scholarly journals Risk of Gestational Diabetes Mellitus (GDM) Using Clinical Prediction Model Based on Maternal Characteristics

2016 ◽  
Vol 11 (1) ◽  
pp. 64-68 ◽  
Author(s):  
Sharmin Jahan ◽  
Mohammad Ali
Keyword(s):  
Diabetes Mellitus ◽  
High Risk ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Prediction Model ◽  
Predictive Value ◽  
Area Under Curve ◽  
Risk Group ◽  
Clinical Prediction ◽  
Clinical Prediction Model

Introduction: The healthcare delivery challenges in Bangladesh are phenomenal. Improving maternal and child health, reducing the high maternal and infant mortality & morbidity are challenging. Arrangement of additional expenditure for GDM screening is again challenging. The efficiency of screening could be enhanced by considering women’s risks of gestational diabetes on the basis of their clinical characteristics.Objectives: To find out the use of the clinical prediction model of gestational diabetes mellitus (GDM) is valid for Bangladeshi pregnant women and to assess the risk of gestational diabetes by using clinical prediction model based on maternal characteristics.Materials and Methods: A cross sectional study was carried out from July 2011 to June 2012 among purposively selected 217 pregnant women of ?24 weeks of gestation in the Gynae and Obstetric outpatient department of Combined Military Hospital, Dhaka. Data were collected by face to face interview, anthropometric measurement and record review. Two step oral glucose tests were done for diagnosis of GDM.Results: According to Chadakaran clinical prediction model 84 (38.7%) respondents were at high risk, 92 (42.4%) were at intermediate risk and 41(18.9%) found at low risk of gestational diabetes but only 24(11.05%) developed gestational diabetes. Highest occurrence of gestational diabetes was found in high risk group 17 (20.2%) with zero occurrence in low risk group. Risk score performance at the level of ?380, sensitivity was 100% and specificity 21.8%, 13.6% positive predictive value, 100% negative predictive value and area under curve was 0.385. At the level of 460 score the sensitivity and specificity was found closest (70.8% and 65.3%, respectively) and area under curve was highest 0.657. The receiver operating characteristics curve of the risk score in the study sample for predicting women with glucose tolerance test demonstrated an area 0.763 (95%, 0.682 – 0.845).Conclusion: The use of clinical prediction model is a simple, non invasive, cost effective useful method to identify women at increased risk of gestational diabetes mellitus and could be short listed for further testing.Journal of Armed Forces Medical College Bangladesh Vol.11(1) 2015: 64-68

scholarly journals Uric Acid and Xanthine Levels in Pregnancy Complicated by Gestational Diabetes Mellitus—The Effect on Adverse Pregnancy Outcomes

2018 ◽  
Vol 19 (11) ◽  
pp. 3696 ◽  
Author(s):  
Anna Pleskacova ◽  
Vendula Bartakova ◽  
Katarina Chalasova ◽  
Lukas Pacal ◽  
Katerina Kankova ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Uric Acid ◽  
High Risk ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Perinatal Outcomes ◽  
Anthropometric Parameters ◽  
Pregnancy And Postpartum ◽  
Adverse Perinatal Outcomes ◽  
Adverse Pregnancy

Uric acid (UA) levels are associated with many diseases including those related to lifestyle. The aim of this study was to evaluate the influence of clinical and anthropometric parameters on UA and xanthine (X) levels during pregnancy and postpartum in women with physiological pregnancy and pregnancy complicated by gestational diabetes mellitus (GDM), and to evaluate their impact on adverse perinatal outcomes. A total of 143 participants were included. Analyte levels were determined by HPLC with ultraviolet detection (HPLC-UV). Several single-nucleotide polymorphisms (SNPs) in UA transporters were genotyped using commercial assays. UA levels were higher within GDM women with pre-gestational obesity, those in high-risk groups, and those who required insulin during pregnancy. X levels were higher in the GDM group during pregnancy and also postpartum. Positive correlations between UA and X levels with body mass index (BMI) and glycemia levels were found. Gestational age at delivery was negatively correlated with UA and X levels postpartum. Postpartum X levels were significantly higher in women who underwent caesarean sections. Our data support a possible link between increased UA levels and a high-risk GDM subtype. UA levels were higher among women whose glucose tolerance was severely disturbed. Mid-gestational UA and X levels were not linked to adverse perinatal outcomes.

scholarly journals Comparison of Venous and Capillary Sampling in Oral Glucose Testing for the Diagnosis of Gestational Diabetes Mellitus: A Diagnostic Accuracy Cross-Sectional Study Using Accu-Chek Inform II

Diagnostics ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1011
Author(s):  
Sofia Nevander ◽  
Eva Landberg ◽  
Marie Blomberg ◽  
Bertil Ekman ◽  
Caroline Lilliecreutz
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Cross Sectional Study ◽  
Oral Glucose ◽  
Sectional Study ◽  
Cross Sectional ◽  
Capillary Sampling

Gestational diabetes mellitus (GDM) is a common complication with negative impacts on mother and child. The primary aim of this study was to examine whether plasma glucose cutoffs for GDM diagnosis based on venous sampling can be replaced by cutoffs based on capillary sampling. A prospective cross-sectional study was performed at an antenatal care clinic including 175 pregnant women undergoing an oral glucose tolerance test (OGTT). Duplicate samples were collected by capillary and venous puncture while fasting and 1 h and 2 h after an OGTT. Both samples were analyzed on Accu-Chek Inform II. The cutoffs for a GDM diagnosis using capillary samples were corrected from 5.1 to 5.3 mmol/L for the fasting sample, from 10.0 to 11.1 mmol/L for the 1 h sample, and from 8.5 to 9.4 mmol/L for the 2-h sample using half of the dataset. Applying these cutoffs to the remaining dataset resulted in a sensitivity, specificity, and accuracy of 85.0%, 95.0%, and 90.3%, respectively, with a positive predictive value (PPV) of 83%, an negative predictive value (NPV) of 96%, and a positive negative likelihood ratio (LHR) of 16.4 using capillary sampling for the GDM diagnosis at fasting and 2-h after. Corrected cutoffs and capillary samples can be used for the diagnosis of GDM with maintained diagnostic accuracy using Accu-Chek Inform II.

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