scholarly journals Gestational diabetes mellitus and obstetric outcomes in a Ghanaian community

2018 ◽  
Vol 8 (1) ◽  
pp. 204
Author(s):  
Ahmed Tijani Bawah ◽  
Robert Amadu Ngala ◽  
Mohammed Mustapha Seini ◽  
Francis Abeku Ussher ◽  
Huseini Alidu ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Pregnancy Outcome ◽  
Obstetric Outcomes ◽  
Retrospective Case ◽  
Family History Of Diabetes ◽  
Maternal Characteristics ◽  
History Of ◽  
Control Study

Background: This study was aimed at evaluating effect of Gestational diabetes mellitus (GDM) and maternal characteristics on pregnancy outcomes. GDM has several risk factors including; advanced maternal age, ethnic background, obesity and family history of diabetes mellitus. These pregnancy complications are associated with fetal morbidity and mortality and may lead to macrosomia and shoulder dystocia. Others are stillbirth, miscarriages, preterm and small for gestational age babies.Methods: This was a retrospective case-control study which compared maternal characteristics and pregnancy outcome among pregnant women with and without GDM. Diagnosis of GDM was done in accordance with the American Diabetes Association (ADA) criteria. Weight and height were determined and Body mass index (BMI) calculated. Pregnancy outcome was determined at the end of pregnancy and information on maternal characteristics obtained using questionnaire and patient folders.Results: Those who developed GDM were significantly older (OR=1.772; 95% CI=1.432-2.192; P<0.0001) and had higher BMI (OR=1.637; 95% CI=1.004-1.289; P=0.044) than those who did not. A significant number of those who developed GDM also had stillbirths (OR= 5.188; 95% CI=1.093-24.613; p=0.038) and cesarean deliveries (OR=14.362; 95% CI=3.661-56.335; p= 0.001).Conclusions: Women who develop GDM are more likely to deliver stillborn or macrosmic babies and may require surgical intervention in order to have normal deliveries.

scholarly journals THE DEMOGRAPHIC PROFILE OF WOMEN WITH GESTATIONAL DIABETES MELLITUS

2021 ◽  
Vol 5 (11) ◽  
Author(s):  
Priyanka Inaniya ◽  
B S Meena ◽  
Mohan Lal Meena ◽  
Aparna Sharma ◽  
Shalini Rathore
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Family History Of Diabetes ◽  
Demographic Profile ◽  
Medical College ◽  
History Of ◽  
Socio Demographic Factors

Background: The present study aimed to study the demographic profile women with gestational diabetes mellitus Methods: This hospital based cross-sectional study Department of Obstetrics and Gynaecology, SMS Medical College, Jaipur. Results: Mean age of patients was 27.68 ± 4.4 Yrs. Most of the study subjects in GDM group (54.7%) were Hindu. Study subjects in GDM group were almost equally from rural (50.7%).Most of the study subjects in both GDM group (88%) were housewives. Habit of smoking was found in only 6.7% females in GDM group. Habit of alcohol was found in 4% females in GDM group. Family history of diabetes was seen more in females with GDM (17.3%). Conclusion: This study concluded that the socio demographic factors influence the occurrence of GDM. Keywords: GDM, Age, Gravida

scholarly journals A study of the prevalence of gestational diabetes mellitus and its maternal and fetal outcomes in a tertiary care hospital

2017 ◽  
Vol 6 (9) ◽  
pp. 4011 ◽  
Author(s):  
Manisha R. Gandhewar ◽  
Binti R. Bhatiyani ◽  
Priyanka Singh ◽  
Pradip R. Gaikwad
Keyword(s):  
Diabetes Mellitus ◽  
Birth Weight ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Tertiary Care ◽  
Significant Risk ◽  
Care Hospital ◽  
Family History Of Diabetes ◽  
Significant Difference ◽  
History Of

Background: The aim of this study was to study the prevalence of gestational diabetes mellitus (GDM) using Diabetes in Pregnancy Study group India (DIPSI) criteria to diagnose patients with GDM and to study the maternal and neonatal outcomes.Methods: 500 patients attending the antenatal clinic between January 2013 to September 2014 with singleton pregnancies between 24 and 28 weeks of gestation were evaluated by administering 75g glucose in a nonfasting state and diagnosing GDM if the 2-hour plasma glucose was more than 140 mg/ dl. Women with multiple pregnancies, pre-existing diabetes mellitus, cardiac or renal disease were excluded from the study.Results: 31 women were diagnosed with GDM (prevalence 6.2%). The prevalence of risk factors such as age more than 25, obesity, family history of Diabetes Mellitus, history of GDM or birth weight more than 4.5kg in previous pregnancy and history of perinatal loss were associated with a statistically significant risk of developing GDM. Though the incidence of Gestational hypertension, polyhydramnios and postpartum haemorrhage was higher in the GDM group, it did not reach statistical significance. More women in the GDM group were delivered by LSCS. There was no significant difference in the incidence of SGA or preterm delivery in the groups. The mean birth weight in GDM group was higher than in the non GDM group.Conclusions: Early detection helps in preventing both maternal and fetal complications. This method of screening is convenient to women as it does not require them to be fasting.

scholarly journals Single Nucleotide Polymorphisms in CDKAL1 Gene Are Associated with Risk of Gestational Diabetes Mellitus in Chinese Population

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Keke Wang ◽  
Qiong Chen ◽  
Yongliang Feng ◽  
Hailan Yang ◽  
Weiwei Wu ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Health Concern ◽  
Nucleotide Polymorphisms ◽  
Family History Of Diabetes ◽  
Gene Level ◽  
Risk Snps ◽  
History Of ◽  
Nested Case Control

Gestational diabetes mellitus (GDM) is a growing public health concern for many reasons, and its etiology remains unclear. Due to the similarity of its pathophysiology with type 2 diabetes (T2DM), we evaluated the relationship between published T2DM susceptibility genes and the risk of GDM. A total of 303 SNPs from genes including IRS1, IGF2BP2, CDKAL1, GCK, TCF7L2, KCNQ1, and KCNJ11 and the risk of GDM were examined in a nested case-control study with 321 GDM cases and 316 controls. The odds ratios (ORs) and their 95% confidence interval (95% CI) were estimated by unconditional logistical regression as a measure of the associations between genotypes and GDM in additive, recessive, dominant, and codominant models adjusting for maternal age, maternal BMI, parity, and family history of diabetes. At the gene level, CDKAL1 was associated with GDM risk. SNPs in the CDKAL1 gene including rs4712527, rs7748720, rs9350276, and rs6938256 were associated with reduced GDM risk. However, SNPs including rs9295478, rs6935599, and rs7747752 were associated with elevated GDM risk. After adjusting for multiple comparisons, rs9295478 and rs6935599 were still significant across the additive, recessive, and codominant models; rs7748720 and rs6938256 were significant in dominant and codominant models; and rs4712527 was only significant in the codominant model. Our study provides evidence for an association between the CDKAL1 gene and risk of GDM. However, its role in the GDM pathogenesis still needs to be verified by further studies.

scholarly journals Prevalence and cause of gestational diabetes mellitus in a tertiary care center in Kolar district: a population based study

2019 ◽  
Vol 8 (7) ◽  
pp. 2709
Author(s):  
Poojita Tummala ◽  
Munikrishna M. ◽  
Kiranmayee P.
Keyword(s):  
Diabetes Mellitus ◽  
Family History ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Pregnant Women ◽  
Tertiary Care ◽  
Oral Glucose ◽  
Care Hospital ◽  
Family History Of Diabetes ◽  
History Of

Background: Gestational diabetes mellitus (GDM) is carbohydrate intolerance at the onset of pregnancy which induces pathological short term or long term outcomes for both mother and baby. The aim of the present study was to know the prevalence of GDM in pregnant women who were attending the antenatal care (ANC) center at a tertiary care hospital in Kolar, Karnataka, India.Methods: This prospective study was conducted in Department of Obstetrics and Gynecology, Sri Devaraj Urs Medical College, a constituent of Sri Devaraj Urs Academy of Higher Education and Research, Kolar, Karnataka, India. The duration of the study was two months. In this study, 108 pregnant women above 24 weeks of gestation were screened for GDM by oral glucose tolerance test. Fasting 2 milli liter blood was collected and were given 75 grams of glucose in 200 milli liters of water and asked to drink within 5 minutes. Again 2 milli liters venous blood was collected after 1 hour and 2 hours from all participants. Plasma sample was used for the estimation of glucose by glucose oxidase and peroxidase (GOD-POD) method.Results: Out of 108, 12 women (11.1%) were diagnosed with GDM. The prevalence rate was higher in the age group of 26-30 years (41.6%).  Among 12 diabetic women, five (47.2%) exercised regularly and seven (58.3%) did not doing exercise. Out of 12 GDM subjects, eight of them had family history of diabetes in first degree relatives; among which one was hypertensive and five were suffering from thyroid problems.Conclusions: In the present study, the prevalence of GDM was found to be 11.1%. Prevalence of GDM might be influenced by increasing age, pre pregnancy weight, family history of diabetes, past history of pregnancy complications, status of literacy and exercise.

scholarly journals Risk Prediction of Gestational Diabetes Mellitus In Women With Polycystic Ovary Syndrome Based On A Nomogram Model

2021 ◽  
Author(s):  
Peilin Ouyang ◽  
You Yiping ◽  
Jia Xiaozhou ◽  
Yang Liqin
Keyword(s):  
Diabetes Mellitus ◽  
Family History ◽  
Gestational Diabetes ◽  
Polycystic Ovary Syndrome ◽  
Gestational Diabetes Mellitus ◽  
Polycystic Ovary ◽  
First Trimester ◽  
Ovary Syndrome ◽  
Family History Of Diabetes ◽  
History Of

Abstract Women with polycystic ovary syndrome are prone to develop gestational diabetes mellitus, a disease which may have significant impact on the postpartum health of both mother and infant. We performed a retrospective cohort study to develop and test a model that could predict gestational diabetes mellitus in the first trimester in women with polycystic ovary syndrome. Our study included 520 pregnant women who were referred to the obstetrics department between December 2017 and March 2020 with a diagnosis of polycystic ovary syndrome. Of these women, 171 were diagnosed with gestational diabetes mellitus in the second trimester. Univariate analysis revealed that in the first trimester, parity, family history of diabetes, age, body mass index (BMI), testosterone, low density lipoprotein cholesterol, triglyceride(TG), total cholesterol(TC), fasting plasma glucose(FPG), Hemoglobin A1c (HbA1C), diastolic blood pressure(DBP)，and insulin levels were predictive factors of gestational diabetes mellitus (P<0.05). Logistic analysis revealed that TG, age, HbA1C, Insulin, TC, BMI and family history of diabetes were independent risk factors for gestational diabetes mellitus. The area under the ROC curve of the gestational diabetes mellitus risk prediction model was 0.917 in this retrospective analysis, demonstrating the great ability to predict. The sensitivity and specificity of the prediction model were 0.814 and 0.871, respectively. The Hosmer–Lemeshow test also showed a good fit to the test.

scholarly journals GESTATIONAL DIABETES MELLITUS

2016 ◽  
Vol 23 (01) ◽  
pp. 015-019
Author(s):  
Afsheen Qazi ◽  
Amin Fahim ◽  
Aneela Qureshi3 ◽  
Mazhar ul Haque
Keyword(s):  
Diabetes Mellitus ◽  
Family History ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Tertiary Care ◽  
Oral Glucose ◽  
Care Hospital ◽  
Family History Of Diabetes ◽  
Number Of Patients ◽  
History Of

Objectives: The present study was designed to find the importance of properscreening and early diagnosis of gestational diabetes mellitus. Study Design: A prospective/descriptive study Place of Study: tertiary care hospital Hyderabad. Duration of Study: fromSeptember 2014 to November 2014. Materials and Methods: A total of 168 pregnant femalesbetween the ages of 20-40 years & in their 24th to 28th week of gestation were enrolled for thestudy. Oral Glucose Tolerance Test of all the participants was done after an overnight fasting of10-12 hours. All the participants were given 75gm of glucose per 100 ml of distilled water. Theblood samples were collected after two hours time for serum glucose levels. Results: Mostof the participants were below 26 years of age 47(27.9%) with the mean age of 30.2±5.83years. However the highest prevalence of GDM was observed in age group 31-35 years (36%).Among the 25 cases of gestational diabetes mellitus the highest number of patients with GDMwere multipara (40%) followed by parity of 3-4 gravida (32%). Twenty seven women (16%)women had family history of diabetes mellitus. Among these 12/27 (44.4%) women were foundwith GDM, compared to 15/141 (10.6%) who have no family history of diabetes mellitus. Total14 (8.33%) women were found obese, out of these 8 (57%) women had GDM while only 6(42.8%) women had no GDM. Conclusion: The prevalence of GDM in the present study isfound to be 14.8%. A prevalence of GDM was higher in the elderly multiparous females whowere overweight and had family history of diabetes mellitus.

scholarly journals First-Trimester Screening for Gestational Diabetes Mellitus Based on Maternal Characteristics and History

2014 ◽  
Vol 38 (1) ◽  
pp. 14-21 ◽  
Author(s):  
Argyro Syngelaki ◽  
Alice Pastides ◽  
Reena Kotecha ◽  
Alan Wright ◽  
Ranjit Akolekar ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Logistic Regression Model ◽  
Cross Validation ◽  
Nice Guidelines ◽  
Maternal Characteristics ◽  
History Of ◽  
Fold Cross Validation

Objectives: To develop and validate a prediction model for gestational diabetes mellitus (GDM) at 11-13 weeks' gestation based on maternal characteristics and history and to compare its performance with the method recommended by the National Institute of Health and Care Excellence (NICE) and five other published prediction models. Methods: A predictive logistic regression model for GDM was developed from 1,827 cases (2.4%) who developed GDM and 73,334 unaffected controls. A 5-fold cross-validation study was performed to validate this model and to compare its performance with those of the NICE guidelines and the previously published models. Results: In the logistic regression model, maternal age, weight, height, racial origin, family history of diabetes, use of ovulation drugs, birth weight, and previous history of GDM were found to be significant predictors of GDM. In screening for GDM in the 5-fold cross-validation study, detection rates (DRs) were higher (p < 0.0001) for the proposed model (DR = 83.2%) than for the NICE guidelines (DR = 77.5%) for a false positive rate of approximately 40% (determined by NICE). The area under the receiver operating characteristic curve of the new model was higher (p < 0.0001) than that of the previous five models (0.823 vs. 0.688-786). Conclusions: Early effective screening for GDM can be achieved based on maternal characteristics and history.

Study the Effect of Maternal Factors on Prevalence of Gestational Diabetes Mellitus and Effect of Treatment Types on Serum Blood Glucose

2021 ◽  
pp. 5264-5269
Author(s):  
Shaymaa Hasan Abbas ◽  
Sura Abbas Khdair
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Blood Glucose ◽  
Family History ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Blood Glucose Level ◽  
Family History Of Diabetes ◽  
Treatment Groups ◽  
History Of

Introduction: Gestational diabetes mellitus (GDM) is one of the most common medical problems occurred during pregnancy. GDM increase the chance for developing type 2 diabetes meletus by seven times. The overall prevalence of GDM in pregnancy is 1-14% according to the American Diabetes Association. Material and Methods: a self-administered questionnaire was used to collect data. The information was collected from pregnant women with gestational DM to assess some maternal risk factors and compare blood glucose level according to different treatment types for GDM. Results: The present study reported that (40.38%) of GDM patients have advanced age (≥35 yrs.). First pregnancy was a risk factors for GDM and it was reported by (9.62%). History of HT and GDM during prior pregnancies were reported by (11.54%) and (% 34.62) respectively. Hypertension or preeclampsia in the current pregnancy was reported by (3.85%). Positive family history of diabetes was associated with (26.92%) GDM patients. All Patients of the present study reported no previous PCOS and smoking history. Also in this study, 44 patients out of 52 GDM patients use medications to control the glucose intolerance, while other patients control it by diet. There were no statistical differences found between treatment groups in term of blood glucose control. Conclusion: Age, history of GDM in the previous pregnancies and family history of diabetes mellitus were identifiable as a risk factors for GDM and their effect were significant in this study while the effect of other risk factors were non-significant. No statistical differences found between treatment groups in term of blood glucose level control and no group achieved the glycemic target.

Abstract MP70: Pre-pregnancy Beta Cell Compensation for Insulin Resistance Associated With Subsequent Gestational Diabetes Mellitus: The CARDIA Study

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Erica P Gunderson ◽  
Amy Krefman ◽  
Cora E Lewis ◽  
Janet Catov ◽  
Norrina B Allen
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Family History ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Beta Cell ◽  
Pancreatic Beta Cell ◽  
Family History Of Diabetes ◽  
History Of ◽  
Beta Cell Compensation

Hypothesis: Gestational diabetes mellitus (GDM) is a disorder of glucose metabolism during pregnancy characterized by pancreatic beta cell dysfunction and greater insulin resistance, but it is unclear whether dysfunction exists before pregnancy. The disposition index (DI) is a physiologic measure of beta cell compensation for insulin resistance strongly predictive of future diabetes. This prospective study evaluates whether a clinical approximation of DI before pregnancy is associated with risk of GDM. Methods: This analysis included 696 women (45% black, 55% white) enrolled in the CARDIA Study, a U.S. multi-center prospective cohort of young adults aged 18-30 at baseline (1985-86) who gave birth at least once during 30 years of follow up, reported GDM status and had fasting glucose and insulin measured before one or more post-baseline births. DI was defined as HOMA-B divided by HOMA-IR using standard formulas. Multinomial logistic regression models estimated odds ratios (OR) and 95%CI for GDM among pre-pregnancy DI tertiles (low, moderate, high) and fully adjusted for time to birth, race, age, parity, BMI, lifestyle behaviors and family history of diabetes, and also stratified by pre-pregnancy BMI. Results: 9% of women reported GDM (64/696) for 794 births. 55% of GDM and 30% of non-GDM were categorized as low DI. Low pre-pregnancy DI compared to moderate DI was associated with higher fully adjusted odds of GDM (OR=2.71, 95%CI:1.37-5.35) in the entire sample. In models stratified by pre-pregnancy BMI, low DI was associated with 4-fold higher odds of GDM among Overweight/Obese (OR=4.22, 95%CI: 1.35-13.91) and somewhat attenuated higher odds of GDM among Normal BMI (OR=1.94, 95%CI: 0.78–4.86); Table 1. Only family history of diabetes was strongly associated with GDM independent of DI. Conclusions: Inadequate beta cell compensation is present before pregnancy and discriminates greatest risk of GDM among high BMI, and may identify higher risk among women of normal BMI.

Machine Learning Prediction Models for Gestational Diabetes Mellitus: A meta-analysis (Preprint)

2020 ◽  
Author(s):  
Zheqing Zhang ◽  
Luqian Yang ◽  
Wentao Han ◽  
Yaoyu Wu ◽  
Linhui Zhang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Machine Learning ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Prediction Models ◽  
Meta Analysis ◽  
Risk Of Bias ◽  
Screening Methods ◽  
Family History Of Diabetes ◽  
History Of

BACKGROUND Gestational diabetes mellitus (GDM) is a kind of common endocrine metabolic diseases, including carbohydrate intolerance of variable severity during pregnancy. The incidence rates of GDM related complications and adverse pregnancy outcomes will decline partly due to early screening. Nowadays, machine learning (ML) models have found an increasingly wide utilization, whether for risk factors selection or early prediction of GDM. OBJECTIVE Though many models for pregnancy women have been proposed and verified through experimental studies, few of them have been clinically recognized. Since seldom publication has evaluated the performance of ML prediction models for GDM, this meta-analysis was conducted and put forward some suggestions for model providers, users and policy makers basing on the findings. METHODS Four reliable electronic databases were searched for studies that developing ML prediction models for GDM in the general population, instead of the high-risk groups. The Prediction model Risk of Bias Assessment Tool (PROBAST) was used as a novel tool assessing the risk of bias of ML models. The software program Meta-Disc 1.4 was utilized to perform the Meta-analysis and determination of heterogeneity. To limit the influence of heterogeneity, results of sensitivity analysis, meta-regression and subgroups analysis were provided. RESULTS Twenty-five studies were analyzed which included women older than 18 years without a history of vital disease. The pooled area under receiver operating characteristic curve (AUC) and the pooled sensitivity and specificity for ML to predict GDM was 0.8492, 0.69 (95%CI: 0.68–0.69, P < .001, I2 = 99.6%)and 0.75 (95%CI:0.75–0.75, P < .001, I2 = 100%) respectively. As one of the most employed ML methods, logistic regression (LR) achieved an overall pooled AUC at 0.8151 while non-LR models performed better with an overall polled AUC at 0.8891. Additionally, maternal age, family history of diabetes, BMI and fasting blood glucose were the four mostly used features of models established by various feature selection methods. CONCLUSIONS ML methods could be cost-effective screening methods for GDM. The importance of quality assessment and unified diagnostic criteria should be further emphasized.

Sign in / Sign up

Export Citation Format

Share Document