JOURNAL OF EVIDENCE BASED MEDICINE AND HEALTHCARE

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2020 Month : July Volume : 7 Issue : 31 Page : 1531-1535

An Analysis of Glucose Levels in Normal Pregnancy and Pregnancy Complicated by Gestational Diabetes Mellitus

Usha Thachappilly1, Vijayalakshmy R. S.2, Sreedevi N. S.3, Vijayalakshmy Moorkkattukara Thekkoot4, Shajee Sivasankaran Nair5, Sajith Vilambil6, Sajeevan Kundila Chandran7

1Associate Professor, Department of Physiology, Government Medical College, Thrissur, Kerala, India.
2Former Professor and Head, Department of Physiology, Government Medical College, Calicut, Kerala, India.
3Professor and Head, Department of Obstetrics and Gynaecology, Pushpagiri Medical College, Thiruvalla, Kerala, India. 4Professor and Head, Department of Physiology, Government Medical College, Thrissur, Kerala, India.
5Associate Professor, Department of Biochemistry, Government Medical College, Thrissur, Kerala, India.
6Associate Professor, Department of Transfusion Medicine, Government Medical College, Thrissur, Kerala, India.
7Additional Professor, Department of Biochemistry, Government Medical College, Thrissur, Kerala, India.

Corresponding Author

Dr. Shajee Sivasankaran Nair,
Email : drno2007@gmail.com

Abstract

BACKGROUND

Effective diagnosis and treatment of DM can reduce hyperglycemia related adverse pregnancy outcomes. We wanted to analyse glucose levels in normal pregnancy and pregnancy complicated by GDM.

 

METHODS

This is a case-control study conducted in the Department of Obstetrics and Gynaecology, Institute of Maternal and Child Health, Medical College, Calicut. A total of 200 subjects was divided into two groups comprising 150 controls (healthy pregnant women with no history of GDM) and 50 cases (pregnant women with GDM). All statistical data were analysed using SPSS software version 16. Continuous variables were expressed as mean ± standard deviation. Qualitative data was expressed as percentage. Independent t test was used for comparing quantitative data between two groups.

 

RESULTS

The mean age of normal pregnant study subjects was 23.76 years. The mean duration from last delivery was 1.37 years among normal pregnant mothers. Among the normal pregnant group, majority had no history of abortion. Mean Systolic Blood Pressure (BP) of normal pregnant category was 113.17 mmHg. Mean diastolic BP was 73.13 mmHg. The mean height and weight in normal pregnant group was 1.56 m and 57.33 Kg respectively. The average BMI was 23.42 among normal pregnant mothers. The mean age of GDM study subjects was 26.24 years. The mean duration from last delivery was 1.74 years among GDM mothers. In the GDM group, majority had no history of abortion. Mean systolic BP of GDM category was 122.04 mmHg. Mean diastolic BP was 79.76 mmHg and ranged between 70 - 100 mmHg. The mean value of blood glucose in women with GDM was 147.86 mg/dL and that in normal pregnant women was 103.59 mg/dL. The result was statistically significant.

 

CONCLUSIONS

Glucose tolerance is significantly reduced in GDM. Screening for GDM and adequate control measures help in detecting women with even minimal abnormality of glucose metabolism which may otherwise be undetected and progress to diabetes.

 

KEYWORDS

Glucose tolerance, Gestational diabetes, Blood glucose, Pregnancy

Background

Pregnancy is characterized by many metabolic adaptations which meet the energy needs of mother and developing foetus.1 Fasting hypoglycaemia, postprandial hyperglycaemia and hyperinsulinemia are characteristic of normal pregnancy. A state of progressive insulin resistance which usually begins in the second trimester and progresses throughout the remainder of pregnancy occurs due to placental secretion of hormones such as progesterone, oestrogen, placental lactogen, prolactin and cortisol and ensures that the foetus has an adequate supply of glucose. This insulin resistance results in a compensatory increase in β cell response and hyperinsulinemia in normal pregnancy. Pregnancy can be regarded as a diabetogenic condition characterized by insulin resistance with a compensatory increase in β cell response and hyperinsulinemia.2 GDM represents a cross section of young women with glucose intolerance and mechanisms that lead to chronic insulin resistance. This research was trying to compare glucose levels in both gestational diabetic and normal mothers.

Diabetes mellitus in pregnancy continues to be a relatively neglected problem and is not adequately recognized. Studies have revealed an increase in the prevalence of GDM with age, status of gravid and Body Mass Index (BMI). Weight gain and additional pregnancies independently increase the risk of developing diabetes. A knowledge of risk factors helps in identifying abnormal glucose tolerance that may be mild and asymptomatic. Most of those women with GDM would not be diagnosed to have abnormal glucose tolerance because majority have lower glucose levels and only some have glucose levels that would be diagnostic of diabetes outside pregnancy. Pregnancy, in essence, serves as a metabolic stress test that uncovers underlying insulin resistance and β cell dysfunction.1

GDM is detected through screening of pregnant women for clinical risk factors. It appears to result from the same broad spectrum of physiological and genetic abnormalities that characterize diabetes outside of pregnancy. GDM thus provides a unique opportunity to study the early pathogenesis of diabetes and develop interventions to prevent progression of the disease and this was one of the reasons for taking up this study. It was found that the degree of glucose intolerance during pregnancy was related to the risk of developing diabetes after pregnancy. Treatment of GDM reduces perinatal morbidity and maternal complications. Management of insulin resistance at this stage is associated with a reduction in the risk of diabetes and preservation of β cell function.2

            We wanted to analyse glucose levels in normal pregnancy and pregnancy complicated by GDM.

 

Methods

The study was conducted in the Department of Obstetrics and Gynaecology, Institute of Maternal and Child Health, Medical College, Calicut.

A total of 200 subjects were included in the study. The subjects were divided into two groups, comprising of controls and cases. Women with diabetes, hypertension and renal disease diagnosed before pregnancy were excluded from the study. The control group included 150 healthy pregnant women with no history of GDM. The cases included 50 pregnant women with GDM diagnosed by OGCT. For OGCT, they were given 50 gm of glucose in about 200 mL of water over 2 to 3 minutes. Exactly at 1 hour, 1 ml of blood is drawn from a forearm vein using a disposable syringe under aseptic precautions into a clean dry bottle containing oxalate. The blood glucose is determined by the Glucose Oxidase/Peroxidase method. (GOD/POD method) The study was conducted for a period of two years. The subjects were selected by random sampling method.

All statistical data were analysed using SPSS software version 16. Continuous variables were expressed as mean ± standard deviation. Qualitative data was expressed as percentage. Independent t test was used for comparing quantitative data between two groups.

Results

The present study on GDM was conducted in a total of 200 subjects divided into two groups. One of the groups comprised of 50 women with GDM and the other included 150 normal pregnant controls.

The mean age of normal pregnant study subjects was 23.76 years. The category fell between 19 years and 30 years. The gravid status of normal pregnant mothers ranged from 1-5 and parity from 0-4. The mean duration from last delivery was 1.37 years among normal pregnant mothers. The normal pregnant group had a range of 0-3 abortions, while had no history of abortion.

Mean systolic BP of normal pregnant category was 113.17 mmHg and it ranged between 110-122 mmHg. Mean diastolic BP was 73.13 mmHg and it ranged between 70-84 mmHg. The mean height and weight of normal pregnant group was 1.56 m and 57.33 Kg respectively. The average BMI was 23.42 among normal pregnant mothers.

The mean age of GDM study subjects was 26.24 years. The category fell between 19 years and 31 years. The gravid status of GDM mothers ranged from 1-6 and parity from 0-5. The mean duration from last delivery was 1.74 years among GDM mothers. The GDM group had a range of 0-3 abortions, while majority had no history of abortion.

Mean systolic BP of GDM category was 122.04 mmHg and it ranged between 110-150 mmHg. Mean diastolic BP was 79.76 mmHg and it ranged between 70-100 mmHg. The mean height and weight of GDM group was 1.54 m and 64.24 Kg respectively. The average BMI was 26.98 among GDM mothers.

The mean value of blood glucose in women with GDM was 147.86 mg/dL and that in normal pregnant women was 103.59 mg/dL. The p value was< 0.001 (highly significant).

 

 

Blood Glucose (mg/dL)

 

GDM

Controls

Mean

147.86

103.59

SD

14.48

13.72

Table 1. Comparison of Blood Glucose in Women with GDM and Normal Pregnant Controls

p value <0.001

Discussion

In current study the mean value of blood glucose in women with GDM and normal pregnant women was compared. The blood glucose level in GDM category was significantly high.

Hyperinsulinemia of normal pregnancy is associated with several unique responses to glucose uptake. Serial glucose tolerance tests indicate a progressive decline in glucose tolerance with advancing gestation. During early pregnancy, glucose tolerance is normal or slightly improved and peripheral sensitivity to insulin and hepatic basal glucose production are normal. Insulin responses to oral glucose are also greater in the first trimester than before pregnancy. These observations are consistent with a 120% increase in the first phase of insulin response following IV glucose administration during 12 to 14 weeks gestation. The first phase response refers to the change in insulin concentration from 0 to 5 minutes after IV glucose. The rate of insulin release relative to the glucose concentration 5 to 60 minutes after IV glucose administration, referred to as the second phase of insulin response, is not significantly different from the non-pregnant state.3 Longitudinal studies of glucose tolerance shows a progressive decline with advancing gestation. In late pregnancy, there are higher peaks of plasma glucose concentration, a delay in rise to the peak concentration and an increase in total area under the glucose tolerance curve compared with the non-pregnant state.4 Pregnant women, however, maintain efficient glucose homeostasis with slightly lower preprandial and higher postprandial glucose concentration following mixed meals. Glucose levels change little when compared to large changes in insulin sensitivity because of compensatory hyperinsulinemia.5 The glucose tolerance curve in pregnancy differs from that in the non-pregnant state as below.

Majority of women with GDM have β cell dysfunction occurring on a background of chronic insulin resistance. The mechanisms underlying insulin resistance of pregnancy are exaggerated in women with GDM.6 A longitudinal study conducted by Xiang et al7 in Latino women with GDM revealed an increased resistance to the effects of insulin on glucose clearance as well as suppression of glucose production and fatty acid levels. These women were found to have 6% higher glucose production, 9% lower glucose clearance and higher circulating FFA levels. Catalano et al8,9 conducted the most detailed metabolic testing in pregnant women with GDM and observed a 22% reduction in insulin-mediated glucose uptake. Linda et al7 observed a 65% reduction in insulin-stimulated glucose transport in GDM. Ward et al10 and Ryan et al11 also had observations consistent with the above findings. A longitudinal study12 on insulin suppression in early pregnancy and late pregnancy in subjects with normal glucose tolerance and women with GDM concluded that the ability of insulin to suppress whole-body lipolysis which is reduced in normal pregnancy is further reduced in GDM. Increase in FFAs and hepatic glucose production has been documented in GDM in several studies.13,14,15,16

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

Conclusion

Glucose tolerance is significantly reduced in GDM. Screening for GDM and adequate control measures help in detecting women with even minimal abnormality of glucose metabolism which may otherwise be undetected and progress to diabetes. This provides an opportunity to study early stages of glucose dysregulation thereby reducing foetal and neonatal complications as well as long term complications in mother and offspring.

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Disclosure and Funding

Disclosure forms provided by the authors are available with the full text of this article at jebmh.com

Study was approved by Human Ethical Committee and Review Board of Institution. Study subjects were counselled separately about the study and a written consent was procured from them.

Financial or Other Competing Interests: None.

 

We thank Dr. Vijayalakshmy R, MD, Professor & Head (Retd.), Department of Physiology, Govt. Medical College, Calicut, for her scholarly guidance in the course of this work. We acknowledge Dr. N. S. Sreedevi, MD, DGO, Professor & Head (Retd.), Department of Obstetrics, Govt. Medical College, Calicut, for her unwavering support.

 

Financial or Other Competing Interests: None.

How to cite this article

Usha T, Vijayalakshmy RS, Sreedevi NS, et al. An analysis of glucose levels in normal pregnancy and pregnancy complicated by gestational diabetes mellitus. J. Evid. Based Med. Healthc. 2020; 7(31), 1531-1535. DOI: 10.18410/jebmh/2020/322