Women with GDM were significantly older (mean age 31.5) than healthy pregnant women group (mean age 25.3). Multiparty, increased BMI and positive family history of DM were found commonly in GDM women than control group. GDM women were more prone to develop pregnancy induced hypertension (36% vs 20%), premature rupture of membrane (30% vs 14%), preterm labour (30% vs 10%) as compared to non GDM group. Rate of cesarean section was not significantly higher in GDM women than healthy women (64% vs 56%). Regarding neonatal complications there was increased risk of hyperbilirubinemia (46% vs 16%), hypoglycemia (20% vs 0) and macrosomia (30% vs 10%) in neonates of GDM women than those of non GDM women. Conclusion: Our study indicates that maternal and neonatal complications are more in GDM women than healthy population. So early detection of GDM and multidisciplinary approach of treatment in the form of dietary advice, lifestyle modification, and insulin therapy can reduce adverse outcomes without increasing the rate of cesarean section.

Diagnosing Gestational Diabetes with a Probably Too Simplified Diagnostic Procedure Compared to International Criteria: The Indian Case Study.

Diagnostic procedures for the diagnosis of gestational diabetes mellitus (GDM) are not uniformly defined worldwide. We retrospectively applied two diagnostic procedures (i.e., the IADPSG and the Indian) to the same pregnant women in order to compare the clinical characteristics and the prevalence of risk factors for GDM. Overall, 1015 pregnant women were evaluated. GDM was diagnosed in 113 cases (11.1%) by the IADPSG criteria and in 105 cases (10.3%) by the Indian criteria. The women diagnosed with GDM according to the IADPSG criteria had higher pre-gestational BMIs, higher previous macrosomia rates, higher first trimester fasting blood glucose levels, higher fasting and 1 h glucose levels after glucose load at OGTT, and lower 2 h glucose levels at OGTT compared with the women with GDM diagnosed according to the Indian criteria. Only 49.6% of the women who were diagnosed by the IADPSG criteria were also diagnosed with GDM by the Indian diagnostic criteria. For 47.8% of the women who were diagnosed by the IADPSG criteria, a diagnosis of GDM was missed by applying the Indian diagnostic criteria. Interestingly, 49 women were diagnosed with GDM by the Indian criteria but were normal according to the IADPSG criteria. Different diagnostic criteria could lead to different GDM detection rates with different practical approaches.

Adiponectin-targeted SERS immunoassay biosensing platform for early detection of gestational diabetes mellitus

The anisotropic gold nanotriangles (AuNTs) were synthesized by a fast seedless growth process. The high-yield monodispersed AuNT colloids were obtained through a purification process based on depletion-induced interactions. AuNTs were modulated with a localized surface plasmon resonance (LSPR) peak of 638 nm wavelength coherent with the Raman excitation light. However, from finite element computation results, the AuNT clusters showed better performance for the 785 nm laser source due to a red shift in their LSPR properties, hence it was selected for the surface-enhanced Raman scattering (SERS) immunoassay. A self-assembly strategy using a thiol group and ON-OFF strategy in the heat map was performed to ensure the stability of SERS immunoassay platform. The sandwich SERS immunoassay biosensor platform for adiponectin detection demonstrated a wide assay range (10–15–10–6 g/mL), good reliability (R2 = 0.994, clinically relevant range), femto-scale limit of detection (3.0 × 10–16 g/mL), and excellent selectivity without interference from other biomarkers. This showed the possibility of effectively detecting adiponectin levels in the biofluids of pregnant women. Therefore, our technology is the first to quantitatively detect adiponectin based on SERS technology for early detection of gestational diabetes mellitus and has the potential to be used as a clinical biosensor capable of diagnosing various obstetric diseases during early pregnancy.

Identification of differential metabolites using untargeted metabolomics between gestational diabetes and normal pregnant women.

To study the metabonomics differences between pregnant women with gestational diabetes mellitus (GDM) in the third trimester and those in a group without GDM by screening a group of highly efficient and sensitive markers for GDM and validating previously published early metabolic markers of GDM. A cross-sectional cohort study based on ultra performance liquid chromatography tandem mass spectrometry untargeted metabolomics analysis of serum samples collected from 59 pregnant women with GDM and 59 pregnant women without GDM. A total of 121 metabolites were detected, and 27 were identified as differential metabolites between GDM and control. The combination of 27 metabolic peaks had area under curve (AUC) values of 0.90, 0.92, and 0.93 in the prediction models using support vector machine, partial least squares, and random forest, respectively. Finally, five metabolite biomarkers were selected to construct logistic regression models: L-valine, hypoxanthine, eicosapentaenoic acid, 2-amino-1,3,4-octadecanotriol, and choline. The AUC value of these metabolites was 0.769 between the GDM group and the control group. The discovery of a group of differential metabolites in pregnant women with GDM in the third trimester and in pregnant women without GDM may facilitate the study of the pathologic mechanism of GDM; it may be possible to find an efficient and sensitive alternative GDM detection method.