Changing diagnostic criteria for gestational diabetes (CDC4G) in Sweden: A stepped wedge cluster randomised trial.

BACKGROUND: The World Health Organisation (WHO) 2013 diagnostic criteria for gestational diabetes mellitus (GDM) has been criticised due to the limited evidence of benefits on pregnancy outcomes in different populations when switching from previously higher glycemic thresholds to the lower WHO-2013 diagnostic criteria. The aim of this study was to determine whether the switch from previous Swedish (SWE-GDM) to the WHO-2013 GDM criteria in Sweden following risk factor-based screening improves pregnancy outcomes. METHODS AND FINDINGS: A stepped wedge cluster randomised trial was performed between January 1 and December 31, 2018 in 11 clusters (17 delivery units) across Sweden, including all pregnancies under care and excluding preexisting diabetes, gastric bypass surgery, or multifetal pregnancies from the analysis. After implementation of uniform clinical and laboratory guidelines, a number of clusters were randomised to intervention (switch to WHO-2013 GDM criteria) each month from February to November 2018. The primary outcome was large for gestational age (LGA, defined as birth weight >90th percentile). Other secondary and prespecified outcomes included maternal and neonatal birth complications. Primary analysis was by modified intention to treat (mITT), excluding 3 clusters that were randomised before study start but were unable to implement the intervention. Prespecified subgroup analysis was undertaken among those discordant for the definition of GDM. Multilevel mixed regression models were used to compare outcome LGA between WHO-2013 and SWE-GDM groups adjusted for clusters, time periods, and potential confounders. Multiple imputation was used for missing potential confounding variables. In the mITT analysis, 47 080 pregnancies were included with 6 882 (14.6%) oral glucose tolerance tests (OGTTs) performed. The GDM prevalence increased from 595/22 797 (2.6%) to 1 591/24 283 (6.6%) after the intervention. In the mITT population, the switch was associated with no change in primary outcome LGA (2 790/24 209 (11.5%) versus 2 584/22 707 (11.4%)) producing an adjusted risk ratio (aRR) of 0.97 (95% confidence interval 0.91 to 1.02, p = 0.26). In the subgroup, the prevalence of LGA was 273/956 (28.8%) before and 278/1 239 (22.5%) after the switch, aRR 0.87 (95% CI 0.75 to 1.01, p = 0.076). No serious events were reported. Potential limitations of this trial are mainly due to the trial design, including failure to adhere to guidelines within and between the clusters and influences of unidentified temporal variations. CONCLUSIONS: In this study, implementing the WHO-2013 criteria in Sweden with risk factor-based screening did not significantly reduce LGA prevalence defined as birth weight >90th percentile, in the total population, or in the subgroup discordant for the definition of GDM. Future studies are needed to evaluate the effects of treating different glucose thresholds during pregnancy in different populations, with different screening strategies and clinical management guidelines, to optimise women's and children's health in the short and long term. TRIAL REGISTRATION: The trial is registered with ISRCTN (41918550).

Multivariable prediction models for fetal macrosomia and large for gestational age: A systematic review.

BACKGROUND: The identification of large for gestational age (LGA) and macrosomic fetuses is essential for counselling and managing these pregnancies. OBJECTIVES: To systematically review the literature for multivariable prediction models for LGA and macrosomia, assessing the performance, quality and applicability of the included model in clinical practice. SEARCH STRATEGY: MEDLINE, EMBASE and Cochrane Library were searched until June 2022. SELECTION CRITERIA: We included observational and experimental studies reporting the development and/or validation of any multivariable prediction model for fetal macrosomia and/or LGA. We excluded studies that used a single variable or did not evaluate model performance. DATA COLLECTION AND ANALYSIS: Data were extracted using the Checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies checklist. The model performance measures discrimination, calibration and validation were extracted. The quality and completion of reporting within each study was assessed by its adherence to the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) checklist. The risk of bias and applicability were measured using PROBAST (Prediction model Risk Of Bias Assessment Tool). MAIN RESULTS: A total of 8442 citations were identified, with 58 included in the analysis: 32/58 (55.2%) developed, 21/58 (36.2%) developed and internally validated and 2/58 (3.4%) developed and externally validated a model. Only three studies externally validated pre-existing models. Macrosomia and LGA were differentially defined by many studies. In total, 111 multivariable prediction models were developed using 112 different variables. Model discrimination was wide ranging area under the receiver operating characteristics curve (AUROC 0.56-0.96) and few studies reported calibration (11/58, 19.0%). Only 5/58 (8.6%) studies had a low risk of bias. CONCLUSIONS: There are currently no multivariable prediction models for macrosomia/LGA that are ready for clinical implementation.

Ultrasound prediction of fetal macrosomia in pregnancies complicated by diabetes mellitus: a systematic review and meta-analysis.

OBJECTIVES: To report the diagnostic accuracy of ultrasound in identifying fetuses with macrosomia in pregnancies complicated by gestational or pregestational diabetes. METHODS: Medline, Embase and Cochrane databases were searched. Inclusion criteria were singleton pregnancies complicated by diabetes undergoing third-trimester ultrasound evaluation. The index test was represented by ultrasound estimation of fetal macrosomia (estimated fetal weight EFW or abdominal circumference AC >90th or 95th percentile). Subgroup analyses were also performed. Sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio were computed using the hierarchical summary receiver-operating characteristics model. RESULTS: Twenty studies were included in the systematic review including 8,530 pregnancies complicated by diabetes. Ultrasound showed an overall moderate accuracy in identifying fetuses with macrosomia with a sensitivity of 71.2 % (95 % CI 63.1-78.2), a specificity of 88.6 % (95 % CI 83.9-92.0). The interval between ultrasound and birth of two weeks showed the highest sensitivity and specificity (71.6 %, 95 % CI 47.9-87.3 and 91.7, 95 % CI 86.2-95.5). EFW sensitivity and specificity were 76.6 % (95 % CI 70.1-82.3) and 82.9 % (95 % CI 80.9-84.8), while AC 84.8 % (95 % CI 78.2-90.0) and 73.7 % (95 % CI 71.0-76.4). CONCLUSIONS: Ultrasound demonstrates an overall good diagnostic accuracy in detecting fetal macrosomia in pregnancies with diabetes.

A customised fetal growth and birthweight standard for Qatar: a population-based cohort study.

OBJECTIVES: Customized birthweight centiles have improved the detection of small for gestational age (SGA) and large for gestational age (LGA) babies compared to existing population standards. This study used perinatal registry data to derive coefficients for developing customized growth charts for Qatar. METHODS: The PEARL registry data on women delivering in Qatar (2017-2018) was used to develop a multivariable linear regression model predicting optimal birthweight. Physiological variables included gestational age, maternal height, weight, ethnicity, parity, and sex of the baby. Pathological variables such as hypertension, preexisting and gestational diabetes and smoking were calculated and excluded to derive the optimal weight at term. RESULTS: The regression model found a term optimal birthweight of 3,235 g for a Qatari nationality mother with median height (159 cm), booking weight (72 kg), parity (1) and gestation at birth (276 days) at the end of an uncomplicated pregnancy. Constitutional coefficients significantly affecting birthweight were gestational age, height, weight, and parity. The main pathological factors were preexisting diabetes (increase by +175.7 g) and smoking (decrease by -190.9 g). The SGA and LGA rates in the entire cohort after applying the population-specific customized centiles were 11.1 and 12.2 %, respectively (contrasting with the Hadlock standard: SGA-26.3 % and LGA-1.8 %, and Fenton standard: SGA-12.9 % and LGA-4.0 %). CONCLUSIONS: Constitutional and pathological variations in fetal growth and birthweight apply in the maternity population in Qatar and have been quantified to allow the generation of customised charts for better identification of pregnancies with abnormal growth. Currently in-use population standards may misdiagnose many SGA and LGA babies.

The White Blood Cell Count in Laboring Women at Term Is Associated with Neonatal Macrosomia.

BACKGROUND: Fetal weight estimation at term is a challenging clinical task. OBJECTIVES: To evaluate the association between peripheral white blood cell (WBC) count of the laboring women and neonatal birth weight (BW) for term uncomplicated pregnancies. METHODS: We conducted a single-center, retrospective cohort study (2006-2021) of women admitted in the first stage of labor or planned cesarean delivery. Complete blood counts were collected at admission. BW groups were categorized by weight (grams): < 2500 (group A), 2500-3499 (group B), 3500-4000 (group C), and > 4000 (group D). Two study periods were used to evaluate the association between WBC count and neonatal BW. RESULTS: There were a total of 98,632 deliveries. The dataset analyses showed a lower WBC count that was significantly and linearly associated with a higher BW; P for trend < 0.001 for women in labor. The most significant association was noted for the > 4000-gram newborns; adjusted odds ratio 0.97, 95% confidence interval 0.96-0.98; P < 0.001; adjusted for hemoglobin level, gestational age, and fetal sex. The 2018-2021 dataset analyses revealed WBC as an independent predictor of macrosomia with a significant incremental predictive value (P < 0.0001). The negative predictive value of the WBC count for macrosomia was significantly high, 93.85% for a threshold of WBC < 10.25 × 103/µl. CONCLUSIONS: WBC count should be considered to support the in-labor fetal weight estimation, especially valuable for the macrosomic fetus.

Maternal circulating metabolic biomarkers and their prediction performance for gestational diabetes mellitus related macrosomia.

INTRODUCTION: Gestational diabetes mellitus (GDM), a metabolism-related pregnancy complication, is significantly associated with an increased risk of macrosomia. We hypothesized that maternal circulating metabolic biomarkers differed between women with GDM and macrosomia (GDM-M) and women with GDM and normal neonatal weight (GDM-N), and had good prediction performance for GDM-M. METHODS: Plasma samples from 44 GDM-M and 44 GDM-N were analyzed using Olink Proseek multiplex metabolism assay targeting 92 biomarkers. Combined different clinical characteristics and Olink markers, LASSO regression was used to optimize variable selection, and Logistic regression was applied to build a predictive model. Nomogram was developed based on the selected variables visually. Receiver operating characteristic (ROC) curve, calibration plot, and clinical impact curve were used to validate the model. RESULTS: We found 4 metabolism-related biomarkers differing between groups [CLUL1 (Clusterin-like protein 1), VCAN (Versican core protein), FCRL1 (Fc receptor-like protein 1), RNASE3 (Eosinophil cationic protein), FDR <  0.05]. Based on the different clinical characteristics and Olink markers, a total of nine predictors, namely pre-pregnancy body mass index (BMI), weight gain at 24 gestational weeks (gw), parity, oral glucose tolerance test (OGTT) 2 h glucose at 24 gw, high-density lipoprotein (HDL) and low-density lipoprotein (LDL) at 24 gw, and plasma expression of CLUL1, VCAN and RNASE3 at 24 gw, were identified by LASSO regression. The model constructed using these 9 predictors displayed good prediction performance for GDM-M, with an area under the ROC of 0.970 (sensitivity = 0.955, specificity = 0.886), and was well calibrated (P Hosmer-Lemeshow test = 0.897). CONCLUSION: The Model included pre-pregnancy BMI, weight gain at 24 gw, parity, OGTT 2 h glucose at 24 gw, HDL and LDL at 24 gw, and plasma expression of CLUL1, VCAN and RNASE3 at 24 gw had good prediction performance for predicting macrosomia in women with GDM.

Comprehensive analysis of macrosomia: exploring the association between first-trimester alanine aminotransferase and uric acid measurements in pregnant women.

OBJECTIVES: Investigating the relationship between liver enzymes, uric acid (UA), and macrosomia will benefit physicians in the early detection of complications that may emerge during/after pregnancy. The study analyzed liver enzyme activity and UA levels in first-trimester pregnant for the risk of macrosomia. METHODS: This retrospective cross-sectional research analyzed the data of pregnant women who gave birth between Jan 2021-2023. All data were extracted from medical records, and UA and AST-ALT were examined in all the participants. RESULTS: Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels were higher in the macrosomia (p<0.05). Similarly, UA levels were higher in the macrosomia (p<0.001). There was a moderate positive correlation between ALT and birth weight (r=0.168, p<0.01), while we found a strong positive correlation between UA and birth weight (r=0.355, p<0.01). In the ROC (receiver operating characteristic), Area Under the Curve (AUC) for ALT and UA was significant (p<0.0001) but not for AST (p=0.157). UA showed a predictive value for macrosomia with 68.1 % sensitivity and 63.8 % specificity at a 3.15 cut-off (AUC:0.689; p:0.0001; CI:0.644-0.725). CONCLUSIONS: These results indicate that ALT and UA may be potentially important in determining the risk of macrosomia. The UA had a more potent marker for macrosomia than ALT. The occurrence of macrosomia might be more closely related to the mother's metabolic syndrome rather than NAFLD.

Screening for late-onset gestational diabetes: Are there any clinical benefits?

OBJECTIVE: To determine whether screening for gestational diabetes mellitus (GDM) in the third trimester and managing those who are screen positive on a diabetes pathway affects obstetric and neonatal outcomes. DESIGN: Retrospective study of prospectively collected data. SETTING: London Teaching Hospital. POPULATION OR SAMPLE: A total of 14 366 women delivering between 1 January 2018 and 31 December 2020. METHODS: Retrospective chart analysis. MAIN OUTCOME MEASURES: Diagnosis of late-onset GDM, obstetric and neonatal outcomes. RESULTS: Five hundred and thirty-one women were tested by home glucose monitoring for late-onset GDM from 33 weeks of gestation. In all, 244 were diagnosed as having GDM (group 1) and managed accordingly, and 287 (group 2) were returned to normal care. A total of 1415 women had GDM diagnosed by oral glucose tolerance test before 33 weeks of gestation (group 3). Of the women in group 2, 49.5% had a spontaneous onset of labour compared with only 25.8% and 27% in groups 1 and 3. However, women in group 2 were significantly more likely to have a macrosomic baby (≥4000 g, 25.4%) than groups 1 (16.0%) or 3 (7.2%), and their babies were more likely to be admitted to special care (5.2% versus 2% in group 1). Macrosomic babies were associated with significantly higher rates of shoulder dystocia, third- and fourth-degree tears and postpartum haemorrhage. CONCLUSIONS: Apparent late-onset GDM affects a significant proportion of women, and targeted intervention was associated with better obstetric and neonatal outcomes. These results suggest that all pregnancies with risk factors for late-onset GDM might benefit from active GDM management irrespective of specific glucose thresholds. TWEETABLE ABSTRACT: Women with risk factors for GDM in the third trimester, and their babies, would probably benefit from active management of their blood sugars irrespective of threshold values.

Performance of whole-genome promoter nucleosome profiling of maternal plasma cell-free DNA for prenatal noninvasive prediction of fetal macrosomia: a retrospective nested case-control study in mainland China.

BACKGROUND: Fetal macrosomia is common occurrence in pregnancy, which is associated with several adverse prognosis both of maternal and neonatal. While, the accuracy of prediction of fetal macrosomia is poor. The aim of this study was to develop a reliable noninvasive prediction classifier of fetal macrosomia. METHODS: A total of 3600 samples of routine noninvasive prenatal testing (NIPT) data at 12+ 0-27+ 6 weeks of gestation, which were subjected to low-coverage whole-genome sequencing of maternal plasma cell-free DNA (cfDNA), were collected from three independent hospitals. We identified set of genes with significant differential coverages by comparing the promoter profiling between macrosomia cases and controls. We selected genes to develop classifier for noninvasive predicting, by using support vector machine (SVM) and logistic regression models, respectively. The performance of each classifier was evaluated by area under the curve (AUC) analysis. RESULTS: According to the available follow-up results, 162 fetal macrosomia pregnancies and 648 matched controls were included. A total of 1086 genes with significantly differential promoter profiling were found between pregnancies with macrosomia and controls (p < 0.05). With the AUC as a reference，the classifier based on SVM (CMA-A2) had the best performance, with an AUC of 0.8256 (95% CI: 0.7927-0.8586). CONCLUSIONS: Our study provides that assessing the risk of fetal macrosomia by whole-genome promoter nucleosome profiling of maternal plasma cfDNA based on low-coverage next-generation sequencing is feasible.

A predictive model of macrosomic birth based upon real-world clinical data from pregnant women.

BACKGROUND: Fetal macrosomia is associated with an increased risk of several maternal and newborn complications. Antenatal predication of fetal macrosomia remains challenging. We aimed to develop a nomogram model for the prediction of macrosomia using real-world clinical data to improve the sensitivity and specificity of macrosomia prediction. METHODS: In the present study, we performed a retrospective, observational study based on 13,403 medical records of pregnant women who delivered singleton infants at a tertiary hospital in Shanghai from 1 January 2018 through 31 December 2019. We split the original dataset into a training set (n = 9382) and a validation set (n = 4021) at a 7:3 ratio to generate and validate our model. The candidate variables, including maternal characteristics, laboratory tests, and sonographic parameters were compared between the two groups. A univariate and multivariate logistic regression was carried out to explore the independent risk factors for macrosomia in pregnant women. Thus, the regression model was adopted to establish a nomogram to predict the risk of macrosomia. Nomogram performance was determined by discrimination and calibration metrics. All the statistical analysis was analyzed using R software. RESULTS: We compared the differences between the macrosomic and non-macrosomic groups within the training set and found 16 independent risk factors for macrosomia (P < 0.05), including biparietal diameter (BPD), head circumference (HC), femur length (FL), amniotic fluid index (AFI) at the last prenatal examination, pre-pregnancy body mass index (BMI), and triglycerides (TG). Values for the areas under the curve (AUC) for the nomogram model were 0.917 (95% CI, 0.908-0.927) and 0.910 (95% CI, 0.894-0.927) in the training set and validation set, respectively. The internal and external validation of the nomogram demonstrated favorable calibration as well as discriminatory capability of the model. CONCLUSIONS: Our model has precise discrimination and calibration capabilities, which can help clinical healthcare staff accurately predict macrosomia in pregnant women.

Can alanine aminotransferase measured in early pregnancy predict macrosomia?

Non-alcoholic fatty liver disease (NAFLD) is a part of the metabolic syndrome and is associated with adverse pregnancy outcomes. The aim of this study was to determine whether unexplained elevated ALT in early pregnancy has any effect in the prediction of large for gestational age (LGA) infants. In this study, the relationship between birth weights of LGA babies and babies with normal weight for gestational age (AGA) and ALT values measured in early pregnancy was evaluated. While a positive, moderately strong, statistically significant correlation was found between infant birth weight and ALT levels in LGA babies this correlation was continued when GDM was not detected and ALT levels were below 36 U/L. Foetal macrosomia, which can develop in advanced gestational weeks, can be predicted with this cheap, easy and simple method that can be checked in the first trimester and pregnancy follow-up can be shaped accordingly.IMPACT STATEMENTWhat is already known on this subject? It is suggested that asymptomatic high ALT values measured in the first trimester can predict a macrosomic foetus.What do the results of this study add? Asymptomatic elevated ALT values measured in the first trimester can predict a macrosomic foetus.What are the implications of these findings for clinical practice and/or further research? Macrosomic foetus development can be predicted with abnormal results obtained with this simple, cheap and easy measurement method measured in the first trimester and pregnancy follow-up can be managed accordingly.

Comparison of one hour versus 90 minute postprandial glucose measurement in women with gestational diabetes; which one is more effective?

In the present study, we aimed to compare postprandial 90 minute measurements and postprandial 1 hour (PP1-HR) measurements for prediction of foetal growth disturbances and pregnancy complications. This was a prospective study conducted in Acibadem Mehmet Ali Aydinlar University Altunizade Hospital in Department of Perinatology. The study group consisted of patients diagnosed with gestational diabetes. In each antepartum visit, the patients fasting plasma glucose as well as PP1-HR and 90 minute measurements were made. Perinatal and neonatal data were obtained from each patient. The rate of large for gestational age infants was increased in patients when either PP1-HR measurement above 140 mg/dl or postprandial 90 minute measurement above 165 mg/dl compared to patients with normal PP1-HR or postprandial 90 minute measurement. Preterm delivery rate was increased in patients with postprandial 90 minute measurement above 165 mg/dl but not in patients with PP1-HR measurement above 140 mg/dl. The optimal cut-off for postprandial 90 minute measurement was 165 mg/dl based on receiver operating characteristics curve. Our preliminary data show that postprandial 90 minute measurements are superior to PP1-HR measurements in predicting large for gestational age infants.Impact StatementWhat is already known on this subject? Gestational diabetes (GDM) is defined as any degree of glucose intolerance with onset or first recognition in pregnancy. Maternal hyperglycaemia has been linked to metabolic alterations in the foetus and thus brings about foetal macrosomia as well as other pregnancy complications such as preterm delivery and preeclampsia.What the results of this study add? The findings of the present study suggest that postprandial 90 minute predicted more cases of LGA infants than postprandial 1-hour (PP1-HR) measurements. In addition, the rate of preterm deliveries was found to be increased in patients with mean postprandial 90 minute measurements above 165 mg/dl compared to patients with postprandial 90 minute measurements below 165 mg/dl. However, the rate of preterm deliveries was similar in patients with elevated PP1-HR measurements and patients with normal PP1-HR measurements.What the implications are of these findings for clinical practice and/or further research? Our study is the first to investigate the usefulness of postprandial 90 minute in a prospective design. Our preliminary data show that postprandial 90 minute measurements are superior to PP 1 measurements in predicting LGA babies. It also correlates better with preterm deliveries.

Umbilical Cord Biometry and Fetal Abdominal Skinfold Assessment as Potential Biomarkers for Fetal Macrosomia in a Gestational Diabetes Romanian Cohort.

Backgroundand Objectives: Gestational diabetes mellitus (GDM) is a pregnancy-associated pathology commonly resulting in macrosomic fetuses, a known culprit of obstetric complications. We aimed to evaluate the potential of umbilical cord biometry and fetal abdominal skinfold assessment as screening tools for fetal macrosomia in gestational diabetes mellitus pregnant women. Materials and methods: This was a prospective case−control study conducted on pregnant patients presenting at 24−28 weeks of gestation in a tertiary-level maternity hospital in Northern Romania. Fetal biometry, fetal weight estimation, umbilical cord area and circumference, areas of the umbilical vein and arteries, Wharton jelly (WJ) area and abdominal fold thickness measurements were performed. Results: A total of 51 patients were enrolled in the study, 26 patients in the GDM group and 25 patients in the non-GDM group. There was no evidence in favor of umbilical cord area and WJ amount assessments as predictors of fetal macrosomia (p > 0.05). However, there was a statistically significant difference in the abdominal skinfold measurement during the second trimester between macrosomic and normal-weight newborns in the GDM patient group (p = 0.016). The second-trimester abdominal circumference was statistically significantly correlated with fetal macrosomia at term in the GDM patient group with a p value of 0.003, as well as when considering the global prevalence of macrosomia in the studied populations, 0.001, when considering both populations. Conclusions: The measurements of cord and WJ could not be established as predictors of fetal macrosomia in our study populations, nor differentiate between pregnancies with and without GDM. Abdominal skinfold measurement and abdominal circumference measured during the second trimester may be important markers of fetal metabolic status in pregnancies complicated by GDM.

[Reducing rate of macrosomia in Iceland in relation to changes in the labor induction rate].

AIM: Diabetes and prolonged pregnancy are risk factors of macrosomia. The aim was to explore the relationship between the increased rate of labor induction and macrosomia in Iceland. Changes in the incidence proportion of macrosomia was estimated by gestational age. Further, the association between labor induction and macrosomia was estimated in reference to expectant management. MATERIAL AND METHODS: Data from the Iceland birth registry on 92,424 singleton births from 1997 to 2018 was used in this cohort study. Macrosomia was defined as birth weight more than 4.5 kg. The incidence proportion during three periods, 1997-2004, 2005-2011, 2012-2018, was calculated and stratified by gestational age. The relative risk reduction of macrosomia over time was calculated with log-binomial regression, using the first period as reference. The risk and relative risk of macrosomia compared with expectant management was estimated and adjusted for diabetes. RESULTS: The total number of macrosomic infants was 5110 and of those only 313 had a mother with diabetes. The incidence proportion of macrosomia was 6.5% during the period 1997-2004, but 4.6% during 2012-2018. A relative risk reduction of macrosomia over time was seen for deliveries after estimated due date. Labor induction decreased the risk of macrosomia, but the association persisted after adjustment for diabetes. CONCLUSION: The rate of macrosomia decreased in Iceland during the last two decades, but only a small proportion of macrosomic infants had a mother with diabetes. Labor induction decreased the risk of macrosomia, an association which seemed independent of diabetes.

Gestational body weight gain and risk of low birth weight or macrosomia in women of Japan: a nationwide cohort study.

OBJECTIVE: Both maternal prepregnancy body mass index (BMI) and gestational weight gain (GWG) influence maternal and pediatric outcomes. We sought to clarify the impact of prepregnancy BMI-specific GWG and its patterns on the risk of low birth weight (LBW) or macrosomia using data from a large nationwide study in Japan. METHODS: This cohort study (n = 98,052) used data from the Japan Environment and Children's Study (JECS). The outcome variables in this study were LBW and macrosomia. We stratified the subjects into groups according to prepregnancy BMI. RESULTS: GWG from pre-pregnancy to the first trimester had a small effect on the risk of LBW and macrosomia. From the first to second trimesters, insufficient GWG was associated with the risk of LBW, and from the second trimester to delivery, a GWG of less than 2 kg was associated with the risk of LBW. These associations were commonly observed in all prepregnancy BMI categories. Irrespective of the GWG from pre-pregnancy to the first trimester, GWG from the first to second trimesters affects LBW and/or macrosomia. Irrespective of the GWG from the first to second trimesters, GWG from the second trimester to delivery affects LBW and/or macrosomia. LBW or macrosomia was associated with the prevalence of a sustained low or high BMI percentile until three years of age, respectively. CONCLUSIONS: The present large national cohort study indicates that the risk of LBW or macrosomia is associated with GWG in women in Japan; the significance of this risk depends on the GWG patterns.

Heterozygous recurrent HNF4A variant p.Arg85Trp causes Fanconi renotubular syndrome 4 with maturity onset diabetes of the young, an autosomal dominant phenocopy of Fanconi Bickel syndrome with colobomas.

Heterozygous pathogenic variants in HNF4A cause hyperinsulinism, maturity onset diabetes of the young type 1, and more rarely Fanconi renotubular syndrome. Specifically, the recurrent missense pathogenic variant c.253C>T (p.Arg85Trp) has been associated with a syndromic form of hyperinsulinism with additional features of macrosomia, renal tubular nephropathy, hypophosphatemic rickets, and liver involvement. We present an affected mother, who had been previously diagnosed clinically with the autosomal recessive Fanconi Bickel Syndrome, and her affected son. The son's presentation expands the clinical phenotype to include multiple congenital anomalies, including penile chordee with hypospadias and coloboma. This specific pathogenic variant should be considered in the differential diagnosis of Fanconi Bickel Syndrome when genetics are negative or the family history is suggestive of autosomal dominant inheritance. The inclusion of hyperinsulinism and maturity onset of the diabetes of the young changes the management of this syndrome and the recurrence risk is distinct. Additionally, this family also emphasizes the importance of genetic confirmation of clinical diagnoses, especially in adults who grew up in the premolecular era that are now coming to childbearing age. Finally, the expansion of the phenotype to include multiple congenital anomalies suggests that the full spectrum of HNF4A is likely unknown.

A first trimester prediction model for large for gestational age infants: a preliminary study.

BACKGROUND: Large for gestational age infants (LGA) have increased risk of adverse short-term perinatal outcomes. This study aims to develop a multivariable prediction model for the risk of giving birth to a LGA baby, by using biochemical, biophysical, anamnestic, and clinical maternal characteristics available at first trimester. METHODS: Prospective study that included all singleton pregnancies attending the first trimester aneuploidy screening at the Obstetric Unit of the University Hospital of Modena, in Northern Italy, between June 2018 and December 2019. RESULTS: A total of 503 consecutive women were included in the analysis. The final prediction model for LGA, included multiparity (OR = 2.8, 95% CI: 1.6-4.9, p = 0.001), pre-pregnancy BMI (OR = 1.08, 95% CI: 1.03-1.14, p = 0.002) and PAPP-A MoM (OR = 1.43, 95% CI: 1.08-1.90, p = 0.013). The area under the ROC curve was 70.5%, indicating a satisfactory predictive accuracy. The best predictive cut-off for this score was equal to - 1.378, which corresponds to a 20.1% probability of having a LGA infant. By using such a cut-off, the risk of LGA can be predicted in our sample with sensitivity of 55.2% and specificity of 79.0%. CONCLUSION: At first trimester, a model including multiparity, pre-pregnancy BMI and PAPP-A satisfactorily predicted the risk of giving birth to a LGA infant. This promising tool, once applied early in pregnancy, would identify women deserving targeted interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT04838431 , 09/04/2021.

The added value of umbilical vein flow in predicting fetal macrosomia at 36 weeks of gestation: A prospective cohort study.

INTRODUCTION: Current models based on fetal biometry and maternal characteristics have a poor performance in predicting macrosomia. The primary aim of this study was to elucidate the diagnostic performance of fetal venous and arterial Dopplers in predicting macrosomia in the third trimester of pregnancy; the secondary aim was to build a multiparametric prediction model including pregnancy, ultrasound and Doppler characteristics able to predict macrosomia accurately. MATERIAL AND METHODS: Prospective cohort study including 2156 singleton pregnancies scheduled for routine ultrasound assessment at 36 weeks of gestation. Fetal biometry, estimated fetal weight (EFW), pulsatility index of the uterine, umbilical, and middle cerebral arteries, cerebroplacental ratio and umbilical vein blood flow (UVBF) normalized for fetal abdominal circumference (UVBF/AC) were recorded. Primary outcome was the prediction of fetal macrosomia, defined as a birthweight >90th percentile; secondary outcome was the prediction of newborns >4000 g. Logistic regression and area under the curve (AUC) analyses were used to analyze the data. RESULTS: Fetal macrosomia complicated 9.8% of pregnancies, and 7.7% of newborns had a birthweight >4000 g. At multivariate logistic regression analysis, maternal body mass index (adjusted odds ratio [aOR] 1.23), pregestational diabetes (aOR 1.83), a prior newborn with a birthweight >95th centile (aOR 1.49), EFW (aOR 2.23) and UVBF (aOR1.84) were independently associated with macrosomia, whereas gestational diabetes mellitus (P = .07) or any of the other Doppler parameters were not. EFW had an AUC of 0.750 and of 0.801 alone and in association with maternal characteristics for the prediction of macrosomia, respectively. The addition of UVBF to this model significantly improved the prediction of fetal macrosomia provided by maternal and ultrasound parameters with an AUC of 0.892 (De Long P = .044 and P = .0078, respectively). The predictive performance for birthweight >4000 g was similar and significantly improved when UVBF was included in the diagnostic algorithm. CONCLUSIONS: Umbilical vein blood flow evaluation in the third trimester improves the diagnosis of fetal macrosomia. The optimal diagnostic performance for macrosomia is achieved by a multiparametric model including umbilical vein flow, maternal characteristics and EFW.

Macrosomia is a risk factor for incident maternal chronic kidney disease.

BACKGROUND: Gestational diabetes mellitus (GDM) and macrosomia are associated with several adverse outcomes including diabetes mellitus and cardiovascular diseases, however, the relationship between GDM/macrosomia with incident chronic kidney disease (CKD) is a matter of debate. The purpose of this study was to examine the association between the history of macrosomia with or without GDM and incident maternal CKD. METHODS: The study population includes 2669 women aged 18-50 years without known diabetes mellitus and CKD from participants of the Tehran Lipid and Glucose Study. The study population was categorized into 3 groups; group 1: GDM/macrosomia and without diabetes mellitus (n = 204), group 2: newly diagnosed incident diabetes mellitus (NDM) in the presence or abcence of GDM/Macrosomia (n = 113), and, group 3: the reference group including women without prior history of GDM/macrosomia and free of NDM (n = 2352). CKD was defined as an estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m2. Multivariable Cox proportional hazard regression adjusted for baseline values of age, body mass index, waist circumference, parity numbers, smoking, educational level, gestational hypertension, eGFR, systolic and diastolic blood pressures (SBP and DBP, respectively), anti-hypertensive medication, and family history of diabetes mellitus was applied for data analyses. RESULTS: During a median follow-up of 11.9 years, 613 incident CKD cases were identified. The multivariable hazard ratio (HR) and 95% confidence interval (CI) on GDM/macrosomia group was [1.32 (1.02-1.72)]; the risk was more prominent among non-hypertensive women [1.41 (1.07-1.85); P for interaction: 0.046]. Moreover, the history of macrosomia alone also showed a significant risk [1.36 (1.04-1.78)]; however, history of GDM alone did not have a significant risk [0.92 (0.34-2.46)]. Age, current smoking, eGFR, and SBP remained as independent risk factors for incident CKD. CONCLUSIONS: A history of GDM/macrosomia or macrosomia alone, independent of subsequent diabetes mellitus was associated with significant risk for incident maternal CKD. Pregnancy may provide a unique situation to identify high-risk women at risk for CKD that could benefit from regular monitoring of kidney function and providing risk modifying strategies.

Three-dimensional power Doppler ultrasonography indicates that increased placental blood perfusion during the third trimester is associated with the risk of macrosomia at birth.

PURPOSE: To investigate the association between placental blood perfusion and the occurrence of macrosomia at birth. METHODS: This was a prospective cohort study including women with singleton pregnancies that aimed to measure placental blood perfusion using three-dimensional (3D) power Doppler ultrasonography in the second and third trimester. We acquired three indices of placental blood flow, including vascularization index (VI), flow index (FI), vascularization flow index (VFI), along with routine two-dimensional (2D) biometric measurements, including abdominal circumference (AC) and estimated fetal weight (EFW). Pregnancy outcomes were divided into two groups: newborns with a normal birth weight and those with macrosomia. We then compared all of the recorded variables between these two groups. We also determined the predictive efficiency of each variable using receiver-operating characteristic (ROC) curves. RESULTS: The placental 3D power Doppler indices, including VI and FI, were significantly higher in the third trimester of pregnancies developing macrosomia, but not during the second trimester, as compared to those with a normal birth weight. ROC curves analysis for third-trimester VI and FI suggested a slight ability to predict macrosomia; this was also the case for AC and EFW. Interestingly, VI showed high sensitivity and low specificity, while FI showed low sensitivity and high specificity; this was also the case for AC and EFW. CONCLUSIONS: Three-dimensional power Doppler ultrasound indices were significantly higher during the third-trimester for pregnancies developing macrosomia. However, these indices had only moderate ability to predict macrosomia.