Diabetic Pregnant Women Research Articles

Antibiotic sensitivity pattern of uropathogens among diabetic and non-diabetic pregnant women in Dhaka, Bangladesh

Objective: To determine the urinary tract infections (UTIs)-causing bacterial profile and antibiotic susceptibility pattern for the proper and complete treatment of UTIs in pregnant women with diabetes mellitus (DM). Methods: We collected 300 urine samples from diabetic and nondiabetic pregnant women at various gestational ages. After isolating and identifying uropathogens, we conducted an antibiotic sensitivity assay against fourteen commonly used antibiotics: amikacin, amoxicillin, ampicillin, azithromycin, cefixime, ceftazidime, ceftriaxone, cefuroxime, ciprofloxacin, co-trimoxazole, gentamicin, levofloxacin, netilmicin, nitrofurantoin. Results: Among the participants, 70% had DM but only 37.3% had positive uropathogen growth. Five gram-negative bacteria (Escherichia coli, Klebsiella spp., Enterobacter spp., Citrobacter spp., and Pseudomonas spp.) and 3 gram-positive bacteria (Streptococcus spp., Staphylococcus spp. and Enterococcus spp.) were indentified. Escherichia coli was the most prevalent bacteria (57.1%), followed by Klebsiella spp. (19.6%). In the antibiotic susceptibility assay, we found 96.5% of the isolated organisms were highly susceptible to levofloxacin, 94.2% to netilmicin, 88.2% to nitrofurantoin, 85.1% to amikacin, 79.8% to gentamicin, respectively. On the other hand, 64.8%, 63.6%, 61.8% of the isolates demonstrated high-level resistance to ampicillin, ceftazidime and amoxicillin whereas 38.0%, 37.1%, 33.6%, 30.9% and 30.0% of the organisms were resistant to co-trimoxazole, azithromycin, ciprofloxacin, cefuroxime, cefixime, respectivey. Conclusions: Our results suggest that amikacin, levofloxacin, netilmicin, nitrofurantoin, and gentamycin can be used as first-line treatments for UTIs, whether the patient has DM or not. Contrarily, amoxicillin, ampicillin, ceftazidime, azithromycin, and co-trimoxazole should be avoided in treating UTIs.

Comparison of the Effects of General Anesthesia & Spinal Anesthesia for Elective Cesarean Section in Diabetic Pregnant Women

Introduction: Caesarean section (CS) is now one of the most commonly performed major operations in pregnant women throughout the world. While regional or general anaesthesia (GA) are both acceptable for caesarean delivery, use of GA has decreased dramatically in the past few decades due to a higher risk of anaesthesia-related maternal mortality. As a consequence, spinal anaesthesia (SA) is now the technique of choice for CS. It has become the preferred anesthetic technique when providing anesthesia for patients undergoing elective cesarean section as the risk of maternal and fetal complications associated with spinal anesthesia is less than with general anesthesia. Aim of the study: The aim of this study was to compare the effects of general & spinal anesthesia for elective cesarean section in diabetic pregnant women. Methods: This was a comparative observational study and was conducted in the Department of Anaesthesiology of Holy Family Red Crescent Medical College Hospital, Dhaka, Bangladesh during the period from January,2022 to December,2020.In our study we included 120 pregnant women with diabetes who were given spinal and general anesthesia during C-section surgery. Our patients were equally divided into two groups – i) Group A (Patients were given general anesthesia) & ii) Group B (Patients were given spinal anesthesia). Result: In total 120 patients from both the groups completed the study. In our study we found the mean age and BMI was 34.48± 11.79 years & 38.48± 14.89 kg/m2 respectively. Among all patients 16%, 58% & 27 % patients had Type 1, Type 2 & gestational diabetes respectively. The mean blood glucose level was significantly lower in SA (80.9 ±17.7) compared to GA (121.1± 17.4) after one hour of surgery. The mean of mother’s perioperative difference was significantly lower in SA (4.0 ± 0.19) compared to GA (9.4 ± 0.21). Conclusion: In our study, we found that general anaesthetic had a substantially higher influence on blood glucose concentrations ..

Antenatal dietary supplementation with myo-inositol for preventing gestational diabetes.

Gestational diabetes with onset or first recognition during pregnancy is an increasing problem worldwide. Myo-inositol, an isomer of inositol, is a naturally occurring sugar commonly found in cereals, corn, legumes and meat. Myo-inositol is one of the intracellular mediators of the insulin signal and correlates with insulin sensitivity in type 2 diabetes. The potential beneficial effect of improving insulin sensitivity suggests that myo-inositol may be useful for women in preventing gestational diabetes. This is an update of a review first published in 2015. To assess if antenatal dietary supplementation with myo-inositol is safe and effective, for the mother and fetus, in preventing gestational diabetes. We searched the Cochrane Pregnancy and Childbirth's Trials Register, ClinicalTrials.gov, WHO ICTRP (17 March 2022) and the reference lists of retrieved studies. We included published and unpublished randomised controlled trials (RCTs) including cluster-RCTs and conference abstracts, assessing the effects of myo-inositol for the prevention of gestational diabetes in pregnant women. We included studies that compared any dose of myo-inositol, alone or in a combination preparation, with no treatment, placebo or another intervention. Quasi-randomised and cross-over trials were not eligible. We excluded women with pre-existing type 1 or type 2 diabetes. Two review authors independently assessed studies for inclusion, assessed risk of bias and extracted the data. We checked the data for accuracy. We assessed the certainty of the evidence using the GRADE approach. We included seven RCTs (one conducted in Ireland, six conducted in Italy) reporting on 1319 women who were 10 weeks to 24 weeks pregnant at the start of the studies. The studies had relatively small sample sizes and the overall risk of bias was low. For the primary maternal outcomes, meta-analysis showed that myo-inositol may reduce the incidence of gestational diabetes (risk ratio (RR) 0.53, 95% confidence interval (CI) 0.31 to 0.90; 6 studies, 1140 women) and hypertensive disorders of pregnancy (RR 0.34, 95% CI 0.19 to 0.61; 5 studies, 1052 women). However, the certainty of the evidence was low to very low. For the primary neonatal outcomes, only one study measured the risk of a large-for-gestational-age infant and found myo-inositol was associated with both appreciable benefit and harm (RR 1.40, 95% CI 0.65 to 3.02; 1 study, 234 infants; low-certainty evidence). None of the included studies reported on the other primary neonatal outcomes (perinatal mortality, mortality or morbidity composite). For the secondary maternal outcomes, we are unclear about the effect of myo-inositol on weight gain during pregnancy (mean difference (MD) -0.25 kilogram (kg), 95% CI -1.26 to 0.75 kg; 4 studies, 831 women) and perineal trauma (RR 4.0, 95% CI 0.45 to 35.25; 1 study, 234 women) because the evidence was assessed as being very low-certainty. Further, myo-inositol may result in little to no difference in caesarean section (RR 0.91, 95% CI 0.77 to 1.07; 4 studies, 829 women; low-certainty evidence). None of the included studies reported on the other secondary maternal outcomes (postnatal depression and the development of subsequent type 2 diabetes mellitus). For the secondary neonatal outcomes, meta-analysis showed no neonatal hypoglycaemia (RR 3.07, 95% CI 0.90 to 10.52; 4 studies; 671 infants; very low-certainty evidence). However, myo-inositol may be associated with a reduction in the incidence of preterm birth (RR 0.35, 95% CI 0.17 to 0.70; 4 studies; 829 infants). There were insufficient data for a number of maternal and neonatal secondary outcomes, and no data were reported for any of the long-term childhood or adulthood outcomes, or for health service utilisation outcomes. Evidence from seven studies shows that antenatal dietary supplementation with myo-inositol during pregnancy may reduce the incidence of gestational diabetes, hypertensive disorders of pregnancy and preterm birth. Limited data suggest that supplementation with myo-inositol may not reduce the risk of a large-for-gestational-age infant. The current evidence is based on small studies that were not powered to detect differences in outcomes such as perinatal mortality and serious infant morbidity. Six of the included studies were conducted in Italy and one in Ireland, which raises concerns about the lack of generalisability to other settings. There is evidence of inconsistency among doses of myo-inositol, the timing of administration and study population. As a result, we downgraded the certainty of the evidence for many outcomes to low or very low certainty. Further studies for this promising antenatal intervention for preventing gestational diabetes are encouraged and should include pregnant women of different ethnicities and varying risk factors. Myo-inositol at different doses, frequency and timing of administration, should be compared with placebo, diet and exercise, and pharmacological interventions. Long-term follow-up should be considered and outcomes should include potential harms, including adverse effects.

Analysis and Comparison for Prediction of Diabetic among Pregnant Women using Innovative Support Vector Machine Algorithm over Random Forest Algorithm with Improved Accuracy

Aim: To achieve accuracy, sensitivity, and precision in AI (Artificial Intelligence) calculations for the prediction of diabetes among pregnant women, a Support Vector Machine and Random Forest algorithms were utilized. Materials and Methods: Research looked at diabetes in pregnant women using accessible data sets such as the Pima Indian dataset from the UCI website to assess the technique’s usefulness. Support Vector Machine (N=40) and Random Forest (N=40) are the two groups in this study, each having a sample size of 40. A pretest power of 80%, a threshold of 0.05, and a confidence interval of 95% were used to compute the sample size. Results: The accuracy, sensitivity, and precision of an algorithm are used to evaluate its performance. The Support Vector Machine has a 75% accuracy rate, whereas the Random Forest has a 74% accuracy rate. The sensitivity rate of the Support Vector Machine is 65%, whereas the sensitivity rate of the Random Forest is 68%. The Support Vector Machine has a precision rate of 80%, whereas the Random Forest has a precision rate of 76%. The accuracy rate is significantly different with p=0.466,p>0.05. Conclusion: When compared to the innovative Support Vector Machine Algorithm, the Random Forest approach predicts superior classifications in identifying the accuracy, sensitivity, and precision for accessing the rate for diabetes prediction among pregnant women.

Analysis and comparison for prediction of Diabetic Pregnant women using Innovative Principal Component Analysis algorithm over Support Vector Machine Algorithm with Improved Accuracy

Aim: The study’s aim is to analyze and compare the accuracy, sensitivity, and precision of diabetic prediction among pregnant women using the innovative Principal Component Analysis algorithm and Support Vector Analysis. Materials and Methods: This study involves two groups: Principal Component Analysis (N=20) algorithm and Support Vector Machine (N=20) with a sample size of 40 for each group. The sample size calculation uses a pre-test power of 80%, a threshold of 0.05, and a confidence interval of 95%. Results: Performance of algorithms are measured using accuracy, sensitivity, and precision. Principal Component Analysis algorithm results in mean accuracy of 79.43% significantly different with P=0.488(p>0.05), a sensitivity of 79.29% with P=0.096 (p<0.05), and a precision of 83.57%. Support Vector Machine algorithm results in mean accuracy of 77.67%, a sensitivity of 76.67%, and a precision of 83.54%. Conclusion: Principal Component Analysis algorithm performed significantly better than the Support Vector Machine algorithm for Diabetic prediction.

Hypothyroidism Among Diabetic Pregnancy and its Effect on Maternal and Fetal Outcome

Background: Diabetic Pregnant women with hypothyroidism are associated with adverse obstetric outcome with various maternal and fetal complications. The aim of this study was to evaluate hypothyroidism in diabetic pregnancy and its effect on maternal and fetal outcome. Material & Methods: This cross-sectional study was conducted in department of Obstetrics and Gynaecology, Women & Children Hospital, NHN, Uttara, Dhaka, Bangladesh, during the period from 13th February 2020 to 9th December 2021. Total 120 pregnant women with diabetes were included in this study. All patients were divided into two groups which include- Group A: 60 pregnant women with diabetes and Group B: 60 pregnant women with diabetes and hypothyroidism. Results: Mean age was 29.3 years (SD±4.9 years) in group A and 29.9 years (SD±6.1 years) in group B. Mean TSH was 2.2 μIU/ml (SD±1.7 μIU/ml) and in group A and 4.4 μIU/ml (SD±3.0 μIU/ml) in group B. Mean TSH was higher in group B than group A with statistically significantly difference (p< 0.0001). Most of the pregnant women had lower uterine cesarean section in both group A (51.7%) and in group B (68.3%) with statistically significant difference (p=0.0409) between the groups. The commonest maternal complication was fetal distress in both group A (13.3%) and in group B (16.7%). Most of the neonates had normal weight in both group A (83.3%) and group B (78.3%). Majority of the neonates had normal Apgar score in one minute in both group A (50%) and group B (58.3%). The Apgar score in 5 minutes was also normal in most of the neonates of both group A (71.7%) and group B (78.3%). The neonatal mortality rate in group B was 1.7%. The commonest fetal complication was low birth weight in both group A (16.7%) and in group B (21.7%). There was no statistically significant (>0.05) difference among both groups in neonate’s outcome. Conclusion: Fetal distress and preeclampsia are most common complication in diabetic pregnant women with hypothyroidism. For neonates, low birth weight, hypothyroidism and respiratory distress are commonly seen. There is higher death rate of neonates in diabetic pregnant women with hypothyroidism. Majority of the pregnant women needed lower uterine cesarean section for the complications.

Frequency of Diabetic and Non-diabetic patients having fetal anomalies at 3rd trimester using ultrasound

Background: Pre-gestational or gestational diabetes in pregnancy is now more common among pregnant mothers as a result of the obesity pandemic. Objective: To determine frequency of diabetic and non-diabetic patients having fetal anomalies at 3rd trimester using ultrasound. Methodology: Descriptive study was conducted at radiology department Chughtai Lab, Lahore. About 250 Diabetic and Non-Diabetic pregnant women of all age were included in this study. Consecutive sampling technique was used Data was analyzed by SSPS version 24.0. All quantitative variables were reported in mean ± S.D were presented in frequency and percentage and bar charts were presented. Results: The mean age of 250 participants was 28±5.1 with minimum age of 15 years and maximum age of 45 years. Out of 250 participants, 210(84%) had no Gestational Diabetes Mellitus and 40(16%) had Gestational Diabetes Mellitus. Out of 250 patients, 204(81.6%) had adequate Amniotic Fluid Index value, 27(10.8%) had Oligohydramnios and 19(7.6%) had Polyhydramnios. In our study 16(6.4%) diabetic patients and 26(10.4%) non-diabetic patients have anomalies. Conclusion: The study concluded that frequency of anomalies doesn’t depend on patients being diabetic or non-diabetic. As in our study diabetic patients are lesser anomalies than the non-diabetic patients.

High glucose causes developmental abnormalities in neuroepithelial cysts with actin and HK1 distribution changes.

It has been reported that the offspring of diabetic pregnant women have an increased risk for neural tube defects. Previous studies in animal models suggested that high glucose induces cell apoptosis and epigenetic changes in the developing neural tube. However, effects on other cellular aspects such as the cell shape changes were not fully investigated. Actin dynamics plays essential roles in cell shape change. Disruption on actin dynamics is known to cause neural tube defects. In the present study, we used a 3D neuroepithelial cyst model and a rosette model, both cultured from human embryonic stem cells, to study the cellular effects caused by high glucose. By using these models, we observed couple of new changes besides increased apoptosis. First, we observed that high glucose disturbed the distribution of pH3 positive cells in the neuroepithelial cysts. Secondly, we found that high glucose exposure caused a relatively smaller actin inner boundary enclosed area, which was unlikely due to osmolarity changes. We further investigated key glucose metabolic enzymes in our models and the results showed that the distribution of hexokinase1 (HK1) was affected by high glucose. We observed that hexokinase1 has an apical-basal polarized distribution and is highest next to actin at the boundaries. hexokinase1 was more diffused and distributed less polarized under high glucose condition. Together, our observations broadened the cellular effects that may be caused by high glucose in the developing neural tube, especially in the secondary neurulation process.

EFFECTS OF DEPRESSION, ANXIETY, OR LOW SELF-ESTEEM UPON GLYCEMIC VARIABILITY, IN DIABETIC PREGNANT VERSUS NON-PREGNANT PATIENTS.

We analyzed the correlation between glycemic variability and psychological problems such as depression, anxiety disorder, and low self-esteem in pregnant and non-pregnant (excluding gestational diabetes) patients with diabetes. Besides its originality, this study might contribute to better / earlier diagnosis of these psychological conditions, with a special interest in pregnant diabetic women. Better management and cost reduction of care could be a consequence. We compared diabetic pregnant and non-pregnant women from the perspective of the glycemic variability (for a period of 15 days prior inclusion in the study) and their results on the standardized questionnaires: Beck depression inventory, Hamilton anxiety scale - HRSA, Rosenberg self-esteem test. A statistically significant correlation was identified in both groups between the glycemic oscillation and depression, anxiety, and low self-esteem. Diabetic pregnant women had a higher statistical significance for the correlation between the glycemic oscillation and depression, as well as between the glycemic oscillation and anxiety than non-pregnant diabetic patients. The present data justify further research. Our results could be developed into a preliminary intervention protocol, using the daily glycemic values measurements, collected by patients.

Feasible Prediction of Diabetes in Pregnant Woman and Neonatal Mellitus in New Born Child using Machine Learning

Diabetes during pregnancy is a major source of health problems in unborn infants and their moms. Because gestational diabetes can develop to permanent diabetes, ML is an important method for predicting the likelihood of such progression based on the given features. Although the current study may predict lifelong diabetes in pregnant women, it cannot predict the likelihood of neonatal diabetes. As a result, new characteristics are required to improve the forecasting of neonatal mellitus and provide the most accurate and feasible diabetes persistence results in pregnant women. Python scripting and the application of Machine Learning methods such as SVM, KNN, and LR can assist in achieving this aim. The preprocessing ML dataset focusing on Diabetes from the Pima Indian diabetes database collected through Kaggle. In addition, two new attributes were added to the paper’s dataset. According to research, machine learning models using characteristics like SVM and decision trees may successfully predict the risk of diabetes in pregnant women. Various factors have been used to predict the beginning of this condition during pregnancy.

A Smart Architecture Leveraging Fog Computing Fusion and Ensemble Learning for Prediction of Gestational Diabetes

Gestational diabetes (GD) is a growing global concern, underscoring the need for early detection and effective management to prevent adverse health consequences. This paper presents an innovative and reliable architecture to predict gestational diabetes in pregnant women. While reducing the frequency of doctor visits by sending the necessary data via Internet of Things (IoT) technology and receiving the prediction results via a mobile application in real time. The proposed architecture is a fusion of fog computing hardware with ensemble machine learning to enable low-latency, energy-efficient solutions for data processing, and cloud computing. The GD_Fog architecture leverages fused fog computing and load balancing techniques to reduce latency, power consumption, Network bandwidth consumption, and response time, and cloud computing is used based on the concept of use on demand for more reliability while harnessing the power of group learning to improve prediction accuracy. In addition, GD_Fog can be configured for different operating modes to ensure optimal quality of service and prediction accuracy in various fog calculation scenarios, which meet different user requirements. Through extensive testing using real-world data from pregnant women, the framework shows promising results, outperforming the latest methods in accuracy and efficiency. Where the percentage of improvement in prediction accuracy was approximately 6.5% when using ensemble learning, and the improvement in energy use, amounted to approximately 87.01% when using fused fog computing instead of cloud computing. These results confirm the potential of the proposed structure as an invaluable tool for the early detection and effective management of gestational diabetes.

Prioritizing the Psychosocial Support Needs of Mothers with Gestational Diabetes: A Delphi Study.

Gestational diabetes is the most common medical complication in pregnancy, and the psychosocial health of women suffering from this condition affects their adherence to treatment and self-efficacy. However, since it is not possible to design interventions dealing with all of these needs, the aim of this study was to prioritize the psychosocial supportive needs of women with gestational diabetes. This was a modified Delphi design study involving 22 experts who were selected using purposive and snowball sampling methods. The study was conducted between April 2021 and June 2021. First, the psychosocial needs of diabetic pregnant women were extracted through a qualitative study involving interviews with multidisciplinary specialists and diabetic pregnant mothers (22 participants) and a systematic review of reputable scientific databases. Throughout the two Delphi stages, the questionnaire was classified, quantified, and analyzed. Based on the results of this study, the following are the top priorities when addressing the psychosocial needs of mothers with gestational diabetes: paying attention to and identifying the mother's worries and anxiety, husband and family support for diabetic pregnant women, the inclusion of specialized nutrition counseling services in mothers' treatment plan, timely education of mothers about diabetes and its complications, and proper nutrition for diabetic mothers. The priorities of the supportive needs obtained in this study can be used to design interventions aimed at promoting psychosocial health, reducing stress and anxiety, and improving medication adherence in women with gestational diabetes.

Prediction of pre-eclampsia in diabetic pregnant women.

Gestational or preexisting diabetes is one of the risk factors of pre-eclampsia. Both are responsible for higher maternal and fetal complications. The objective was to study clinical risk factors of pre-eclampsia and biochemical markers in early pregnancy of women with diabetes mellitus (DM)/gestational diabetes mellitus (GDM) for the development of pre-eclampsia. The study group comprised pregnant women diagnosed with GDM before the 20 wk of gestation and DM before pregnancy and the control group had age-, parity- and period of gestation-matched healthy women. Sex hormone-binding globulin (SHBG), insulin-like growth factor-I (IGF-I) and 25-hydroxy vitamin D [25(OH)D] levels and the polymorphism of these genes was evaluated at recruitment. Out of 2050 pregnant women, 316 (15.41%) women (296 had GDM and 20 DM before pregnancy) were included in the study group. Of these, 96 women (30.38%) in the study group and 44 (13.92%) controls developed pre-eclampsia. Multivariate logistic regression analysis indicated those who belonged to the upper middle and upper class of socio-economic status (SES) were likely to be at 4.50 and 6.10 times higher risk of developing pre-eclampsia. The risk of getting pre-eclampsia among those who had DM before pregnancy and pre-eclampsia in their previous pregnancy was about 2.34 and 4.56 times higher compared to those who had no such events, respectively. The serum biomarkers [SHBG, IGF-I and 25(OH)D] were not found to be useful in predicting pre-eclampsia in women with GDM. To predict risk of development of pre-eclampsia, the fitted risk model by backward elimination procedure was used to calculate a risk score for each patient. Receiver operating characteristic (ROC) curve for pre-eclampsia showed that area under the curve was 0.68 (95% confidence interval: 0.63-0.73); P<0.001. The findings of this study suggested that pregnant women with diabetes were at a higher risk for pre-eclampsia. SES, history of pre-eclampsia in previous pregnancy and pre-GDM were found to be the risk factors.

Relationship of serum adiponectin levels with lipid profile in diabetic and non-diabetic pregnant women

Relationship of serum adiponectin levels with lipid profile in diabetic and non-diabetic pregnant women

The role of folate in mitigating murine cardiac hypertrophy in offspring of diabetic dams

Maternal diabetes is associated with short- and long-term cardiac disease. Prenatal folate is often recommended for diabetic pregnant women to reduce the incidence of cardiac and neural tube defects in their offspring. However, no such recommendation exists for the progeny of offspring of diabetic mothers despite the epidemiologic observation that there is a two-fold increase in cardiovascular disease. Contrary to previous reports, our lab has shown that left ventricular hypertrophy re-emerges in early adulthood. This study aimed to determine the role of folate supplementation in mitigating cardiac hypertrophy in the offspring of diabetic mice. Maternal hyperglycemia was induced in CD-1 females (n=10) with streptozotocin (150mg/kg). Control mice (n=10) were given an equal volume of saline. After hyperglycemia was confirmed ( >250mg/dL), both groups were mated with CD-1 males. After weaning, the offspring of diabetic (ODM) and control (OCM) were fed a non-supplemented versus supplemented folate diet for five weeks. Cardiac hypertrophy was assessed with echocardiograms at eight weeks and stratified by sex. We used t-test to compare the left ventricular internal diameter and left posterior wall thickness. P-values < 0.05 were significant. At eight weeks, compared to OCM, ODM had a smaller left ventricle internal diameter and increased posterior wall thickness consistent with myocardial hypertrophy. However, after receiving folate supplementation, only male ODM had a resolution of cardiac hypertrophy at eight weeks. For females ODM fed with folate supplementation, cardiac hypertrophy persisted. Folate did not mitigate cardiac hypertrophy overall. However, it did for male offspring of diabetic dams specifically. Folate supplementation may have a role in attenuating hypertrophy in male offspring of diabetic dams. Future studies will assess cardiac hypertrophy in the offspring of mothers with diabetes and determine if there is a role in post-natal folate supplementation.

The effect of couple supportive counseling on self-efficacy in women with insulin-treated gestational diabetes: A randomized clinical trial.

Gestational diabetes is the most common medical complication and a common metabolic disorder during pregnancy. Increasing people's self-efficacy is one of the best ways to control this disease. As there is a lag of intervention in this regard, the purpose of this study was to determine the effect of couple supportive counseling on self-efficacy in women with insulin-treated gestational diabetes. In this randomized clinical trial, 64 women with gestational diabetes who referred to diabetes clinic of Mashhad Ommolbanin Hospital were divided into intervention and control groups through block randomization during 2019. Their gestational age was in 26-30 weeks. For the couples in the intervention group, three couple supportive counseling session was held. Each session lasted 1 h and was held one time per week. The instruments were diabetes self-efficacy questionnaire, fasting and 2-h postprandial checklist and Cassidy social support, which were assessed before and 4 weeks after intervention in both groups. Data was analyzed by SPSS software version 25 through Mann-Whitney and Wilcoxon test. P values of < 0.05 were reported to be significant. In the preintervention, the diabetes self-efficacy score had no significant difference in the intervention (30/6 ± 38/50) and control groups (09/8 ± 56/51) (P = 515/0). However, in the postintervention, the diabetes self-efficacy score was significantly higher in the intervention group (58/6 ± 41/71) compared to the control group (15/7 ± 31/51) (P < 001/0). Also, before the intervention, there was no significant difference between the intervention (30/2 ± 72/10) and control group (87/1 ± 63/11) (P = 137/0) regarding social support. However, after the intervention, there was a significant difference between the intervention and control groups (879/0 ± 53/13, 03/2 ± 41/11, P < 0/001 respectively). Also, data analysis showed a significant correlation between self-efficacy and social support (r = 0.451, P < 0.001), self-efficacy and fasting blood sugar (P < 0.001, r = -0.577), and 2 h post prandial (r = -0.778, P < 0.001). Couple supportive counseling leads to increased self-efficacy and social support in pregnant women with gestational diabetes. Therefore, it is recommended to use this counseling as an effective method in the management of diabetic pregnant women during their prenatal care to have a healthier pregnancy.

Reliability of Estimation of HBA1C for Diagnosing Gestational Diabetes

Gestation Diabetes mellitus is a condition that, if left untreated, can have adverse effects not only on the mother but also on the unborn child. Even though the oral glucose tolerance test (OGTT), which is the typical method of screening for gestational diabetes in pregnant women and has been widely used and recognised for a number of decades, there is still a need for a test that is both more accurate and simpler to administer in order to diagnose GDM. This is the case despite the fact that the standard method involves an OGTT Subjects and Methods: In this prospective observational study, OGTT and HbA1c were performed in 400 antenatal women between 24 and 28 weeks of gestation; the pregnant women were followed up thereafter. Repeat OGTT and HbA1c were done in women with GDM at 6 weeks postpartum. Results: Among the 400 women, 52 were diagnosed with GDM, for an incidence of 9%. The mean HbA1c level in women with GDM was 6.2 – 0.6%, whereas it was 5.4 – 0.5% in those with normoglycemia. Women with GDM had a higher incidence of pregnancy-related complications compared with normoglycemic women. An HbA1c cutoff of 5.3% had a sensitivity of 95.6% and a specificity of 51.6% for the diagnosis of GDM and would have avoided OGTT in approximately half of antenatal women, while missing 5% of the women. However, those with an abnormal HbA1c will require a confirmatory OGTT, as 50% of normoglycemic women would be misclassified as having GDM by this approach. On repeat testing postpartum, two of 52 women (4.4%) had overt diabetes mellitus, whereas five (11.1%) had impaired glucose tolerance. Conclusions: Although HbA1c cannot replace OGTT in the diagnosis of GDM, it can be used as a screening test, avoiding OGTT in approximately 50% of women, if a cutoff of 5.3% is used. The findings of all of these trials make it abundantly evident that the HbAlc test is superior than the traditional OGTT in a number of important respects. The great reproducibility of the HbAlc assay, improved instrumentation and standardisation of the HbAlc assay, less biological variability, and the fact that it is not affected by short-term changes in lifestyle are all factors that contribute to these advantages. It is possible to use it as a primary screening test for all pregnant women due to the fact that the patient does not need to prepare significantly for the test and that it takes less time. If, on the other hand, the HbAlc result is discovered to be greater than the reference range, then it is absolutely necessary to perform a confirmatory test in order to establish a diagnosis of GDM. It is anticipated that HbAlc will be able to function as a diagnostic marker in the not-too-distant future. Keywords: GDM; HbAlc.

Urinary incontinence and sexual dysfunction in type 1 diabetic pregnant women: preliminary results

Introduction: Pregnancy and diabetes mellitus can promote various musculoskeletal disorders, predisposing individuals to urinary and sexual dysfunction. Objective: To evaluate the frequency of urinary incontinence and sexual dysfunction in pregnant women with type 1 diabetes. Methods: A cross-sectional, observational, analytical study was conducted. Thirteen pregnant women with type 1 diabetes were assessed from April 2017 to February 2018 using the International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF) and the Female Sexual Function Index (FSFI). The statistical program SPSS version 20.1 was used for data analysis to determine the mean and standard deviation, central tendency and dispersion, and absolute (n) and relative (%) frequencies. The Pearson linear correlation test was used to evaluate the correlation between the ICIQ-SF and the FSFI. Results: The frequency of urinary incontinence was 38.5%, which produced a slight impact on the quality of life of pregnant women. The FSFI general score was 20.49, identifying the presence of sexual dysfunction (FSFI ≤ 26). In the group of pregnant women, 92.3% (n = 12) presented sexual dysfunction, and the satisfaction and arousal domains showed a higher frequency of problems. The ICIQ-SF and FSFI showed a moderate but not significant correlation (r = 0.534, p = 0.60). The data exhibited a normal distribution according to Levene’s test. Conclusion: The frequency of urinary incontinence in pregnant women with type 1 diabetes was low, but sexual dysfunction was present, and the satisfaction and arousal domains showed the highest frequency of problems.

Screening of Nephropathy in Pregnant Diabetic Women

Screening of Nephropathy in Pregnant Diabetic Women

Investigating the Relationship Between Serum C-Reactive Protein, Ferritin levels, and Gestational Diabetes in Pregnant Women Living in Qazvin City

Background: This study aimed to compare the serum levels of C-reactive protein (CRP) and ferritin in the first trimester of pregnancy between normal and abnormal pregnant women (complicated with gestational diabetes) to determine if these chemicals have any predictive value in the diagnosis of gestational diabetes. Methods: This prospective cohort study was carried out on 300 pregnant women attending the Prenatal Clinic of Kosar Hospital, Qazvin City, Iran, during 2017-2018. Based on Carpenter and Constant criteria, the pregnant women undertook an oral glucose tolerance test with 75 g glucose to diagnose gestational diabetes. We also measured the serum levels of CRP and ferritin in all the women in the first trimester. The obtained data were analyzed using SPSS software version 24. P&lt;0.05 was considered statistically significant Results: A total of 40 pregnant women were found to have gestational diabetes. The levels of CRP and ferritin were slightly higher in women with gestational diabetes, although this increase was not statistically significant. Regarding the receiver operating characteristic curve, body mass index (BMI) could predict the incidence of gestational diabetes (72.5% sensitivity, 53.1% specificity, P=0.023). The higher BMI and CRP levels in the first trimester were also significantly associated with macrosomia, which could predict macrosomia with 75% sensitivity, 73.6% specificity for BMI (P=0.005), and 87.5% sensitivity, 58.1% specificity for BMI. Conclusion: There was no correlation between CRP and ferritin levels and gestational diabetes in the first trimester of pregnancy. BMI before pregnancy was the only variable related to gestational diabetes. Increased values of both CRP and BMI were associated with fetal macrosomia