Gestational diabetes mellitus prediction model: A risk factors analysis of pregnant women with gestational diabetes mellitus but have normal oral glucose tolerance test results in the second trimester of pregnancy

1.Introduction

Gestational diabetes mellitus (GDM) is a metabolic disease that is a threat to pregnant women and fetal health risk factors, because it may be associated with a variety of perinatal complications, such as ketoacidosis, gestational hypertension, polyhydramnios, macrosomia, fetal congenital malformation, fetal intrauterine death, dystocia, urogenital infection, puerperal infection and neonatal hypoglycemia, respiratory distress syndrome, neonatal low blood calcium disease, and high blood bilirubin [1, 2, 3]. The current diagnostic criteria for GDM are an oral glucose tolerance test (OGTT) at 24–28 weeks of gestation. Pregnant women diagnosed with GDM will make timely dietary adjustments and take medication if necessary [4]. In pregnant women with normal OGTT results but at high risk of GDM during pregnancy, blood glucose testing is repeated in the third trimester. Many risk factors for GDM have been identified and incorporated into clinical practice recommendations [5, 6], including age, race, BMI, family history of diabetes, previous history of GDM, and multiple pregnancies [7], insulin, fasting glucose, free fatty acids, triglycerides, hepatic lipase, and low-density lipoprotein [8]. Like a metabolic disease, the energy metabolism factor of pregnant women also plays a key role in the control of GDM [9, 10].

The object of this study is for GDM pregnant women with normal OGTT results in the second trimester. These data are more clinically meaningful. Meanwhile they are diagnosed by the existing test and non-invasive energy metabolism test. It improves the accuracy of GDM prediction, reduces unnecessary detection, and provides more time for a clinical intervention of GDM. For early prevention and treatment, it is necessary to find a risk model that can accurately and comprehensively predict the risk of the GDM pregnant women with normal OGTT results in the second trimester.

2.Materials and methods

2.1Background, population, exclusion, and inclusion criteria

This is a cross-sectional retrospective study. One hundred and sixty-eight pregnant women were randomly recruited from July 2018 to April 2019 for routine prenatal examinations and delivery in Haidian Maternal and Child Health Hospital of Beijing. According to the inclusion and exclusion criteria, a prospective observational cohort was established after obtaining informed consent, and metabolic conditions were detected according to the experimental design until the end of delivery. Ninety pregnant women completed oral glucose tolerance tests and energy metabolic tests at 24–28 weeks. The specific filter flowchart is shown in Fig. 1.

Figure 1.

Flowchart of research object selection.

Inclusion criteria: (1) Single pregnancy; (2) Regularity of the menstrual cycle; (3) Fetal development and gestational week consistent; (4) No chronic hypertension, diabetes, anemia, and other cardiovascular diseases, normal liver and kidney function; (5) Normal thyroid function, no obvious symptoms of acute or chronic infection, no other obstetric complications and complications; and (6) Pregnant women must not take blood pressure-lowering drugs and cardiovascular drugs. Exclusion criteria: (1) Multiple pregnancy; (2) Pregnancy complications, fetal malformation, and thyroid dysfunction occur during this pregnancy; (3) Termination of pregnancy; and (4) According to the record, during the measurement of metabolic parameters, the mask leakage occurred.

3.Results

A total of 62 pregnant women were included in this study, including 24 normal and 38 GDM pregnant women with normal OGTT results in the second trimester, and the basic baseline information was shown in Table 1. The age of pregnant women in the GDM group was higher than that in the normal group (29.5 ± 2.4 vs. 31.3 ± 4.1), and there was no significant difference in other factors.

Table 2 shows the correlation of energy metabolism factors, epidemiological factors, and biochemical factors with GDM. Due to the small amount of experimental data, the predictive variables of OR > 1, P< 0.05, and clinical high-risk factors were selected from the three groups. Vo2, REE/kg, RMR/kg, BMI, BMI-LP, IOM recommendations, and GLU were selected according to OR, P-value, and clinical suggestions. There was no data below the IOM recommendations, so the data of IOM recommendations only contains the within and above the IOM.

Table 3 shows the performance comparison results of the five models. By comparison, for GDM pregnant women with normal OGTT results in the second trimester, the model with the combined performance of the three factors was the most stable, with better prediction accuracy and ability. The models with and without energy metabolism factors were compared. After the addition of energy metabolism factors, the performance of the model is more stable, the sensitivity is higher, and the accuracy is better than the model without energy metabolism. It has been proved that energy metabolism is valuable for the inclusion of predictive models.

Table 4 shows the results of the comprehensive model. After the reverse elimination method is adopted, 5 variables are taken in the model. Including the Vo2/kg, REE/kg, BMI-LP, the IOM recommendations, and fasting plasma glucose. REE/kg, IOM recommendations, and GLU were significant risk factors for GDM pregnant women with normal OGTT results in the second trimester. However, Vo2/kg and BMI-LP were also protective of normal pregnant women. The regression equation was established according to the results:

The prediction model of the GDM pregnant women with normal OGTT results in the second trimester was:

4.Discussion

The decisive factors for GDM pregnant women with normal OGTT result in the second trimester are various. In this study, Vo2/kg, REE/kg, BMI-LP, the IOM recommendations, and fasting plasma glucose is proven to be effective in predicting the diagnosis of GDM in the third trimester of pregnancy. Among the pregnant women included in the experiment, although they were all normal pregnant women in the second trimester, there are still differences between pregnant women who were normal before delivery and pregnant women diagnosed with diabetes in the third trimester. But due to the small number of samples, normal pregnant women and GDM pregnant women with normal OGTT results in the second trimester could not be well represented. The sensitivity and positive prediction rate of the model were low, and most of the clinical high-risk factors in this study did not show the same high risk as other studies. However, the inquiry is in the middle of pregnancy is normal pregnant women, so in the middle of pregnancy is smaller for part of the risk factors related. More conclusions can be drawn if more sample sizes can be included to discuss the differences in risk factors between GDM and normal pregnant women with OGTT in the second trimester.