Gestational and Previous Diabetes in Pregnancy: Perinatal Results

  • Original Article
  • Asp Biomed Clin Case Rep. 2020 Mar 14;3(1):75-86

Canêdo JA1, Faleiros GQA1, dos Santos Toledo PM1, Catizani RB1, Panconi CR2, Coutinho LM2, de Souza HD2, Machado PP2, Andrade LB3, Antunes MA2, de Oliveira MF2, Zimmermmann JB2*

1Faculty of Medicine of Barbacena, Minas Gerais, Brazil

2Faculty of Medicine, Federal University of Juiz de Fora, Minas Gerais, Brazil

3Universitary Hospital, Federal University of Juiz de Fora and High Risk Prenatal Care Group, Cnpq, Brazil

Corresponding Author: Prof. Juliana Barroso Zimmermmann

Address: Faculty of Medicine, Federal University of Juiz de Fora, Maternal and Child Department of Medicine’s Faculty, Juiz de Fora, MG, Brazil; E-mail:

Received date: 12 December 2019; Accepted date: 06 March 2020; Published date: 14 March 2020

Citation: Canêdo JA, Faleiros GQA, dos Santos Toledo PM, Catizani RB, Panconi CR, Coutinho LM, de Souza HD, Machado PP, Andrade LB, Antunes MA, de Oliveira MF, Zimmermmann JB. Gestational and Previous Diabetes in Pregnancy: Perinatal Results. Asp Biomed Clin Case Rep. 2020 Mar 14;3(1):75-86.

Copyright © 2020 Canêdo JA, Faleiros GQA, dos Santos Toledo PM, Catizani RB, Panconi CR, Coutinho LM, de Souza HD, Machado PP, Andrade LB, Antunes MA, de Oliveira MF, Zimmermmann JB. This is an open-access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

Keywords: Gestational and Previous Diabetes in Pregnancy; Macrosomia; Glycaemia; Diabetes Mellitus


Objective: Evaluating the association between gestational diabetes and fetal/maternal complications such as poor obstetric outcomes.

Methods: Historical cohort comprising patients from the High-Risk Service of Federal University of Juiz de Fora (UFJF,) who were diagnosed with diabetes (exposed), as well as patients from the Low-Risk Service of UFJF (non-exposed). Data generated through anamnesis, physical examination and medical conduct, as well as data of newborns such as fetal weight, ICU admission and fetal/neonatal death), were collected and stored in the Epi Info software (version 6.0); p < 0.05.

Results: 176 patients treated in the aforementioned services, 108 diabetic, and 68 non-diabetics, were investigated in the current study. In total, 92 (52.2%) of them were diagnosed with Gestational Diabetes Mellitus (GDM); 6 had DM type 1 (3.4%) and 10 had DM type 2 (5.6%). Therefore, 68 patients (38.6%) presented normal glucose metabolism. The mean age of the patients was 30.27 ± 6.77 years, the mean number of births was 1.06 ± 1.20. Macrosomia was diagnosed in 6.81% (n = 6) of the cases; it was associated with maternal glycemia (p < 0.05). D- and F-class pregnant women, who had been previously diagnosed with diabetes, presented lower fetal weight than other pregnant women (p = 0.03). Treatment was based on diet, insulin or metformin, whenever necessary. Fasting glycemia levels decreased throughout the gestational trimesters. Eighteen (10.2%) preterm fetuses were identified; 12 were born from diabetic mothers and 6 were born from non-diabetic ones (p = 0.01; X2 = 10.51). All infants hospitalized in the neonatal ICU (n = 10) were born from diabetic mothers; their mean gestational age was 36.28 + 2.9 weeks, whereas the mean gestational age of infants who were not hospitalized in the ICU was 38.31 ± 1.5 (p = 0.005; T = 12.58). Cesarean section was the most common way of delivery adopted for diabetic pregnant women (p = 0.04).

Conclusion: Based on the results, gestational diabetes (GDM) is a predisposing factor to fetal macrosomia, prematurity, and hospitalization in neonatal ICUs. Pregnant women subjected to proper glycemic control in the current study presented lower complication rates in comparison to other studies in the literature.


Nowadays, approximately 415 million adults around the world have Diabetes mellitus (DM), whereas 318 million adults have glucose intolerance and present a high risk of developing the disease in the future. DM and its complications are among the leading causes of death in most countries – based on estimates, DM is responsible for 1 out of 12 adult deaths worldwide [1]. Obstetric history of gestational diabetes mellitus (GDM) is the major risk factor for the development of type 2 diabetes and metabolic syndrome among women [1,2].

GDM is one of the most common gestational complications; this condition leads to considerable perinatal risk when it remains undiagnosed or is not properly treated. Fetal macrosomia, neonatal birth injuries, neonatal hypoglycemia and hyperbilirubinemia, neonatal respiratory distress syndrome, hypocalcemia, prematurity, and intrauterine fetal death stand out among fetal complications [3-5]. Also, GDM is believed to determine complications such as increased incidence of obesity, hypertension, metabolic syndrome and diabetes in these newborns’ adulthood. A possible explanation for this outcome is based on epigenetics [6].

Epigenetic inheritance enables different organisms to adjust their gene expression, based on the environment they live in, without changing their genome. For example, experiences lived by parents (e.g., diets) can be passed on to future generations; thus, fetuses who grow in environments with an excess of sugars would get used to hyperinsulinemia and lipid storage, and this process could result in the development of metabolic syndrome in their adult life. Another interesting and contradictory finding is that fetuses subjected to lack of nutrients could also develop type 2 diabetes in the future because they get used to store energy to survive. Therefore, the intrauterine environment can modulate one’s adult life, regardless of genomic coding. This reasoning is the basis of the theory known as intrauterine programming [6-8].

Diabetic pregnant women presenting poor metabolic control are prone to higher miscarriage, infection, high blood pressure, pre-eclampsia, preterm delivery, and cesarean delivery rates. These women will be at increased risk of developing type 1 or 2 diabetes after pregnancy; however, such risk can be minimized or postponed by providing them lifestyle-changing guidelines [1]. Congenital malformations, IUGR (Intrauterine Growth Restriction), oligohydramnios and fetal death stand out among the consequences faced by pregnant women who were diagnosed with diabetes before pregnancy and who did not present proper blood glucose control [8,9].

It is necessary to screen DM during pregnancy due to the substantial number of maternal and fetal complications that may happen; however, several criteria are reported and used in different healthcare services in Brazil and abroad. According to the HAPO (Hyperglycemia and Adverse Pregnancy Outcomes) study [10] conducted in 2008, there is not a single cutoff point for glycemia levels above which the risk of adverse outcomes would increase, and it means that unfavorable events happen even at normal blood glucose levels. The American Diabetes Association (ADA) [11] endorsed this diagnostic criterion in 2011, based on studies carried out by the International Association of Diabetes and Pregnancy Study Groups (IADPSG) [12], which defined the following cutoff values: 92 mg/dl for fasting, 180 mg/dl for 1 h after the intake of 75g of dextrosol (anhydrous glucose) and 153 mg/dl for 2 hours after the intake of the same dextrosol dose.

The service in the assessed hospital has been using these criteria since then and it was possible noticing an increased number of GDM cases. Therefore, it is necessary for assessing diabetic pregnant women in Brazil, as well as investigating the association between GDM and unfavorable maternal/fetal outcomes.


The current study analyzed a historical cohort comprising patients treated in the low- and high-risk services of the Medical School of Federal University of Juiz de Fora (BRAZIL). Pregnant women diagnosed with diabetes were considered exposed patients, whereas non-diabetic pregnant women were considered non-exposed patients. They were referred from the low obstetric risk centers of the two aforementioned services. It was possible comparing the pregnant women because the outpatient clinics adopted the protocol by FEBRASGO [13] for clinical follow-up [14-16].

The sample calculation was based on statistics from the UFJF Obstetrics Service. After signing an agreement with Juiz de Fora City Hall, the service at UFJF took the responsibility of providing care to diabetic pregnant women who live in Juiz de Fora city and its surrounding region; consequently, the frequency of these patients in our facilities was extremely high. If one takes into consideration the frequency of “exposed” patients (40%) and the possible existence of “non-exposed” patients (10%), the sample size required for the current study comprised 51 patients per group, at 5% alpha error and 20% beta error, but we selected 176 patients for this study – 108 were diabetic and 68 were metabolically healthy.

Patients, who had agreed to participate in the study, as well as to be subjected to the protocol adopted by the healthcare service, were included in the study. Those who did not allow their data to be evaluated or who did not agree with the protocol of the aforementioned service were excluded from it. Primary outcomes comprised fetal and neonatal death, newborn weight (NB), NB hospitalization in neonatal ICU and prematurity and secondary outcomes comprised pre-eclampsia, other intercurrences in prenatal care and intercurrences responsible for pregnancy interruption.

All anamnesis data (age, gestational age, gestation, miscarriage, history of DM and intercurrences in the current and previous pregnancies – intrauterine fetal death, fetal macrosomia, polyhydramnios, hypertensive syndromes), physical examination (blood pressure, weight gain), medical conduct (insulin therapy and diet) and newborns (weight) were also collected. Fasting blood glucose was measured in the three gestational trimesters.

Blood glucose measurements were taken in the 3 gestational trimesters based on the enzymatic method by using fluoridated plasma kept at 2-8°C for at most two days after patients fasted for 8 hours. Values ranging from 60 to 91 mg/dl were normally based on criteria set by ADA [11]. Glycaemia ranging from 92 and 125 mg/dl were considered abnormal and compatible with GDM, whereas glycemia higher than 126 mg/dl was considered abnormal and compatible with DM before pregnancy [17,18].

The oral glucose tolerance test with 75g of dextrosol (OGTT75g) was applied to all pregnant women who presented normal fasting glycemia (< 92 mg/dl) from the 24th to the 28th gestational week. The herein adopted cutoff values were > 92 mg/dl (at fasting), > 180 mg/dl (1h after the intake of 75g of dextrosol) and > 153 mg/dl (2 h after the intake of 75g of dextrosol). Abnormal values in the glycemic curve were diagnosed as GDM. The test was performed with fluoridated plasma, which was kept at 2-8°C for at most two days [17,18].

All patients perform examinations with obstetric ultrasound from the 34th to the 36th gestational weeks were used to diagnose polyhydramnios and macrosomia. Amniotic fluid index (AFI) higher than 18 cm was diagnosed as polyhydramnios, oligohydramnios was diagnosed when the largest pocket was smaller than 2 cm and macrosomia was diagnosed when the waist circumference was higher than the 80th percentile of the gestational age [19-21].

All the diabetic patients were classified based on the criteria suggested by Priscilla White (PW) classification [22] (Fig-1).

Information collected during the study was exported to a system that was specifically developed for this research in the Access platform and processed in the computer through statistical processing resources available in the Epi-Info software, version 6.04. The frequency of the examined variables was distributed, and the prevalence rates indicated for each case were calculated. The means and standard deviations of variables expressed in numerical scale were also calculated. The comparison between groups identified among participants was performed in contingency tables type R x C (in the case of categorical variables) or through comparison of means (in the case of numerical variables). The Chi-square and/or Student’s t-tests were used to analyze the statistical significance of differences observed in the analysis, depending on the nature of data to be compared. Linear regression was used to associate numerical variables such as weight, blood pressure, AFI, fasting and postprandial glycemia, and fetal weight. The significance level adopted in the analysis was 5%.

The present study is part of the project approved by the Ethics and Research Commission of Minas Gerais State Hospital Foundation, (country), under Opinion n. 44281815.3.0000.5147.

Fig-1: Priscilla White’s classification for diabetic patients identified in the study

There are 2 classes of gestational diabetes (diabetes which began during pregnancy): Class A1: gestational diabetes; diet controlled; Class A2: gestational diabetes; medication controlled. The second group of diabetes which existed before pregnancy can be split up into these classes: Class B: onset at age 20 or older or with duration of less than 10 years; Class C: onset at age 10-19 or duration of 10–19 years; Class D: onset before age 10 or duration greater than 20 years; Class E: overt diabetes mellitus with calcified pelvic vessels; Class F: diabetic nephropathy; Class R: proliferative retinopathy; Class H: ischemic heart disease; Class T: prior kidney transplant


We investigated 176 patients, in 108 (61.36%) were diabetic and 68 (38.63%) were metabolically healthy. The mean age of the patients was 30.27 ± 6.77 years. Clinical and epidemiological data are shown in (Table-1) and (Table-2).

Diabetic pregnant women recorded higher glycemic levels in the first, second and third gestational trimesters than the non-exposed group. However, the mean glycemia levels recorded for the exposed group decreased as the gestational trimesters progressed. The mean glucose levels are shown in (Table-3).

The oral glucose tolerance test was applied to only 127 patients because the remaining ones had been screened through fasting glycemia and did not require OGTT application, based on previously established criteria [11]. Based on fasting glycemia and the OGTT with 75 g of dextrosol, 52.27% (n = 92) of patients were diagnosed with gestational diabetes; however, 3.41% (n = 6) of pregnant women were known to be diabetic patients type 1 and 5.68 % (n = 10) were type 2. Also, 38.64% (n = 68) of the patients were considered metabolically healthy in the glucose test. DM cases were classified based on criteria set by Priscilla White (PW), as shown in (Fig-1).

The treatment was based on diet developed for diabetic patients, as well as on the use of sweeteners, and of insulin associated with metformin, whenever necessary. Exercising was encouraged; however, 100% of patients reported to practice only routine exercises throughout the day. No patient practiced yoga, pilates or aqua aerobics. There was no case of exclusive metformin use. The treatment users are shown in (Table-4) and glucose means are shown in (Table-5).

The mean weight of infants born from diabetic mothers was 3215.08 ± 551.34 g, whereas the mean weight of those born from non-diabetic mothers was 3146.44 ± 547.49 g (p = 0.47; T = 1.97). Macrosomia was diagnosed in 6.81% (n = 6) of newborns. The mean weight of newborns of diabetic mothers who used insulin was 3390.41 ± 467.71 g, whereas the mean weight of newborns of non-insulin users was 3282 ± 505.0 g (p = 0.287; T = 1.9). The newborn weight classification and its association with PW’s classification are shown in (Table-6). D and F class pregnant women presented lower fetal weight than the other pregnant women (p = 0.03). There was an association between macrosomia and mean glycemic level of 115.33 ± 42.74 in the third gestational trimester (p = 0.03). There was a single case of intrauterine fetal death involving a patient diagnosed with GDM, who presented good dietary-based glycemic control (A1 of PW in Table-6); true umbilical cord knot was identified after labor induction.

There were 18 preterm fetuses (10.2%); 12 were born from diabetic mothers and 6 were born from non-diabetic mothers (p = 0.01; X2 = 10.51). Thus, it is possible saying that diabetes is a predisposing factor for prematurity. Ten (10) newborns were referred to the neonatal ICU and discharged in good health conditions. The mean weight of fetuses referred to the ICU was 2698.62 ± 504.78 g, whereas the mean weight of newborns who were directly referred to the rooming-in was 3207 ± 504.75 g (p = 0.01; T = 6.69). All infants hospitalized in the neonatal ICU (n = 10) were born from diabetic mothers; the mean gestational age of these infants was 36.28 ± 2.9 weeks, whereas the mean gestational age of infants who were not hospitalized in the ICU was 38.31 ± 1.5 (p = 0.005; T = 12.58).

Cesarean section was the delivery method most often applied to diabetic pregnant women (p = 0.04). The association between PW’s classification and gestational age at the delivery time was performed; the worse the PW classification, the younger the gestational age at pregnancy interruption time (p = 0.0019; X2 = 20.87). Thus, the most severe classifications were the ones that presented premature pregnancy interruption.

There was one case of congenital malformation (Tetralogy of Fallot) involving an NB of type 1 diabetic mother who presented good glucose control after the second gestational trimester, although the mother’s blood glucose levels were high when she got pregnant. This NB died 6 days after delivery; the infant presented hemodynamic instability and could not be subjected to surgery. We identified 10 cases of neonatal ICU admission, 18 cases of prematurity, 1 case of intrauterine fetal death and 1 case of neonatal death were identified. The (Fig-2) presents these results.

The secondary outcomes were pre-eclampsia, urinary tract infection, maternal hypoglycemia, polyhydramnios, vaginitis and chronic fetal distress Urinary tract infection (n = 3; 3.4%), hypoglycemia (n = 2; 2.27%), polyhydramnios (n = 2; 2.27%), vaginitis (n = 4, 4.54%), pre-eclampsia (n = 4; 4.54%) and chronic fetal distress with IUGR (n = 2; 2.27%) stood out among prenatal complications.

Intrauterine fetal death (0.57%), intrauterine growth restriction (IUGR) (1.14%), fetal distress (3.9%) and pre-eclampsia (5.11%) were the main complications identified in pre-natal follow-ups that resulted in pregnancy interruption (delivery). The association between these variables and mean blood glucose levels in each gestational trimester was performed. There was no association among first, second and third trimester blood glucose levels and variables such as fetal death (p = 0.3), IUGR (p = 0.2), pre-eclampsia (p = 0.8) and fetal distress (p = 0.7).

Table-1: Epidemiological and Clinical Aspects of the Studied Patients

Table-2: Previous Mothers’ Diseases

Table-3: Mean of Blood Glucose in the Three Gestational Trimesters

Table-4: Distribution of Patients in PW classification and type of Diabetes Identified and Treatment Performed

Table-5: Average Blood Glucose values per Trimester in Insulin users and non-users

Table-6: Association between PW Classification and Fetal Weight (grams)


Frequency of primary outcomes: Admission to neonatal ICU, prematurity, macrosomia, fetal and neonatal death.


The current study assessed 176 pregnant women (mean age = 30.27 ± 6.77 years; p < 0.05) – exposed pregnant women were the ones presenting the highest mean age, as well as the largest number of pregnancies and births. These data are compatible with the literature since older women also have longer menacme; consequently, they are more likely to experience more pregnancies and births [8,14,15]. It is worth emphasizing that these pregnant women were part of the exposed group; therefore, they experienced risk pregnancy and were more likely to present associated pathologies such as hypertension, hypothyroidism, thrombophilia, and diabetes before pregnancy. Thus, besides the pathology to be studied (DM), pregnant women in the exposed group presented other complicating risk factors such as CAH, thrombophilia, and hypothyroidism, which can affect the obstetric outcomes. According to a study carried out at IMIP (2012) with 35-to-39-year-old pregnant women, more than 70% of patients had some type of complication, including GDM. Thus, the association between age difference and pathologies that existed before pregnancy may be determinant factors for the worst maternal-fetal outcomes [23].

There was no significant association between the patient’s weight before pregnancy and GDM. However, patients diagnosed with diabetes, either before or during pregnancy, had lower weight gain than patients in the non-exposed group. According to a study conducted in Kuwait with 868 mothers who did not have history of diabetes mellitus before pregnancy, 109 patients (12.6%, 95% CI: 10.4, 14.8) reported to have been diagnosed with GDM during their last pregnancy; GDM prevalence increased as maternal age and pre-gestational BMI increased [24].

Results in the present study do not comply with studies available in the literature, according to which excessive weight gain is associated with gestational diabetes. This difference may be associated with the previous control applied to type I and II diabetic patients assessed in the current study. Nowadays, the assessed institution has a specific outpatient clinic focused on pre-gestational DM control; these patients are followed-up before pregnancy. Another study has shown that promoting a healthy body mass index and lower gestational weight gain can help to reduce the number of patients with gestational complications, which seems to be the key to the success of our diabetic patients’ pregnancies [25]. On the other hand, it is essential mentioning that the mean weight gain of low-risk pregnant women was extremely high. Based on data analysis, few patients presented excessive weight gain and increased the mean values recorded for this variable. Both groups presented similar median weight gain.

These results are consistent with the ones reported by Yan et al (2019) [26], who evaluated 13,738 patients, in total. They conducted a multivariate analysis and found that patients’ systolic blood pressure (OR 1,015; 90% CI 1,011-1.02) was a risk factor associated with the incidence of GDM; this finding complies with the present study. The plasma glucose levels showed that diabetic pregnant women recorded increased glucose levels in the first, second and third gestational trimesters, which was expected if one takes into consideration the herein investigated pathology. However, according to the evaluation of the mean blood glucose recorded for the exposed group in each gestational trimesters, these patients presented a substantial decrease in this parameter throughout the gestational trimesters (from 98.66 ± 25.14 to 87.56 ± 22.73). Efficient prenatal follow-ups, trained staff, and test availability can make a difference in the prognosis of these patients. Insulin dose manipulation, dietary control and changes in dietary habits were the strategies adopted to control the blood glucose levels in these patients, who have presented reduced glycemic levels, based on the comparison between gestational trimesters. Thus, it is possible saying that efficient prenatal care works as a modulator of unfavorable maternal outcomes [27].

According to Priscila White’s classification, most patients included in the present study were in the A1 category, which indicated predominantly dietary treatment and was compatible with the medical literature [10-12]. At the time the HAPO study was published, there was criticism regarding the excessive number of patients who would be considered diabetic when fasting glucose was abnormal, regardless of the OGTT results. Later, ADA (2011) [11] has explained that the inclusion of pregnant women in the diabetic group did not necessarily mean that they would all be medicated. On the contrary, prenatal care, proper dietary guidelines, exercising, and diet would suffice for most patients and could change the maternal-fetal outcome. Therefore, the initial approach applied to all pregnant women comprised diet, orientations, clinical control and exercising [10-12].

The physical exercise indicated in the current study was not performed by patients. Despite the encouragement to do so, none of our patients was enrolled in yoga, pilates or aqua aerobics classes. These exercises have been reported to help to reduce excessive maternal weight gain and the incidence of fetal macrosomia [28]. Pregnant women who were subjected to dietary control in the current study presented adequate blood glucose levels throughout pregnancy. Those who used insulin did not always reach the ideal blood glucose value, despite the glucose reduction identified throughout the gestational trimesters. These patients needed adjustments in their insulin doses or the association between regular and NPH insulin. Therefore, it is believed that controlled physical exercises could help to achieve such control [28].

However, one cannot neglect that the economic factor may have been decisive in this regard since the service provided at the assessed institution does not provide free physical exercise classes for pregnant women. The social and economic features of the selected patients refer to people who predominantly earn one minimum wage per month and, therefore, who have unfavorable socioeconomic status. It is known that this population does not have easy access to nutrition and leisure, fact that overall jeopardizes pregnancy and conceptus. Thus, low purchasing power can lead to lower access to food, in quantitative and qualitative terms, as well as to the consumption of high energy density food products, which, in their turn, are cheaper and contribute to unsuccessful glycemic control. However, we have tried to control this variable by encouraging patients to eat legumes, vegetables, and seasonal fruits, which are economically easier to be purchased. One cannot neglect the fact that, besides their low economic conditions, these patients also have low schooling. Although this association was not investigated in the current study, it can hinder patients’ access to information about pregnancy and newborn care or even compromise their understanding about what is informed; both situations can affect the health of the mother-child binomial [29].

It is known that vasculopathy starts from category D; the fetal results recorded in the present study were close to IUGR, prematurity, and oligohydramnios [30]. Based on the comparison between fetal weight and PW categories, the fetuses of pregnant women with vasculopathy presented lower weight due to endothelial damages that extended towards the placental bed. On the other hand, categories A, B and C recorded the highest fetal weights, which were associated with maternal blood glucose levels. The highest likelihood of macrosomia development was observed in pregnant women with increased blood glucose levels (p < 0.05). These results are consistent with the ones reported by Rodrigues et al. [31], who found that high blood glucose levels are independent predictors of weight gain in infants born from diabetic mothers.

Diabetic pregnant women presented the following primary outcomes: fetal and neonatal mortality (1.8%), macrosomia (6.81%), prematurity (16.6%) and hospitalization in neonatal ICU (9 %). All these findings presented lower rates than the ones reported in many other services [32-35]. There was an association between diabetes and prematurity and between diabetes and hospitalization in neonatal ICU (p < 0.05).

Wang et al. (2019) [32] conducted a study aimed at identifying stillborn babies of diabetic pregnant women admitted at Westmead Hospital from 2006 to 2017. They identified 37 women (seven with type 1 diabetes [DM1], 11 with type 2 diabetes [DM2] and 19 with DMG) who had 38 stillborn babies. The main stillbirth causes comprised lethal congenital malformations (n = 9), placental and umbilical abnormalities (n = 6), intrauterine growth restriction (IUGR; n = 6) and obstetric factors (n = 4). Malformations were predominantly cardiovascular (n = 7), musculoskeletal (n = 5) and gastrointestinal (n = 4). There was no difference in the proportion of stillborn infants with malformations between groups of patients diagnosed with diabetes before and during pregnancy (p = 0.22). The present study recorded the neonatal death of an infant born from a pregnant patient who had been diagnosed with diabetes before pregnancy (the fetus presented cardiac malformation – Tetralogy of Fallot), as well as the intrauterine fetal death (during labor) of an infant born from a patient diagnosed with gestational diabetes. True umbilical cord knot was identified after fetal expulsion through the vaginal route.

Hospitalization in neonatal ICU, macrosomia and prematurity presented increased association with diabetic pregnant women (p < 0.05). According to a study conducted by Stogianni et al (2019) [33] with 280 pregnant women, 48 patients had pre-gestational diabetes, 97 had DMG and 135 did not have diabetes. Patients in the diabetes group had higher BMI at the beginning of pregnancy (p = 0.0001), lower gestational weight gain (11.1 ± 6.7 kg vs 13.1 ± 7.1 kg, p = 0.005), larger number of preterm labors (p = 0.0001) and larger number of macrosomic newborns (p = 0.06) than the non-diabetic group. Mothers with GDM gained less weight (9.9 kg Vs 13.5 kg) (p = 0.006). Mothers with type 1 diabetes gave birth to a larger number of macrosomic babies (60%) than mothers with DM2 (27%). Urinary tract infection (n = 3; 3.4%), hypoglycemia (n = 2; 2.27%), polyhydramnios (n = 2; 2.27%), vaginitis (n = 4; 4.54%), pre-eclampsia (n = 4; 4.54%) and chronic fetal distress with IUGR (n = 2; 2.27%) were the secondary outcomes identified during prenatal follow-ups. These findings are compatible with data available in the medical literature [28-32,34,35].

This study was very important because it showed that a trained team can offer the population that uses the public service a quality service, even for high-risk pregnant women, even in a developing country. Our service to serve the needy population of the city and region and the university not only as a source of knowledge for students but also to the strong assistance that we have in public universities in our country. In addition, glycemic control is largely responsible for the success of these pregnancies. We were unable to establish a cut-off point for the blood glucose level that would be at risk for fetal death or other perinatal complications and perhaps this could be considered a weak point in our study, but undoubtedly adequate blood glucose control was responsible for the good result. and this is also the great legacy of this study.


However, the current study recorded less complications than the ones reported in the medical literature. This result can be attributed to good glycemic control which is the best allied to favorable perinatal outcomes in pregnant women with diabetes mellitus. The methods adopted to achieve this outcome can change based on patients’ treatment (diet, insulin, exercising); however, glycemia level close to normal values is the most important element in such control. The current study could not set a cut-off point capable of associating blood glucose levels and unfavorable outcomes; it may have happened because these levels are labile and change after food and medication intake. However, based on the collected data, diabetic pregnant women presented unfavorable fetal outcomes (prematurity and hospitalization in neonatal ICU) and increased blood glucose levels were associated with fetal macrosomia.


[1] Soares RI. Diabetes gestacional e programação fetal (Master’s thesis). <>

[2] Reichelt AJ, Weinert LS, Mastella LS, Gnielka V, Campos MA, Hirakata VN, Oppermann MLR, Silveiro SP, Schmidt MI. Clinical characteristics of women with gestational diabetes – comparison of two cohorts enrolled 20 years apart in southern Brazil. Sao Paulo Med J. 2017 Jul-Aug;135(4):376-82. [PMID: 28793129]

[3] Ribeiro SP, Costa RB, Dias CP. Macrossomia neonatal: fatores de risco e complicações pós-parto. Nascer e Crescer. 2017 Mar;26(1):21-30.

[4] Oliveira AC, Graciliano NG. Hypertensive disorders of pregnancy and gestational diabetes mellitus in a public maternity hospital of a Northeastern Brazilian capital, 2013: prevalence and associated factors. Epidemiol. Serv. Saúde [online]. 2015;24(3):441-51.

[5] Massucatti LA, Pereira RAP, Maioli TU. Prevalência de diabetes gestacional em Unidades de Saúde Básica. Rev Enferm Atençao Saude. 2012;1(1):70-79.

[6] Elner VR, Siqueira IR. Epigenética aplicada à saúde e a doença. Princípios fundamentais baseados em evidências atuais. <>

[7] Buzinaro EF, Berchieri CB, Haddad AL, Padovani CR, Pimenta WD. Sobrepeso na adolescência de filhos de mães que tiveram distúrbios glicêmicos na gestação. Arquivos Brasileiros de Endocrinologia & Metabologia. 2008 Feb;52(1):85-92.

[8] Zimmermmann JB, Coutinho T, Duarte AMB. Condutas em obstetrícia para gestação de baixo risco. Protocolo do Serviço de Obstetrícia da Faculdade de Medicina da UFJF. 2018 Sept:349.

[9] Uzun Çilingir IG. Pregnancy Outcomes in Women with Strictly Controlled Type 1 Diabetes Mellitus. Indian J Endocrinol Metab. 2018 Nov-Dec;22(6):798-800. [PMID: 30766821]

[10] HAPO Study Cooperative Research Group, Metzger BE, Lowe LP, Dyer AR, Trimble ER, Chaovarindr U, Coustan DR, Hadden DR, McCance DR, Hod M, McIntyre HD, Oats JJ, Persson B, Rogers MS, Sacks DA. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med. 2008 May 8;358(19):1991-2002. [PMID: 18463375]

[11] ADA. Standards of Medical Care in Diabetes. American Diabetes Association. Position Statement. Diabetes Care. 2011;34(Suppl1):S11-61.

[12] International Association of Diabetes and Pregnancy Study Groups Consensus Panel, Metzger BE, Gabbe SG, Persson B, Buchanan TA, Catalano PA, Damm P, Dyer AR, Leiva Ad, Hod M, Kitzmiler JL, Lowe LP, McIntyre HD, Oats JJ, Omori Y, Schmidt MI. International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care. 2010 Mar;33(3):676-82. [PMID: 20190296]

[13] FEBRASGO. Ficha pré-natal. <>

[14] Zimmermmann JB, Nani AC, Junqueira CB, Iani GC, Gomes G, Bahia S. Aspectos ginecológicos e obstétricos de pacientes atendidas nos serviços público e privado de saúde: há diferenças?. Revista Brasileira de Ginecologia e Obstetrícia. 2011 Dec;33(12):401-7.

[15] Amaral FE, Amarante PO, de Pinho Andrade RV, Resende U, Marangoni MC, Cruz R, Zimmermmann JB. Qualidade do pré-natal: uma comparação entre gestantes atendidas na Faculdade de Medicina de Barbacena e na Universidade Federal de Juiz de Fora. Clinical & Biomedical Research. 2016 Oct 21;36(3):124-34.

[16] Oliveira MA, Vellarde GC, Sá RAM. Entendendo a pesquisa clínica III: estudos de coorte. Femina. 2015;43(3):105-10.

[17] BRASIL. Rastreamento e Diagnóstico do Diabetes mellitus gestacional no Brasil. <>

[18] Sociedade Brasileira de Diabetes. Diabetes mellitus gestacional: diagnóstico, tratamento e acompanhamento pós-gestação. <>

[19] Velho MT, Morais EN, Ethur AB. Determinação Ultra-sonográfica do Índice do Líquido Amniótico em Grávidas Normais, da 12ª à 42ª Semana de Gravidez. Revista Brasileira de Ginecologia e Obstetrícia. 2001 May;23(4):225-32.

[20] Bandarra ARS. Macrossomia na diabetes gestacional. <>

[21] BRASIL. FEBRASGO. Pré-eclâmpsia. <>

[22] Bennett SN, Tita A, Owen J, Biggio JR, Harper LM. Assessing White’s classification of pregestational diabetes in a contemporary diabetic population. Obstet Gynecol. 2015 May;125(5):1217-23. [PMID: 25932851]

[23] Alves NCC, Feitosa KMA, Mendes MES, Caminha MFC. Complicações na gestação em mulheres com idade maior ou igual a 35 anos. Rev Gaúcha Enferm. 2017;38(4): e2017-0042.

[24] Groof Z, Garashi G, Husain H, Owayed S, AlBader S, Mouhsen H, Mohammad A, Ziyab AH. Prevalence, Risk Factors, and Fetomaternal Outcomes of Gestational Diabetes Mellitus in Kuwait: A Cross-Sectional Study. J Diabetes Res. 2019 Mar 3;2019:9136250. [PMID: 30944829]

[25] Santos S, Voerman E, Amiano P, Barros H, Beilin LJ, Bergström A, Charles MA, Chatzi L, Chevrier C, Chrousos GP, Corpeleijn E, Costa O, Costet N, Crozier S, Devereux G, Doyon M, Eggesbø M, Fantini MP, Farchi S, Forastiere F, Georgiu V, Godfrey KM, Gori D, Grote V, Hanke W, Hertz-Picciotto I, Heude B, Hivert MF, Hryhorczuk D, Huang RC, Inskip H, Karvonen AM, Kenny LC, Koletzko B, Küpers LK, Lagström H, Lehmann I, Magnus P, Majewska R, Mäkelä J, Manios Y, McAuliffe FM, McDonald SW, Mehegan J, Melén E, Mommers M, Morgen CS, Moschonis G, Murray D, Ní Chaoimh C, Nohr EA, Nybo Andersen AM, Oken E, Oostvogels A, Pac A, Papadopoulou E, Pekkanen J, Pizzi C, Polanska K, Porta D, Richiardi L, Rifas-Shiman SL, Roeleveld N, Ronfani L, Santos AC, Standl M, Stigum H, Stoltenberg C, Thiering E, Thijs C, Torrent M, Tough SC, Trnovec T, Turner S, van Gelder M, van Rossem L, von Berg A, Vrijheid M, Vrijkotte T, West J, Wijga AH, Wright J, Zvinchuk O, Sørensen T, Lawlor DA, Gaillard R, Jaddoe V. Impact of maternal body mass index and gestational weight gain on pregnancy complications: an individual participant data meta-analysis of European, North American and Australian cohorts. BJOG. 2019 Jul;126(8):984-95. [PMID: 30786138]

[26] Yan B, Yu Y, Lin M, Li Z, Wang L, Huang P, Song H, Shi X, Yang S, Li X, Li X. High, but stable, trend in the prevalence of gestational diabetes mellitus: A population-based study in Xiamen, China. J Diabetes Investig. 2019 Sep;10(5):1358-64. [PMID: 30869198]

[27] Weinert LS, Silveiro SP, Oppermann ML, Salazar CC, Simionato BM, Siebeneichler A, Reichelt AJ. Diabetes gestacional: um algoritmo de tratamento multidisciplinar. Arquivos Brasileiros de endocrinologia & metabologia. 2011 Oct;55(7):435-45.

[28] Brasil. Diabetes na gestação: recomendações para o preparo e o acompanhamento da mulher com diabetes durante a gravidez. Diretrizes da Sociedade Brasileira de Diabetes. <>

[29] Andrade BD, Silva AC, Santos MT, Campos T, Luquetti SC, Cândido AP, Oliveira RM, Nemer AS, Netto MP. Fatores nutricionais e sociais de importância para o resultado da gestação, em mulheres em acompanhamento na rede de atenção primária de Juiz de Fora. Rev Med Minas Gerais. 2015;25(3):344-52.

[30] Mañé L, Flores-Le Roux JA, Gómez N, Chillarón JJ, Llauradó G, Gortazar L, Payà A, Pedro-Botet J, Benaiges D. Association of first-trimester HbA1c levels with adverse pregnancy outcomes in different ethnic groups. Diabetes Res Clin Pract. 2019 Apr;150:202-10. [PMID: 30880095]

[31] Tavares MD, Lopes ÉS, Araújo RA, de Sousa Azulay RS, dos Santos Faria M. Profile of Pregnant Women with Gestational Diabetes Mellitus at Increased Risk for Large for Gestational Age Newborns. Revista Brasileira de Ginecologia e Obstetrícia/RBGO Gynecology and Obstetrics. 2019 May;41(05):298-305.

[32] Wang M, Athayde N, Padmanabhan S, Cheung NW. Causes of stillbirths in diabetic and gestational diabetes pregnancies at a NSW tertiary referral hospital. Aust N Z J Obstet Gynaecol. 2019 Aug;59(4):561-66. [PMID: 30663043]

[33] Stogianni A, Lendahls L, Landin-Olsson M, Thunander M. Obstetric and perinatal outcomes in pregnancies complicated by diabetes, and control pregnancies, in Kronoberg, Sweden. BMC Pregnancy Childbirth. 2019 May 7;19(1):159. [PMID: 31064335]

[34] Gortazar L, Flores-Le Roux JA, Benaiges D, Sarsanedas E, Payà A, Mañé L, Pedro-Botet J, Goday A. Trends in prevalence of gestational diabetes and perinatal outcomes in Catalonia, Spain, 2006 to 2015: the Diagestcat Study. Diabetes Metab Res Rev. 2019 Jul;35(5):e3151. [PMID: 30865356]

[35] Pintaudi B, Fresa R, Dalfrà M, Dodesini AR, Vitacolonna E, Tumminia A, Sciacca L, Lencioni C, Marcone T, Lucisano G, Nicolucci A, Bonomo M, Napoli A; STRONG Study Collaborators. The risk stratification of adverse neonatal outcomes in women with gestational diabetes (STRONG) study. Acta Diabetol. 2018 Dec;55(12):1261-73. [PMID: 30221320]