Real-time predictive model of extrauterine growth retardation in preterm infants with gestational age less than 32 weeks.

The aim of this study was to develop a real-time risk prediction model for extrauterine growth retardation (EUGR). A total of 2514 very preterm infants were allocated into a training set and an external validation set. The most appropriate independent variables were screened using univariate analysis and Lasso regression with tenfold cross-validation, while the prediction model was designed using binary multivariate logistic regression. A visualization of the risk variables was created using a nomogram, while the calibration plot and receiver operating characteristic (ROC) curves were used to calibrate the prediction model. Clinical efficacy was assessed using the decision curve analysis (DCA) curves. Eight optimal predictors that namely birth weight, small for gestation age (SGA), hypertensive disease complicating pregnancy (HDCP), gestational diabetes mellitus (GDM), multiple births, cumulative duration of fasting, growth velocity and postnatal corticosteroids were introduced into the logistic regression equation to construct the EUGR prediction model. The area under the ROC curve of the training set and the external verification set was 83.1% and 84.6%, respectively. The calibration curve indicate that the model fits well. The DCA curve shows that the risk threshold for clinical application is 0-95% in both set. Introducing Birth weight, SGA, HDCP, GDM, Multiple births, Cumulative duration of fasting, Growth velocity and Postnatal corticosteroids into the nomogram increased its usefulness for predicting EUGR risk in very preterm infants.

Fetal abdominal obesity in women with one value abnormality on diagnostic test for gestational diabetes mellitus.

Previous studies have shown that fetal abdominal obesity (FAO) was already observed at the time of gestational diabetes mellitus (GDM) diagnosis and persisted until delivery despite management in older and/or obese women. In this study, we investigated whether fetuses of women with milder hyperglycemia than GDM have accelerated abdominal growth, leading to adverse pregnancy outcomes. We retrospectively reviewed the medical records of 7,569 singleton pregnant women who were universally screened using a 50-g glucose challenge test (GCT) and underwent a 3-h 100-g oral glucose tolerance test (OGTT) if GCT result was ≥140mg/dL. GDM, one value abnormality (OVA), and normal glucose tolerance (NGT, NGT1: GCT negative, NGT2: GCT positive & OGTT negative) were diagnosed using Carpenter-Coustan criteria. With fetal biometry data measured simultaneously with 50-g GCT, relative fetal abdominal overgrowth was investigated by assessing the fetal abdominal overgrowth ratios (FAORs) of the ultrasonographically estimated gestational age (GA) of abdominal circumference(AC) per actual GA by the last menstruation period(LMP), biparietal diameter(BPD) or femur length(FL), respectively. FAO was defined as FAOR ≥90th percentile The FAORs of GA-AC/GA-LMP and GA-AC/GA-BPD were significantly higher in OVA subjects compared to NGT subjects but not in NGT2 subjects. Although the frequency of FAO in OVA (12.1%) was between that of NGT (9.6%) and GDM (18.3%) without statistically significant difference, the prevalence of large for gestational age at birth and primary cesarean delivery rates were significantly higher in OVA (9.8% and 29.7%) than in NGT (5.1% and 21.5%, p<0.05). Particularly, among OVA subjects with FAO, the prevalence (33.3% and 66.7%) was significantly higher than in those without FAO (9.7% and 24.2%, p<0.05). The degree of fetal abdominal growth acceleration in OVA subjects was intermediate between that of NGT and GDM subjects. OVA subjects with FAO at the time of GDM diagnosis were strongly associated with adverse pregnancy outcomes.

A first trimester prediction model and nomogram for gestational diabetes mellitus based on maternal clinical risk factors in a resource-poor setting.

BACKGROUND: The implementation of universal screening for Gestational Diabetes Mellitus (GDM) is challenged by several factors key amongst which is limited resources, hence the continued reliance on risk factor-based screening. Effective identification of high-risk women early in pregnancy may enable preventive intervention. This study aimed at developing a GDM prediction model based on maternal clinical risk factors that are easily assessable in the first trimester of pregnancy in a population of Nigerian women. METHODS: This was a multi-hospital prospective observational cohort study of 253 consecutively selected pregnant women from which maternal clinical data was collected at 8-12 weeks gestational age. Diagnosis of GDM was made via a one-step 75-gram Oral Glucose Tolerance Test (OGTT) at 24-28 weeks of gestation. A GDM prediction model and nomogram based on selected maternal clinical risk factors was developed using multiple logistic regression analysis, and its performance was assessed by Receiver Operator Curve (ROC) analysis. Data analysis was carried out using Statistical Package for Social Sciences (SPSS) version 25 and Python programming language (version 3.0). RESULTS: Increasing maternal age, higher body mass index (BMI), a family history of diabetes mellitus in first-degree relative and previous history of foetal macrosomia were the major predictors of GDM. The model equation was: LogitP = 6.358 - 0.066 × Age - 0.075 × First trimester BMI - 1.879 × First-degree relative with diabetes mellitus - 0.522 × History of foetal macrosomia. It had an area under the receiver operator characteristic (ROC) curve (AUC) of 0.814 (95% CI: 0.751-0.877; p-value < 0.001), and at a predicted probability threshold of 0.745, it had a sensitivity of 79.2% and specificity of 74.5%. CONCLUSION: This first trimester prediction model reliably identifies women at high risk for GDM development in the first trimester, and the nomogram enhances its practical applicability, contributing to improved clinical outcomes in the study population.

Psychometric evaluation of a novel tool for assessing gestational diabetes and hypertension care: knowledge, attitudes, and practices of midwives and nurses.

While standardized assessment of knowledge, attitudes, and practices (KAP) related to gestational diabetes and hypertension is possible with a valid tool, existing research remains limited. This prospective validation study aimed to develop and validate a novel tool to assess the KAP of midwives and obstetric nurses. We included 125 midwives and obstetric nurses who routinely care for patients with gestational diabetes and hypertension. The tool demonstrated good internal consistency (Cronbach's alpha): knowledge (0.729, 95% CI, 0.654-0.776), attitude (0.756, 95% CI, 0.690-0.814), and practices (0.925, 95% CI, 0.905-0.943). Difficulty indices (d) ranged from 0.38 to 0.99 (knowledge), 0.41 to 0.99 (attitudes), and 0.41 to 0.93 (practices), indicating appropriate item difficulty. Discrimination indices (D) confirmed items could differentiate between respondents with low and high knowledge levels (D range: 0.02-0.77 for knowledge, 0.06-0.64 for attitudes, 0.20-0.84 for practices). The robust psychometric properties of this tool support its use in future research on KAP related to diabetes and gestational hypertension management in midwives and nurses. This instrument has the potential to be valuable in various settings, including baseline assessment before educational programs or evaluation of learning outcomes after interventions.

Maternal Neudesin Levels in Pregnant Women with Gestational Diabetes Mellitus.

BACKGROUND: Our aim was to investigate the changes in neudesin levels in pregnant women with GDM and the relationship between neudesin and metabolic parameters. METHODS: Forty pregnant women diagnosed with GDM and forty age- and gestational week-matched control subjects were included in the study. Demographic data were obtained from records. Maternal lipid profiles, glucose levels, fasting insulin, HbA1C, and HOMA-IR results were compared between the groups. Correlation tests were performed to evaluate the relationship between neudesin and clinical and laboratory diagnostic parameters. p < 0.05 were interpreted as statistically significant. RESULTS: The human serum neudesin levels were significantly lower in the GDM group compared with the controls. The correlation tests showed statistically negative and weak correlations between the neudesin levels and the maternal age, 50 g OGCT, 100 g OGTT 3 hours, and HbA1C. The optimum neudesin cutoff value for a diagnosis of GDM disease is 6.94 ng/dL, with a sensitivity of 65.9% and a specificity of 63.2%. CONCLUSIONS: This study has shown that lower neudesin levels may occur as a reflection of changes in glucose metabolism during intrauterine life.

Glucose levels measured with continuous glucose monitoring in uncomplicated pregnancies.

INTRODUCTION: To characterize glucose levels during uncomplicated pregnancies, defined as pregnancy with a hemoglobin A1c <5.7% (<39 mmol/mol) in early pregnancy, and without a large-for-gestational-age birth, hypertensive disorders of pregnancy, or gestational diabetes mellitus (ie, abnormal oral glucose tolerance test). RESEARCH DESIGN AND METHODS: Two sites enrolled 937 pregnant individuals aged 18 years and older prior to reaching 17 gestational weeks; 413 had an uncomplicated pregnancy (mean±SD body mass index (BMI) of 25.3±5.0 kg/m2) and wore Dexcom G6 continuous glucose monitoring (CGM) devices throughout the observed gestational period. Mealtimes were voluntarily recorded. Glycemic levels during gestation were characterized using CGM-measured glycemic metrics. RESULTS: Participants wore CGM for a median of 123 days each. Glucose levels were nearly stable throughout all three trimesters in uncomplicated pregnancies. Overall mean±SD glucose during gestation was 98±7 mg/dL (5.4±0.4 mmol/L), median per cent time 63-120 mg/dL (3.5-6.7 mmol/L) was 86% (IQR: 82-89%), median per cent time <63 mg/dL (3.5 mmol/L) was 1.8%, median per cent time >120 mg/dL (6.7 mmol/L) was 11%, and median per cent time >140 mg/dL (7.8 mmol/L) was 2.5%. Mean post-prandial peak glucose was 126±22 mg/dL (7.0±1.2 mmol/L), and mean post-prandial glycemic excursion was 36±22 mg/dL (2.0±1.2 mmol/L). Higher mean glucose levels were low to moderately associated with pregnant individuals with higher BMIs (103±6 mg/dL (5.7±0.3 mmol/L) for BMI ≥30.0 kg/m2 vs 96±7 mg/dL (5.3±0.4 mmol/L) for BMI 18.5-<25 kg/m2, r=0.35). CONCLUSIONS: Mean glucose levels and time 63-120 mg/dL (3.5-6.7 mmol/L) remained nearly stable throughout pregnancy and values above 140 mg/dL (7.8 mmol/L) were rare. Mean glucose levels in pregnancy trend higher as BMI increases into the overweight/obesity range. The glycemic metrics reported during uncomplicated pregnancies represent treatment targets for pregnant individuals.

Early Gestational Diabetes Mellitus: An Update.

Erythroderma is a dermatological emergency presenting with generalized erythema and scaling involving >90% of the body surface.1 There are various causes of erythroderma, such as psoriasis, atopic dermatitis, phytophotodermatitis, pityriasis rubra pilaris, pemphigus foliaceus, cutaneous T-cell lymphoma, and drug eruptions.2 However, erythroderma induced by dermatophytosis is encountered rarely. We, here, describe a case of erythroderma developed secondary to extensive dermatophytosis.

Antenatal oral glucose tolerance test abnormalities in the prediction of future risk of postpartum diabetes in women with gestational diabetes: Results from the LIVING study.

OBJECTIVES: To explore associations between type and number of abnormal glucose values on antenatal oral glucose tolerance test (OGTT) with postpartum diabetes in South Asian women diagnosed with gestational diabetes (GDM) using International Association of the Diabetes and Pregnancy Study Groups criteria. METHODS: This post-hoc evaluation of the Lifestyle Intervention IN Gestational Diabetes (LIVING) study, a randomized controlled trial, was conducted among women with GDM in the index pregnancy, across 19 centers in Bangladesh, India, and Sri Lanka. Postpartum diabetes (outcome) was defined on OGTT, using American Diabetes Association (ADA) criteria. RESULTS: We report data on 1468 women with GDM, aged 30.9 (5.0) years, and with median (interquartile range) follow-up period of 1.8 (1.4-2.4) years after childbirth following the index pregnancy. We found diabetes in 213 (14.5%) women with an incidence of 8.7 (7.6-10.0)/100 women-years. The lowest incidence rate was 3.8/100 women years, in those with an isolated fasting plasma glucose (FPG) abnormality, and highest was 19.0/100 women years in participants with three abnormal values. The adjusted hazard ratios for two and three abnormal values compared to one abnormal value were 1.73 (95% confidence interval [CI], 1.18-2.54; p = .005) and 3.56 (95% CI, 2.46-5.16; p < .001) respectively. The adjusted hazard ratio for the combined (combination of fasting and postglucose load) abnormalities was 2.61 (95% CI, 1.70-4.00; p < .001), compared to isolated abnormal FPG. CONCLUSIONS: Risk of diabetes varied significantly depending upon the type and number of abnormal values on antenatal OGTT. These data may inform future precision medicine approaches such as risk prediction models in identifying women at higher risk and may guide future targeted interventions.

Review of Genetic and Artificial Intelligence approaches to improving Gestational Diabetes Mellitus Screening and Diagnosis in sub-Saharan Africa.

Background: Adverse outcomes from gestational diabetes mellitus (GDM) in the mother and newborn are well established. Genetic variants may predict GDM and Artificial Intelligence (AI) can potentially assist with improved screening and early identification in lower resource settings. There is limited information on genetic variants associated with GDM in sub-Saharan Africa and the implementation of AI in GDM screening in sub-Saharan Africa is largely unknown. Methods: We reviewed the literature on what is known about genetic predictors of GDM in sub-Saharan African women. We searched PubMed and Google Scholar for single nucleotide polymorphisms (SNPs) involved in GDM predisposition in a sub-Saharan African population. We report on barriers that limit the implementation of AI that could assist with GDM screening and offer possible solutions. Results: In a Black South African cohort, the minor allele of the SNP rs4581569 existing in the PDX1 gene was significantly associated with GDM. We were not able to find any published literature on the implementation of AI to identify women at risk of GDM before second trimester of pregnancy in sub-Saharan Africa. Barriers to successful integration of AI into healthcare systems are broad but solutions exist. Conclusions: More research is needed to identify SNPs associated with GDM in sub-Saharan Africa. The implementation of AI and its applications in the field of healthcare in the sub-Saharan African region is a significant opportunity to positively impact early identification of GDM.

Effect of Prenatal Care on Perinatal Outcomes of Pregnant Women with Diabetes Mellitus: A Systematic Review.

Objective: to evaluate the effect of prenatal care (PC) on perinatal outcomes of pregnant women with diabetes mellitus (DM). Methods: systematic review developed according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines and conducted through the population, intervention, control, and outcomes (PICO) strategy. Clinical trials and observational studies were selected, with adult pregnant women, single-fetus pregnancy, diagnosis of DM, or gestational DM and who had received PC and/or nutritional therapy (NT). The search was carried out in PubMed, Scopus, and BIREME databases. The quality of the studies was evaluated using the tools of the National Heart, Lung and Blood Institute-National Institutes of Health (NHLBI-NIH). Results: We identified 5972 records, of which 15 (n=47 420 pregnant women) met the eligibility criteria. The most recurrent outcomes were glycemic control (14 studies; n=9096 participants), hypertensive disorders of pregnancy (2; n=39 282), prematurity (6; n=40 163), large for gestational age newborns (4; n=1556), fetal macrosomia (birth weight >4kg) (6; n=2980) and intensive care unit admission (4; n=2022). Conclusions: The findings suggest that PC interferes with the perinatal outcome, being able to reduce the risks of complications associated with this comorbidity through early intervention, especially when the NT is an integral part of this assistance.

Early prediction of gestational diabetes mellitus using maternal demographic and clinical risk factors.

OBJECTIVE: To build and validate an early risk prediction model for gestational diabetes mellitus (GDM) based on first-trimester electronic medical records including maternal demographic and clinical risk factors. METHODS: To develop and validate a GDM prediction model, two datasets were used in this retrospective study. One included data of 14,015 pregnant women from Máxima Medical Center (MMC) in the Netherlands. The other was from an open-source database nuMoM2b including data of 10,038 nulliparous pregnant women, collected in the USA. Widely used maternal demographic and clinical risk factors were considered for modeling. A GDM prediction model based on elastic net logistic regression was trained from a subset of the MMC data. Internal validation was performed on the remaining MMC data to evaluate the model performance. For external validation, the prediction model was tested on an external test set from the nuMoM2b dataset. RESULTS: An area under the receiver-operating-characteristic curve (AUC) of 0.81 was achieved for early prediction of GDM on the MMC test data, comparable to the performance reported in previous studies. While the performance markedly decreased to an AUC of 0.69 when testing the MMC-based model on the external nuMoM2b test data, close to the performance trained and tested on the nuMoM2b dataset only (AUC = 0.70).

Prevalence and Predictors of Gestational Diabetes Mellitus in Sub-Saharan Africa: A 10-Year Systematic Review.

BACKGROUND: Gestational diabetes mellitus (GDM) remains a global public health problem, which affects the well-being of mothers and their children in sub-Saharan Africa (SSA). Studies conducted in different geographical areas provide varied results on its prevalence and predictors. Understanding the extent and predictors of GDM in SSA is important for developing effective interventions and policies. Thus, this review aimed to investigate the prevalence of GDM and its predictive factors in sub-Saharan Africa. METHODS: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards in this review. An extensive search of the PubMed, Web of Sciences and EMBASE databases was carried out covering papers from 2012 to 2022 to assess the prevalence and predictors of GDM. Microsoft Excel 2019 was utilised for study management. GraphPad Prism Version 8.0 and the MedCalc statistical software were employed for data analysis. The findings were analysed using textual descriptions, tables, forest plots and heat maps. RESULTS: Using 30 studies with 23,760 participants that satisfied the inclusion criteria, the review found the overall prevalence of GDM in SSA to be 3.05% (1.85%-4.54%). History of preterm delivery, alcohol consumption, family history of diabetes, history of stillbirths, history of macrosomia, overweight or obesity and advanced mother age were all significant predictors of gestational diabetes. Additionally, various biomarkers such as haemoglobin, adiponectin, leptin, resistin, visfatin, vitamin D, triglycerides and dietary intake type were identified as significant predictors of GDM. CONCLUSION: In sub-Saharan Africa, there is a high pooled prevalence of gestational diabetes mellitus. In the light of the predictors of GDM identified in this review, it is strongly recommended to implement early screening for women at risk of developing gestational diabetes during their pregnancy. This proactive approach is essential for enhancing the overall well-being of both mothers and children.

Increased risk of cardiovascular and renal disease, and diabetes for all women diagnosed with gestational diabetes mellitus in New Zealand-A national retrospective cohort study.

BACKGROUND: Gestational diabetes mellitus increases the risk of developing type 2 diabetes. The aim of this study is to compare cardiometabolic and renal outcomes for all women in New Zealand with gestational diabetes (2001-2010) with women without diabetes, 10-20 years following delivery. METHODS: A retrospective cohort study, utilizing a national dataset providing information for all women who gave birth between 1 January 2001 and 31 December 2010 (n = 604 398). Adolescent girls <15 years, women ≥50 years and women with prepregnancy diabetes were excluded. In total 11 459 women were diagnosed with gestational diabetes and 11 447 were matched (for age and year of delivery) with 57 235 unexposed (control) women. A national hospital dataset was used to compare primary outcomes until 31 May 2021. RESULTS: After controlling for ethnicity, women with gestational diabetes were significantly more likely than control women to develop diabetes-adjusted hazard ratio (HR) 20.06 and 95% confidence interval (CI) 18.46-21.79; a first cardiovascular event 2.19 (1.86-2.58); renal disease 6.34 (5.35-7.51) and all-cause mortality 1.55 (1.31-1.83), all p values <.0001. The HR and 95% CI remained similar after controlling for significant covariates: diabetes 18.89 (17.36-20.56), cardiovascular events 1.79 (1.52-2.12), renal disease 5.42 (4.55-6.45), and all-cause mortality 1.44 (1.21-1.70). When time-dependent diabetes was added to the model, significance remained for cardiovascular events 1.33 (1.10-1.61), p = .003 and renal disease 2.33 (1.88-2.88), p < .0001 but not all-cause mortality. CONCLUSIONS: Women diagnosed with gestational diabetes have an increased risk of adverse cardiometabolic and renal outcomes. Findings highlight the importance of follow-up screening for diabetes, cardiovascular risk factors, and renal disease.

Efficacy of a phone reminder to improve adherence to post-partum glucose tolerance testing after gestational diabetes and clinical predictors of post-partum follow-up compliance.

AIM: To assess the effectiveness of a phone reminder to improve adherence to post-partum glucose tolerance testing in women with gestational diabetes mellitus (GDM) and to identify clinical predictors of adherence to post-partum follow-up. METHODS: Retrospective study including 543 women with GDM. We assessed the adherence rate to post-partum glucose tolerance testing in women who received a phone reminder (n = 297) compared to women not alerted (n = 246). Demographic and clinical variables were collected to identify the predictors of adherence to the post-partum oral glucose tolerance test (OGTT). RESULTS: The adherence to post-partum OGTT was higher in women who received the phone reminder compared to those not alerted (60.6 % vs. 35.4 %, p < 0.001). Women less compliant compared to those more compliant, had a higher pre-pregnancy body mass index (BMI) (29.3 ± 7.9 vs. 27.0 ± 6.1 Kg/m2, p = 0.03). The adherence was lower in pre-pregnant obese compared to non-obese women (42.7 % vs. 52.0 %, p < 0.05), in women with only one, compared to multiple OGTT alterations during pregnancy (44.5 % vs. 57.8 %, p < 0.05), and in women non-insulin treated compared to those insulin-treated (40.0 % vs. 57.1 % vs, p < 0.001). CONCLUSIONS: The phone reminder improved post-partum follow-up adherence. Pre-pregnancy BMI, number of OGTT alterations and type of therapy could identify poorly adherent women.

The application of plasma circRAD18 in the prediction of gestational diabetes mellitus (GDM) and its adverse effects.

BACKGROUND: In cancer biology, circRAD18 promotes glucose metabolism, potentially indicating its involvement in glucose metabolism-related disorders, such as gestational diabetes mellitus (GDM). The present study investigated the predictive role of circRAD18 in GDM and its potential adverse effects. METHODS: A total of 482 women who intended to get pregnant in short-term were enrolled. For those who successfully conceived, plasma samples were collected and followed up until delivery to monitor the occurrence of GDM and its associated adverse events. The accumulation of circRAD18 in plasma was analyzed using RT-qPCR. GDM-free curves and ROC curves were plotted to assess the predictive value of plasma circRAD18 for GDM. RESULTS: After admitting 482 female patients, 388 of them achieved pregnancy within half a year. During the follow-up period, 52 cases were diagnosed with GDM. Compared to non-GDM group (n = 336), the GDM group (n = 52) had a lower accumulation level of circRAD18 on the day of pregnancy confirmation. In addition, low levels of circRAD18 accumulation on that day distinguished potential GDM patients from non-GDM cases. The 388 cases were divided into high and low circRAD18 level groups (n = 194). GDM-free curve analysis showed that patients in the low circRAD18 level group had a higher incidence of GDM compared to the high level group (43/194 vs. 9/194). A close association was found between low levels of plasma circRAD18 and hypertension, but not premature delivery, intrauterine death, malformation, intrauterine infection, miscarriage, macrosomia or intrauterine distress. CONCLUSION: The reduction in the accumulation of plasma circRAD18 is predictive of GDM and hypertension in pregnant women.

Importance of Prenatal Diagnosis of Ileal Atresia in Gestational Diabetes Cases.

BACKGROUND Maldevelopment of the fetal bowel can result in the rare condition of intestinal atresia, which results in congenital bowel obstruction. This report describes a case of prenatal diagnosis of fetal ileal atresia at 22 weeks' gestation. CASE REPORT Here, we present a 24-year old woman who was 22 weeks into her first pregnancy when she underwent routine fetal ultrasound. She was diagnosed with gestational diabetes mellitus. Her body mass index was normal and she had normal weight gain. The ultrasonographic examination performed revealed a hyperechoic bowel and a small dilatation of the bowel. The couple was counselled for possible intestinal atresia and its postnatal implications. At 33 weeks of gestation, polyhydramnios appeared, and the intestinal distension was much more pronounced, with hyperechoic debris in the intestinal lumen (succus-entericus). After birth, surgery was performed and we concluded the patient had type II atresia, which was surgically treated. CONCLUSIONS This report has highlighted the importance of antenatal ultrasound in detecting fetal abnormalities, and has shown that rare conditions such as intestinal atresia can be accurately diagnosed and successfully managed. Surgical correction, if implemented promptly after stabilizing the general condition, can have a relatively good prognosis. Coexisting fetal ileal atresia and gestational diabetes mellitus are rare occurrences, which can make each condition even more difficult to treat.

Do WHO criteria for gestational diabetes fit a rural population in Tanzania? - A follow-up study assessing mother and child health six years after a pregnancy diagnosed with gestational diabetes.

AIMS AND METHODS: In low- and middle- income countries (LMICs) consequences of gestational diabetes (GDM) is understudied. Using a prospective cohort of mothers (n = 197)and children (n = 251), from rural north-eastern Tanzania, we assessed prediabetes and type 2 diabetes (T2D) prevalence six years after a pregnancy with/without GDM. RESULTS: The prevalence of prediabetes (49.4 % vs. 46.4 %) orT2D (20.0 % vs. 16.1 %), p ≥ 0.36, based on fasting plasma glucose (FPG) or HbA1clevels (prediabetes: 16.9 % vs. 13.8 % and T2D 1.2 % vs. 0 %, p = 0.47), andcardio-metabolic health parameters,weresimilar between women with/without previous GDM. These results were supported by similar perinatal outcomes and child health at follow-up.The overall prevalence ofprediabetes/T2D was high, but no differences in other cardio-metabolic risk markers were observed in women with prediabetes/T2D compared to women with normal glucose tolerance. CONCLUSIONS: Despite high prevalence of GDM amongTanzanian women, the diagnosis was not associated with adverse pregnancy outcomes, nor with increased risk of prediabetes or T2D at follow-up. FPG and HbA1c may be poor markers for diabetes in this population, and further follow-up studies with longer time intervals are warranted to evaluate which GDM diagnostic criteria are most optimal for women in rural Tanzania and similar LMIC settings.

One abnormal value in oral glucose tolerance test during pregnancy and type 2 diabetes risk: Insights from a 5-Year Follow-Up study.

OBJECTIVES: To evaluate the risk of type 2 diabetes(T2D) following one abnormal value(OAbV) in an oral glucose tolerance test(oGTT) performed during pregnancy. STUDY DESIGN: A retrospective analysis of parturients between 01.01.2017 and 31.12.2020 with 5 years of follow-up after delivery. Glucose levels during pregnancy were extracted from the computerized laboratory system of Meuhedet HMO and cross-tabulated with the Israeli National Registry of Diabetes. Women with multiple gestations or pregestational diabetes were excluded. Maternal characteristics and risk of T2D were stratified and compared between 3 groups: normal glucose status, OAbV in oGTT, and gestational diabetes. Statistical analysis included univariate analysis followed by survival analysis. Further analysis was stratified to women with and without obesity. RESULTS: 58,693 women entered the analysis. Following an adjustment to maternal age, obesity, hypertension, and hyperlipidemia, OAbV in oGTT was associated with a 1.8-fold increased risk of T2D in a 5-year follow-up compared to normal glucose status. When stratified by obesity, OAbV was associated with a 3.7-fold increase in T2D in women without obesity, however, was no longer a statistically significant predictor of T2D among women with obesity. CONCLUSIONS: Women with OAbV oGTT during pregnancy are at increased risk for developing T2D over 5 years of follow-up.

Establishment of pregnancy-specific lipid reference intervals in pregnant women in a single-centre and assessment of the predictive value of early lipids for gestational diabetes mellitus: a prospective cohort study.

INTRODUCTION: This study was aimed at establishing a pregnancy-specific lipid reference interval (RI) in pregnant women in a single-centre in the Beijing area of China, simultaneously exploring the predictive value of lipid levels in early pregnancy for gestational diabetes mellitus (GDM). MATERIAL AND METHODS: From October 2017 to August 2019, Peking University International Hospital established records for 1588 pregnant women, whose lipid profiles were determined during the first and third trimesters. The Hoffmann technique was used to calculate gestation-specific lipid RI. The 95% reference range for gestational lipids was also estimated for 509 healthy pregnant women screened according to the Clinical and Laboratory Standards Institute guideline. Multivariate logistic regression analysis was used to calculate odds ratios (OR) and their 95% confidence interval (CI), and the receiver operating characteristic (ROC) curve was applied to assess the predictive value of lipids in the first trimester for the diagnosis of GDM. RESULTS: Total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels were significantly higher in the third trimester (p < 0.05). Hoffmann technique RI of the lipid profiles and the 95% reference range of the lipid profiles in healthy pregnant women did not differ statistically (p > 0.05). TC, TG, and LDL-C levels were higher in the GDM group in the first trimester (p < 0.05), and the risk of GDM was 2.1 times higher in women with higher TG (95% CI: 1.13-3.77, p < 0.05). The optimal ROC cut-off for TG to predict GDM was 2.375 mmol / L, and the area under the ROC curve was 0.622 (95% CI: 0.592-0.751), with a sensitivity of 73.7% and a specificity of 59.3%. CONCLUSIONS: This study established pregnancy-specific lipid RI for pregnant women in a single centre in the Beijing area of China. Pregnant women with TG ≥ 2.375 mmol/L in the first trimester were at significantly increased risk for GDM.