Prominent themes in shoulder dystocia research: A bibliometric and document-based analysis.

BACKGROUND: This study aims to comprehensively examine the academic development of shoulder dystocia (SD) through bibliometric and document analysis and to identify topics that can guide future research. METHODS: In this study, performance, co-citation, co-word, and document analyses were used as bibliometric analysis techniques. RESULTS: The study identified 3 main themes in terms of the intellectual structure of Shoulder Dystocia (SD): "Management of SD, Risk Factors and Associated Complications," "Clinical Practices, Birth Abnormalities and Effects of Complications," and "Impact of Education, Clinical Maneuvers and Fetal Health Outcomes." Co-occurrence analysis identified 4 significant themes: "Management and Clinical Practice of SD," "Fetal Macrosomia and Risk Factors," "Obstetric Maneuvers and Brachial Plexus Injury," and "Clinical Trends and Risks in SD." Additionally, ten consolidated themes were identified as a result of thematic coding analysis. CONCLUSION: Shoulder dystocia remains a critical component of obstetric practice. Themes such as training and simulation, risk factors, and technical and management approaches are consistently emphasized. Technological advances and studies on how machine learning techniques can be used effectively in this field reflect innovative approaches in the scientific literature. This analysis confirms that shoulder dystocia is a complex topic requiring a multidisciplinary approach and that research in this field is constantly evolving.

Decreased complexity of glucose time series index associated with adverse pregnancy outcomes in gestational diabetes mellitus.

AIM: We investigated the relationship between the complexity of the glucose time series index (CGI) during pregnancy and adverse pregnancy outcomes in women with gestational diabetes mellitus (GDM). MATERIALS AND METHODS: In this retrospective cohort study, 388 singleton pregnant women with GDM underwent continuous glucose monitoring (CGM) at a median of 26.86 gestational weeks. CGI was calculated using refined composite multiscale entropy based on CGM data. The participants were categorized into tertiles according to their baseline CGI (CGI <2.32, 2.32-3.10, ≥3.10). Logistic regression was used to assess the association between CGI and composite adverse outcomes or large for gestational age (LGA). The discrimination performance of CGI was estimated using receiver operating characteristic analysis. RESULTS: Of the 388 participants, 71 (18.3%) had LGA infants and 63 (16.2%) had composite adverse outcomes. After adjustments were made for confounders, compared with those with a high CGI (CGI ≥3.10), participants with a low CGI (CGI <2.32) had a higher risk of composite adverse outcomes (odds ratio: 12.10, 95% confidence interval: 4.41-33.18) and LGA (odds ratio: 12.68, 95% confidence interval: 4.04-39.75). According to the receiver operating characteristic analysis, CGI was significantly better than glycated haemoglobin and conventional CGM indicators for the prediction of adverse pregnancy outcomes (all p < .05). CONCLUSION: A lower CGI during pregnancy was associated with composite adverse outcomes and LGA. CGI, a novel glucose homeostasis predictor, seems to be superior to conventional glucose indicators for the prediction of adverse pregnancy outcomes in women with GDM.

Maternal anaemia and polycythaemia during pregnancy and risk of inappropriate birth weight for gestational age babies: a retrospective cohort study in the northern belt of Ghana.

BACKGROUND: Small for gestational age (SGA) and large for gestational age (LGA) births are topical issues due to their devastating effects on the life course and are also accountable for neonatal mortalities and long-term morbidities. OBJECTIVE: We tested the hypothesis that abnormal haemoglobin levels in each trimester of pregnancy will increase the risk of SGA and LGA deliveries in Northern Ghana. DESIGN: A retrospective cohort study was conducted from April to July 2020. SETTINGS AND PARTICIPANTS: 422 postpartum mothers who had delivered in the last 6-8 weeks before their interview dates were recruited through a systematic random sampling technique from five primary and public health facilities in Northern Ghana. PRIMARY MEASURES: Using the INTERGROWTH-21st standard, SGA and LGA births were obtained. Haemoglobin levels from antenatal records were analysed to determine their effect on SGA and LGA births by employing multinomial logistic regression after adjusting for sociodemographic and obstetric factors at a significance level of α=0.05. RESULTS: Prevalence of anaemia in the first, second and third trimesters of pregnancy was 63.5%, 71.3% and 45.3%, respectively, and that of polycythaemia in the corresponding trimesters of pregnancy was 5.9%, 3.6% and 1.7%. About 8.8% and 9.2% of the women delivered SGA and LGA babies, respectively. After adjusting for confounders, anaemic mothers in the third trimester of pregnancy had an increased risk of having SGA births (adjusted OR, aOR 5.56; 95% CI 1.65 to 48.1; p<0.001). Mothers with polycythaemia in the first, second and third trimesters of pregnancy were 93% (aOR 0.07; 95% CI 0.01 to 0.46; p=0.040), 85% (aOR 0.15; 95% CI 0.08 to 0.64; p<0.001) and 88% (aOR 0.12; 95% CI 0.07 to 0.15; p=0.001) protected from having SGA births, respectively. Interestingly, anaemia and polycythaemia across all trimesters of pregnancy were not statistically significant with LGA births. CONCLUSION: Anaemia during pregnancy increased from the first to the second trimester and subsequently decreased in the third trimester while polycythaemia consistently decreased from the first to the third trimester. LGA babies were more predominant compared with SGA babies. While anaemia in the third trimester of pregnancy increased the risk of SGA births, polycythaemia across the trimesters offered significant protection. Healthcare providers and stakeholders should target pressing interventions for anaemia reduction throughout pregnancy, especially during the third trimester to achieve healthy birth outcomes.

Associations between maternal early pregnancy depression and longitudinal fetal growth.

BACKGROUND: The impacts of maternal depression during mid-to-late pregnancy on fetal growth have been extensively investigated. However, the association between maternal depression during early pregnancy and fetal intrauterine growth are less clear. METHODS: A prospective study comprised 23,465 eligible pregnant women and their offspring was conducted at a hospital-based center in Shanghai. Prenatal depression was assessed used using Patient Health Questionnaire (PHQ-9) before 14 gestational weeks. Differences in fetal growth trajectory of different maternal depressive statuses during three periods (16-23, 24-31, and 32-41 gestational weeks) were compared using a multilevel model with fractional polynomials. RESULTS: Women with depressive symptoms during early pregnancy had higher longitudinal fetal trajectories, with an estimated increase in fetal weight (ß = 0.33; 95 % CI, 0.06-0.61), compared to those without depressive symptoms. Increases in fetal abdominal circumference among women with depressive symptoms were observed before 23 gestational weeks. Offspring born to mothers with early pregnancy depression had a significantly higher birth weight of 14.13 g (95 % CI, 1.33-27.81 g) and an increased risk of severe large size for gestational age (adjusted odds ratio [aOR], 1.64; 95 % CI, 1.32-2.04) and macrosomia (aOR, 1.21; 95 % CI, 1.02-1.43). LIMITATIONS: Self-rated scale was used to assess depressive symptoms rather than clinical diagnosis. And Long-term effects of early pregnancy depression on offspring were not explored. CONCLUSIONS: The study revealed an association between maternal depression during early pregnancy and increased fetal biometrics, higher birth weight, and an elevated risk of severe large size for gestational age and macrosomia.

Association between maternal lipid profiles and vitamin D status in second trimester and risk of LGA or SGA: a retrospective study.

Background: Accumulating evidence has linked dyslipidemia during pregnancy to the risk of delivering infants born either large for gestational age (LGA) or small for gestational age (SGA). However, the effects of the vitamin D status on these relationships require further investigation. This study investigated whether the relationship between lipid profiles and the risk of LGA or SGA was influenced by vitamin D levels during the second trimester. Methods: Maternal lipid profile levels, including total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and vitamin D levels, were measured in a cohort of 6,499 pregnant women during the second trimester. Multivariate regression models and subgroup analyses were employed to evaluate the potential associations between maternal lipid profiles, vitamin D levels, and the risk of LGA or SGA. Results: The prevalence of SGA infants was 9.8% (n=635), whereas that of LGA infants was 6.9% (n=447). Maternal TG levels were found to be positively associated with the risk of LGA (odds ratio [OR] = 1.41, 95% confidence interval [CI]:1.17-1.70), whereas a negative association was observed between maternal TG, TC, LDL-C levels, and risk of SGA. Additionally, mothers with higher HDL-C levels were less likely to give birth to an LGA infant (OR=0.58, 95% CI:0.39-0.85). Importantly, associations between TG, TC, LDL-c, and SGA as well as between TG and LGA were primarily observed among pregnant women with insufficient vitamin D levels. As for HDL-C, the risk of LGA was lower in mothers with sufficient vitamin D (OR = 0.42, 95% CI:0.18-0.98) compared to those with insufficient vitamin D (OR = 0.65, 95% CI:0.42-0.99). Conclusion: Vitamin D status during the second trimester exerts a modifying effect on the association between lipid profiles and the risk of LGA and SGA infants.

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).

Prevalence of macrosomic newborn and maternal and neonatal complications in a high-risk maternity.

Objective: Evaluate the prevalence of macrosomic newborns (birth weight above 4000 grams) in a high-risk maternity from 2014 to 2019, as well as the maternal characteristics involved, risk factors, mode of delivery and associated outcomes, comparing newborns weighing 4000-4500 grams and those weighing above 4500 grams. Methods: This is an observational study, case-control type, carried out by searching for data in hospital's own system and clinical records. The criteria for inclusion in the study were all patients monitored at the service who had newborns with birth weight equal than or greater than 4000 grams in the period from January 2014 to December 2019, being subsequently divided into two subgroups (newborns with 4000 to 4500 grams and newborns above 4500 grams). After being collected, the variables were transcribed into a database, arranged in frequency tables. For treatment and statistical analysis of the data, Excel and R software were used. This tool was used to create graphs and tables that helped in the interpretation of the results. The statistical analysis of the variables collected included both simple descriptive analyzes as well as inferential statistics, with univariate, bivariate and multivariate analysis. Results: From 2014 to 2019, 3.3% of deliveries were macrosomic newborns. The average gestational age in the birth was 39.4 weeks. The most common mode of delivery (65%) was cesarean section. Diabetes mellitus was present in 30% of the deliveries studied and glycemic control was absent in most patients. Among the vaginal deliveries, only 6% were instrumented and there was shoulder dystocia in 21% of the cases. The majority (62%) of newborns had some complication, with jaundice (35%) being the most common. Conclusion: Birth weight above 4000 grams had a statistically significant impact on the occurrence of neonatal complications, such as hypoglycemia, respiratory distress and 5th minute APGAR less than 7, especially if birth weight was above 4500 grams. Gestational age was also shown to be statistically significant associated with neonatal complications, the lower, the greater the risk. Thus, macrosomia is strongly linked to complications, especially neonatal complications.

Association of trajectories and cumulative exposure of antenatal depression with high birth weight.

BACKGROUND: Inconsistent associations between antenatal depression and fetal birth weight were reported previously, and little is known about the dynamic changes and long-term cumulative effect of antenatal depression during pregnancy. METHODS: Participants were from the Tongji-Huaxi-Shuangliu Birth Cohort. Depressive symptoms were measured using the Edinburgh Postnatal Depression Scale in early, middle, and late pregnancy respectively. Trajectories of antenatal depression were assessed using the latent class mixed model. The percentage of days with depression (PDD) and frequency of antenatal depression were measured to assess the cumulative exposure. Multivariable logistic regression models were used to evaluate the associations of antenatal depression with macrosomia and large for gestational age (LGA). RESULTS: We identified four distinct trajectories, including the low stable group (n = 1,327, 27.99 %), the moderate stable group (n = 2,610, 55.05 %), the peak group (n = 407, 8.58 %), and the valley group (n = 397, 8.37 %). Compared with the low stable group, the valley group showed a higher risk of macrosomia (OR, 1.98; 95 % CI, 1.17, 3.38) and LGA (OR, 1.44; 95 % CI, 1.002, 2.09); the peak group showed a higher risk of LGA (OR, 1.52; 95 % CI, 1.07, 2.16), but the association was not significant for macrosomia (OR, 1.47; 95 % CI, 0.85, 2.55). Consistently, cumulative antenatal depression was also positively associated with the risks of macrosomia and LGA. LIMITATION: The antenatal depression was self-reported using a screening scale and information bias could not be ruled out. CONCLUSION: Certain trajectories and cumulative exposure of antenatal depression were associated with higher risks of high birth weight.

Prenatal exposure to ambient air pollution and risk of fetal overgrowth: Systematic review of cohort studies.

OBJECTIVES: Fetal overgrowth has detrimental effects on both the mother and the fetus. The global issue of ambient air pollution has been found to contribute to fetal overgrowth through various pathways. This study aimed to identify the association between prenatal exposure to ambient air pollution and the risk of fetal overgrowth. METHODS: We identified articles between January 2013 and February 2024 by searching the Web of Sciences(WoS), PubMed, Proquest, Scopus, and Google Scholar databases. Quality assessment was performed using the Newcastle Ottawa scale. This review was provided based on the PRISMA guideline and registered with PROSPERO, "CRD42023488936". RESULTS: The search generated 1719 studies, of which 22 cohort studies were included involving 3,480,041 participants. Results on the effects of air pollutants on fetal overgrowth are inconsistent because they vary in population and geographic region. But in general, the results indicate that prenatal exposure to air pollutants, specifically PM2.5, NO2, and SO2, is linked to a higher likelihood of fetal overgrowth(macrosomia and large for gestational age). Nevertheless, the relationship between CO and O3 pollution and fetal overgrowth remains uncertain. Furthermore, PM10 has a limited effect on fetal overgrowth. It is essential to consider the time that reproductive-age women are exposed to air pollution. Exposure to air pollutants before conception and throughout pregnancy has a substantial impact on the fetus's vulnerability to overgrowth. CONCLUSIONS: Fetal overgrowth has implications for the health of both mother and fetus. fetal overgrowth can cause cardiovascular diseases, obesity, type 2 diabetes, and other diseases in adulthood, so it is considered an important issue for the health of the future generation. Contrary to popular belief that air pollution leads to intrauterine growth restriction and low birth weight, this study highlights that one of the adverse consequences of air pollution is macrosomia or LGA during pregnancy. Therefore governments must focus on implementing initiatives that aim to reduce pregnant women's exposure to ambient air pollution to ensure the health of future generations.

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.

Development and evaluation of machine learning models for predicting large-for-gestational-age newborns in women exposed to radiation prior to pregnancy.

INTRODUCTION: The correlation between radiation exposure before pregnancy and abnormal birth weight has been previously proven. However, for large-for-gestational-age (LGA) babies in women exposed to radiation before becoming pregnant, there is no prediction model yet. MATERIAL AND METHODS: The data were collected from the National Free Preconception Health Examination Project in China. A sum of 455 neonates (42 SGA births and 423 non-LGA births) were included. A training set (n = 319) and a test set (n = 136) were created from the dataset at random. To develop prediction models for LGA neonates, conventional logistic regression (LR) method and six machine learning methods were used in this study. Recursive feature elimination approach was performed by choosing 10 features which made a big contribution to the prediction models. And the Shapley Additive Explanation model was applied to interpret the most important characteristics that affected forecast outputs. RESULTS: The random forest (RF) model had the highest average area under the receiver-operating-characteristic curve (AUC) for predicting LGA in the test set (0.843, 95% confidence interval [CI]: 0.714-0.974). Except for the logistic regression model (AUC: 0.603, 95%CI: 0.440-0.767), other models' AUCs displayed well. Thereinto, the RF algorithm's final prediction model using 10 characteristics achieved an average AUC of 0.821 (95% CI: 0.693-0.949). CONCLUSION: The prediction model based on machine learning might be a promising tool for the prenatal prediction of LGA births in women with radiation exposure before pregnancy.

Perinatal Outcomes of Diet Therapy in Gestational Diabetes Mellitus Diagnosed before 24 Gestational Weeks.

To evaluate perinatal outcomes and risk factors for large for gestational age (LGA; birth weight over 90 percentile) in gestational diabetes diagnosed before 24 gestational weeks and treated with diet therapy alone until delivery (Diet Early gestational diabetes mellitus (Diet Early GDM)), we assessed the maternal characteristics and perinatal outcomes of patients with early GDM (n = 309) and normal glucose tolerance (NGT; n = 309) at Keio University Hospital. The gestational weight gain (GWG) expected at 40 weeks was significantly lower in the Diet Early GDM group than in the NGT group. The Diet Early GDM group exhibited a significantly lower incidence of low birth weight (<2500 g) and higher Apgar score at 5 min than the NGT group. Multiple logistic regression analysis revealed that the pre-pregnancy body mass index and GWG expected at 40 weeks were significantly associated with LGA for Diet Early GDM. No differences were observed in random plasma glucose levels in the first trimester, 75 g oral glucose tolerance test values, and initial increase or subsequent decrease between the two groups. Dietary early GDM did not exhibit a worse prognosis than NGT. To prevent LGA, it might be important to control maternal body weight not only during pregnancy but also before conception.

Maternal Hypertriglyceridemia in Gestational Diabetes: A New Risk Factor?

Elevated maternal triglycerides (TGs) have been associated with excessive fetal growth. However, the role of maternal lipid profile is less studied in gestational diabetes mellitus (GDM). We aimed to study the association between maternal lipid profile in the third trimester and the risk for large-for-gestational-age (LGA) newborns in women with GDM. We performed an observational and retrospective study of pregnant women with GDM who underwent a lipid profile measurement during the third trimester. We applied a logistic regression model to assess predictors of LGA. A total of 100 singleton pregnant women with GDM and third-trimester lipid profile evaluation were included. In the multivariate analysis, pre-pregnancy BMI (OR 1.19 (95% CI 1.03-1.38), p = 0.022) and hypertriglyceridemia (OR 7.60 (1.70-34.10), p = 0.008) were independently associated with LGA. Third-trimester hypertriglyceridemia was found to be a predictor of LGA among women with GDM, independently of glycemic control, BMI, and pregnancy weight gain. Further investigation is needed to confirm the role of TGs in excessive fetal growth in GDM pregnancies.

Impact of pregestational obesity on perinatal complications: update in a Latin American cohort.

OBJECTIVES: While the association between pregestational obesity and perinatal complications has been established, it is necessary to update the current understanding of its impact on maternal and foetal health due to its growing prevalence. Thus, this study aimed to investigate the association between pregestational obesity with the leading perinatal complications during the last 6 years. STUDY DESIGN: A cross-sectional study was performed in San Felipe, Chile. Anonymised data of 11,197 deliveries that occurred between 2015 and 2021 were included. METHODS: Pregestational body mass index was defined according to the World Health Organisation during the first trimester of pregnancy. The association between pregestational obesity and perinatal complications was analysed by calculating the odds ratio (OR), which was adjusted for confounding variables. Statistical differences were considered with a P-value of <0.05. RESULTS: The prevalence of pregestational obesity was 30.1%. Pregestational obesity was related to a high incidence of perinatal complications (≥3 complications; P < 0.0001). The main perinatal complications were caesarean section, large for gestational age (LGA), gestational diabetes (GD), macrosomia, hypertensive disorders of pregnancy (HDP), premature rupture of membranes (PROM), intrauterine growth restriction, and failed induction. Pregestational obesity was shown to be a risk factor for macrosomia (OR: 2.3 [95% confidence interval {95% CI}: 2.0-2.8]), GD (OR: 1.9 [95% CI: 1.6-2.1]), HDP (OR: 1.8 [95% CI: 1.5-2.1]), LGA (OR: 1.6 [95% CI: 1.5-1.8]), failed induction (OR: 1.4 [95% CI: 1.0-1.8]), PROM (OR: 1.3 [95% CI: 1.1-1.6]), and caesarean section (OR: 1.3 [95% CI: 1.2-1.4]). CONCLUSIONS: Pregestational obesity has been shown to be a critical risk factor for the main perinatal complications in the study population. Pregestational advice is imperative not only in preventing pregestational obesity but also in the mitigation of critical perinatal complications once they arise.

[Retrospective study of 60 cases of uterine rupture at the Maternity Center of Monastir, Tunisia]. / Etude rétrospective sur 60 cas de rupture utérine du centre de maternité de Monastir, Tunisie.

Uterine rupture is a life-threatening obstetric complication. The purpose of this study was to investigate the epidemiological features, maternal and foetal prognosis and different treatment options for uterine rupture in healthy and scarred uteri. We conducted a retrospective monocentric descriptive and analytical study of 60 cases of uterine rupture collected in the Department of Gynaecology-Obstetrics of the Center of Maternity and Neonatology, Monastir, from 2017 to 2021. Patients were classified according to the presence or absence of a uterine scar. Sixty patients were enrolled in the study. The majority of cases of rupture occurred in patients with scarred uterus (n=55). The most common clinical sign was abnormal foetal heart rate. No maternal deaths were recorded and perinatal mortality rate was 11%. Mean BMI, fetal macrosomia rate and mean parity were significantly higher in the healthy uterus group than in the scarred uterus group (p=0.033, 0.018, and 0.013, respectively). The maternal complications studied (post-partum haemorrhage, hysterectomy, blood transfusion, prolonged hospitalisation) were significantly more frequent in patients with unscarred uterine rupture (p=0.039; p=0.032; p=0.009; p=0.025 respectively). Uterine rupture is a life-threatening obstetrical event for the foetus and the mother. Fetal heart rate abnormality is the most common sign associated with uterine rupture. Management is based on conservative treatment in most cases. Patients with scarred uterus have a better prognosis.

Perinatal factors and early neonatal outcomes of abnormal birthweight infants in Hangzhou, China, 2015-2021: a retrospective cohort study.

BACKGROUND: This study aimed to investigate the perinatal factors and early neonatal outcomes of abnormal birth weight (ABW) in Hangzhou, China from 2015 to 2021. METHODS: A retrospective cohort study was designed to analyse the data of 76 847 newborns, in which the case groups included 3042 cases of low birth weight (LBW) and 2941 cases of fetal macrosomia (MAC), and 70 864 cases of normal weight were as the reference group. RESULTS: The incidence of LBW and MAC was 3.96% and 3.83% in Hangzhou, China from 2015 to 2021. Prematurity (<37 weeks), multiple births, hospitalisation >7 days, fetal anomalies, caesarean section, pregnancy complications, maternal coinfection with pathogens and summer births would be correlated with the incidence of LBW (ORs=43.50, 7.60, 2.09, 1.89, 1.57, 1.28, 1.19 and 1.18, all p<0.05). Factors such as post-term pregnancy (>41 weeks), scarred uterus, anterior vaginal incision and gravidity ≥2 were correlated with decreased incidence of LBW, with ORs of 0.05, 0.54, 0.65 and 0.80. Moreover, caesarean delivery, post-term pregnancy (> 41 weeks), parity ≥1, lateral vaginal incision, gravidity ≥2, hospitalisation >7 days, winter births and pregnancy complications also have association with the incidence of MAC (ORs=3.92, 2.73, 2.19, 1.87, 1.22, 1.20, 1.17 and 1.13, all p<0.05) while prematurity (<37 weeks), scarred uterus and anterior vaginal incision have close association with decreased incidence of MAC, with ORs of 0.07, 0.21 and 0.74 (all p<0.05). CONCLUSION: There was a trend of yearly increase in ABW in Hangzhou, China from 2015 to 2021. Several neonatal and maternal-related variables such as caesarean section, pregnancy complications and hospitalisation >7 days are associated with the odds of LBW and MAC, however, factors such as pregnancy with scarred uterus relate to the decrease of ABW. Close monitoring and intervention during pregnancy are essential to reduce the occurrence of ABW.

Ultrasonographic placental parameters at 11-13+6 weeks' gestation in the prediction of complications in pregnancy after assisted reproductive technology.

OBJECTIVE: To evaluate the performance of maternal factors, biophysical and biochemical markers at 11-13 + 6 weeks' gestation in the prediction of gestational diabetes mellitus with or without large for gestational age (GDM ± LGA) fetus and great obstetrical syndromes (GOS) among singleton pregnancy following in-vitro fertilisation (IVF)/embryo transfer (ET). MATERIALS AND METHODS: A prospective cohort study was conducted between December 2017 and January 2020 including patients who underwent IVF/ET. Maternal mean arterial pressure (MAP), ultrasound markers including placental volume, vascularisation index (VI), flow index (FI) and vascularisation flow index (VFI), mean uterine artery pulsatility index (mUtPI) and biochemical markers including placental growth factor (PlGF) and soluble fms-like tyrosine kinase-1 (sFlt-1) were measured at 11-13 + 6 weeks' gestation. Logistic regression analysis was performed to determine the significant predictors of complications. RESULTS: Among 123 included pregnancies, 38 (30.9%) had GDM ± LGA fetus and 28 (22.8%) had GOS. The median maternal height and body mass index were significantly higher in women with GDM ± LGA fetus. Multivariate logistic regression analysis demonstrated that in the prediction of GDM ± LGA fetus and GOS, there were significant independent contributions from FI MoM (area under curve (AUROC) of 0.610, 95% CI 0.492-0.727; p = 0.062) and MAP MoM (AUROC of 0.645, 95% CI 0.510-0.779; p = 0.026), respectively. CONCLUSION: FI and MAP are independent predictors for GDM ± LGA fetus and GOS, respectively. However, they have low predictive value. There is a need to identify more specific novel biomarkers in differentiating IVF/ET pregnancies that are at a higher risk of developing complications.

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.

An innovative supervised longitudinal learning procedure of recurrent neural networks with temporal data augmentation: Insights from predicting fetal macrosomia and large-for-gestational age.

BACKGROUND: Longitudinal data in health informatics studies often present challenges due to sparse observations from each subject, limiting the application of contemporary deep learning for prediction. This issue is particularly relevant in predicting birthweight, a crucial factor in identifying conditions such as macrosomia and large-for-gestational age (LGA). Previous approaches have relied on empirical formulas for estimated fetal weights (EFWs) from ultrasound measurements and mixed-effects models for interim predictions. METHOD: The proposed novel supervised longitudinal learning procedure features a three-step approach. First, EFWs are generated using empirical formulas from ultrasound measurements. Second, nonlinear mixed-effects models are applied to create augmented sequences of EFWs, spanning daily gestational timepoints. This augmentation transforms sparse longitudinal data into a dense parallel sequence suitable for training recurrent neural networks (RNNs). A tailored RNN architecture is then devised to incorporate the augmented sequential EFWs along with non-sequential maternal characteristics. RESULTS: The RNNs are trained on augmented data to predict birthweights, which are further classified for macrosomia and LGA. Application of this supervised longitudinal learning procedure to the Successive Small-for-Gestational-Age Births study yields improved performance in classification metrics. Specifically, sensitivity, area under the receiver operation characteristic curve, and Youden's Index demonstrate enhanced results, indicating the effectiveness of the proposed approach in overcoming sparsity challenges in longitudinal health informatics data. CONCLUSIONS: The integration of mixed-effects models for temporal data augmentation and RNNs on augmented sequences shows effective in accurately predicting birthweights, particularly in the context of identifying excessive fetal growth conditions.

Mediating effect of gestational weight gain on the preventive effect of exercise during pregnancy on macrosomia: a randomized clinical trial.

OBJECTIVE: We sought to investigate the impact of individualized exercise guidance during pregnancy on the incidence of macrosomia and the mediating effect of gestational weight gain (GWG). DESIGN: A prospective randomized clinical trial. SETTING: A Hospital in Xingtai District, Hebei Province. POPULATION: Older than 20 years of age, mid-pregnancy, and singleton pregnant women without contraindications to exercise during pregnancy. METHODS: A randomized clinical trial was conducted from December 2021 to September 2022 to compare the effects of standard prenatal care with individualized exercise guidance on the incidence of macrosomia. MAIN OUTCOME MEASURE: Incidence of macrosomia. RESULTS: In all, 312 singleton women were randomized into an intervention group (N = 162) or a control group (N = 150). Participants who received individualized exercise guidance had a significantly lower incidence of macrosomia (3.73% vs. 13.61%, P = 0.002) and infants large for gestational age (9.94% vs. 19.73%, P = 0.015). However, no differences were observed in the rate of preterm birth (1.86% vs. 3.40%, P = 0.397) or the average gestational age at birth (39.14 ± 1.51 vs. 38.69 ± 1.85, P = 0.258). Mediation analysis revealed that GWG mediated the effect of exercise on reducing the incidence of macrosomia. CONCLUSION: Individualized exercise guidance may be a preventive tool for macrosomia, and GWG mediates the effect of exercise on reducing the incidence of macrosomia. However, evidence does not show that exercise increases the rate of preterm birth or affects the average gestational age at birth. TRIAL REGISTRATION: The trial is registered at www.clinicaltrails.gov [registration number: NCT05760768; registration date: 08/03/2023 (retrospectively registered)].