Development and validation of prediction models for fetal growth restriction and birthweight: an individual participant data meta-analysis.

Background: Fetal growth restriction is associated with perinatal morbidity and mortality. Early identification of women having at-risk fetuses can reduce perinatal adverse outcomes. Objectives: To assess the predictive performance of existing models predicting fetal growth restriction and birthweight, and if needed, to develop and validate new multivariable models using individual participant data. Design: Individual participant data meta-analyses of cohorts in International Prediction of Pregnancy Complications network, decision curve analysis and health economics analysis. Participants: Pregnant women at booking. External validation of existing models (9 cohorts, 441,415 pregnancies); International Prediction of Pregnancy Complications model development and validation (4 cohorts, 237,228 pregnancies). Predictors: Maternal clinical characteristics, biochemical and ultrasound markers. Primary outcomes: fetal growth restriction defined as birthweight <10th centile adjusted for gestational age and with stillbirth, neonatal death or delivery before 32 weeks' gestation birthweight. Analysis: First, we externally validated existing models using individual participant data meta-analysis. If needed, we developed and validated new International Prediction of Pregnancy Complications models using random-intercept regression models with backward elimination for variable selection and undertook internal-external cross-validation. We estimated the study-specific performance (c-statistic, calibration slope, calibration-in-the-large) for each model and pooled using random-effects meta-analysis. Heterogeneity was quantified using τ2 and 95% prediction intervals. We assessed the clinical utility of the fetal growth restriction model using decision curve analysis, and health economics analysis based on National Institute for Health and Care Excellence 2008 model. Results: Of the 119 published models, one birthweight model (Poon) could be validated. None reported fetal growth restriction using our definition. Across all cohorts, the Poon model had good summary calibration slope of 0.93 (95% confidence interval 0.90 to 0.96) with slight overfitting, and underpredicted birthweight by 90.4 g on average (95% confidence interval 37.9 g to 142.9 g). The newly developed International Prediction of Pregnancy Complications-fetal growth restriction model included maternal age, height, parity, smoking status, ethnicity, and any history of hypertension, pre-eclampsia, previous stillbirth or small for gestational age baby and gestational age at delivery. This allowed predictions conditional on a range of assumed gestational ages at delivery. The pooled apparent c-statistic and calibration were 0.96 (95% confidence interval 0.51 to 1.0), and 0.95 (95% confidence interval 0.67 to 1.23), respectively. The model showed positive net benefit for predicted probability thresholds between 1% and 90%. In addition to the predictors in the International Prediction of Pregnancy Complications-fetal growth restriction model, the International Prediction of Pregnancy Complications-birthweight model included maternal weight, history of diabetes and mode of conception. Average calibration slope across cohorts in the internal-external cross-validation was 1.00 (95% confidence interval 0.78 to 1.23) with no evidence of overfitting. Birthweight was underestimated by 9.7 g on average (95% confidence interval -154.3 g to 173.8 g). Limitations: We could not externally validate most of the published models due to variations in the definitions of outcomes. Internal-external cross-validation of our International Prediction of Pregnancy Complications-fetal growth restriction model was limited by the paucity of events in the included cohorts. The economic evaluation using the published National Institute for Health and Care Excellence 2008 model may not reflect current practice, and full economic evaluation was not possible due to paucity of data. Future work: International Prediction of Pregnancy Complications models' performance needs to be assessed in routine practice, and their impact on decision-making and clinical outcomes needs evaluation. Conclusion: The International Prediction of Pregnancy Complications-fetal growth restriction and International Prediction of Pregnancy Complications-birthweight models accurately predict fetal growth restriction and birthweight for various assumed gestational ages at delivery. These can be used to stratify the risk status at booking, plan monitoring and management. Study registration: This study is registered as PROSPERO CRD42019135045. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 17/148/07) and is published in full in Health Technology Assessment; Vol. 28, No. 14. See the NIHR Funding and Awards website for further award information.

One in ten babies is born small for their age. A third of such small babies are considered to be 'growth-restricted' as they have complications such as dying in the womb (stillbirth) or after birth (newborn death), cerebral palsy, or needing long stays in hospital. When growth restriction is suspected in fetuses, they are closely monitored and often delivered early to avoid complications. Hence, it is important that we identify growth-restricted babies early to plan care. Our goal was to provide personalised and accurate estimates of the mother's chances of having a growth-restricted baby and predict the baby's weight if delivered at various time points in pregnancy. To do so, first we tested how accurate existing risk calculators ('prediction models') were in predicting growth restriction and birthweight. We then developed new risk-calculators and studied their clinical and economic benefits. We did so by accessing the data from individual pregnant women and their babies in our large database library (International Prediction of Pregnancy Complications). Published risk-calculators had various definitions of growth restriction and none predicted the chances of having a growth-restricted baby using our definition. One predicted baby's birthweight. This risk-calculator performed well, but underpredicted the birthweight by up to 143 g. We developed two new risk-calculators to predict growth-restricted babies (International Prediction of Pregnancy Complications-fetal growth restriction) and birthweight (International Prediction of Pregnancy Complications-birthweight). Both calculators accurately predicted the chances of the baby being born with growth restriction, and its birthweight. The birthweight was underpredicted by <9.7 g. The calculators performed well in both mothers predicted to be low and high risk. Further research is needed to determine the impact of using these calculators in practice, and challenges to implementing them in practice. Both International Prediction of Pregnancy Complications-fetal growth restriction and International Prediction of Pregnancy Complications-birthweight risk calculators will inform healthcare professionals and empower parents make informed decisions on monitoring and timing of delivery.

Development and validation of a prognostic model to predict birth weight: individual participant data meta-analysis.

Objective: To predict birth weight at various potential gestational ages of delivery based on data routinely available at the first antenatal visit. Design: Individual participant data meta-analysis. Data sources: Individual participant data of four cohorts (237 228 pregnancies) from the International Prediction of Pregnancy Complications (IPPIC) network dataset. Eligibility criteria for selecting studies: Studies in the IPPIC network were identified by searching major databases for studies reporting risk factors for adverse pregnancy outcomes, such as pre-eclampsia, fetal growth restriction, and stillbirth, from database inception to August 2019. Data of four IPPIC cohorts (237 228 pregnancies) from the US (National Institute of Child Health and Human Development, 2018; 233 483 pregnancies), UK (Allen et al, 2017; 1045 pregnancies), Norway (STORK Groruddalen research programme, 2010; 823 pregnancies), and Australia (Rumbold et al, 2006; 1877 pregnancies) were included in the development of the model. Results: The IPPIC birth weight model was developed with random intercept regression models with backward elimination for variable selection. Internal-external cross validation was performed to assess the study specific and pooled performance of the model, reported as calibration slope, calibration-in-the-large, and observed versus expected average birth weight ratio. Meta-analysis showed that the apparent performance of the model had good calibration (calibration slope 0.99, 95% confidence interval (CI) 0.88 to 1.10; calibration-in-the-large 44.5 g, -18.4 to 107.3) with an observed versus expected average birth weight ratio of 1.02 (95% CI 0.97 to 1.07). The proportion of variation in birth weight explained by the model (R2) was 46.9% (range 32.7-56.1% in each cohort). On internal-external cross validation, the model showed good calibration and predictive performance when validated in three cohorts with a calibration slope of 0.90 (Allen cohort), 1.04 (STORK Groruddalen cohort), and 1.07 (Rumbold cohort), calibration-in-the-large of -22.3 g (Allen cohort), -33.42 (Rumbold cohort), and 86.4 g (STORK Groruddalen cohort), and observed versus expected ratio of 0.99 (Rumbold cohort), 1.00 (Allen cohort), and 1.03 (STORK Groruddalen cohort); respective pooled estimates were 1.00 (95% CI 0.78 to 1.23; calibration slope), 9.7 g (-154.3 to 173.8; calibration-in-the-large), and 1.00 (0.94 to 1.07; observed v expected ratio). The model predictions were more accurate (smaller mean square error) in the lower end of predicted birth weight, which is important in informing clinical decision making. Conclusions: The IPPIC birth weight model allowed birth weight predictions for a range of possible gestational ages. The model explained about 50% of individual variation in birth weights, was well calibrated (especially in babies at high risk of fetal growth restriction and its complications), and showed promising performance in four different populations included in the individual participant data meta-analysis. Further research to examine the generalisability of performance in other countries, settings, and subgroups is required. Trial registration: PROSPERO CRD42019135045.

Hypoglycemia in Oral Glucose Tolerance Test during Pregnancy and Risk for Type 2 Diabetes-A Five-Year Cohort Study.

Objective: To evaluate the risk of progression to type 2 diabetes (T2D) following reactive hypoglycemia in 100 g oral glucose tolerance test (oGTT). Methods: A retrospective analysis of parturients with up to 5-year follow-up postpartum. Data were extracted from the computerized laboratory system of Meuhedet, an Israeli HMO and cross-linked with the Israeli National Registry of Diabetes. Included were parturients with no prior diabetesand available oGTT values during pregnancy. Reactive hypoglycemia was defined as glucose levels lower than 60 mg/dL in at least one of 3 post-glucose load values in oGTT. The cohort was divided into 3 groups: normal glucose status, reactive hypoglycemia, and GDM. Maternal characteristics, laboratory data, and progression to T2D over 5 years were compared. Univariate and survival analyses assessed the adjusted hazard ratio for T2D, stratified by obesity Results: Among 14,122 parturients, 16.8% had reactive hypoglycemia, 71% had normal glucose status, and 12.2% had GDM. Adjusted for age, obesity, and hypertension, Parturients with reactive hypoglycemia had similar T2D risk compared to normal glucose status and a lower risk compared to GDM patients, regardless of obesity status. Conclusions: Reactive hypoglycemia during oGTT does not increase the risk of progressing to T2D.

Timing of gestational diabetes diagnosis and progression to type 2 Diabetes: A comparative analysis.

AIM: To evaluate and compare the risk of progressing to type 2 diabetes (T2DM) based on the timing of gestational diabetes (GDM) diagnosis during pregnancy. METHODS: Retrospective analysis of pregnant individuals with gestational diabetes and post-pregnancy follow up. Data sourced from Meuhedet HMO's computerized laboratory system, cross-tabulated with the Israeli National Diabetes Registry. The cohort was divided into normoglycemic, early GDM (diagnosed by fasting plasma glucose 92-125 mg/dL (5.1-6.9 mM) at < 15 weeks), 2nd trimester GDM (diagnosed at 24-28 weeks), and late GDM (diagnosed after 29 weeks). Statistics included univariate analysis followed by survival analysis. Risk was further analyzed for individuals by obesity status. RESULTS: 75,459 entered the analysis: 90 % normoglycemic, 7.9 % early GDM, 1.4 % 2nd trimester GDM, and 0.7 % late GDM. Median post-pregnancy follow-up time was 4.3 (IQR 3.3-5.1). 2nd trimester GDM showed the highest T2DM risk annually after pregnancy. Cox regression analysis, adjusted for confounders, revealed a significantly higher T2DM risk for 2nd-trimester GDM compared to early and late GDM. Late GDM did not confer additional significant T2DM risk. Stratification by obesity status highlighted that early GDM increased the risk of T2DM only in individuals without obesity. CONCLUSIONS: GDM diagnosis timing significantly impacts T2DM risk. 2nd trimester GDM carries the highest T2DM risk.

First-trimester fasting plasma glucose levels and progression to type 2 diabetes: A 5-year cohort study.

OBJECTIVE: Impaired fasting glucose is a prediabetic condition defined as glucose levels of 100-125 mg/dL and is considered a risk factor for type 2 diabetes. However, this definition does not confer to pregnancy. The significance of first-trimester fasting glucose and future progression to diabetes is not well defined. Therefore, we aimed to evaluate the progression to type 2 diabetes according to first- trimester fasting plasma glucose levels, as compared with gestational diabetes, a well-established risk factor for diabetes, in up to 5-year follow-up postpartum. METHODS: A retrospective analysis of 69 001 parturients, evaluating fasting plasma glucose levels measured during the first trimester. The primary outcome was the incidence of type 2 diabetes within 5 years post-delivery. Fasting plasma glucose levels were categorized in 10 mg/dL increments. Receiver operating characteristic-area under the curve (ROC-AUC) statistics and the Youden index were employed to identify the optimal fasting plasma glucose cutoff for progression to type 2 diabetes. Survival analysis was applied to calculate the adjusted hazard ratios (aHRs) for type 2 diabetes progression with further stratification to maternal obesity status. RESULTS: The identified fasting plasma glucose cutoff for progression to type 2 diabetes was 86.5 mg/dL. This cut-off demonstrated superior performance compared with gestational diabetes diagnosis. Stratification by maternal obesity revealed enhanced predictive capabilities for type 2 diabetes, particularly among patients without obesity. CONCLUSIONS: Increased first-trimester fasting plasma glucose levels are associated with progression to type 2 diabetes, at least as gestational diabetes. For patients without obesity, first-trimester fasting plasma glucose has a more pronounced impact on progression to diabetes.

Pregnancy Outcomes in Women with Poorly Controlled Pregestational Diabetes Mellitus.

BACKGROUND: The prevalence of pregestational diabetes mellitus (PGDM) in women of reproductive age has surged globally, contributing to increased rates of adverse pregnancy outcomes. Hemoglobin A1c (HbA1c) is a crucial marker for diagnosing and monitoring PGDM, with periconceptional levels influencing the risk of congenital anomalies and complications. OBJECTIVES: To evaluate the association between periconceptional HbA1c levels and perinatal complications in pregnant women with poorly controlled PGDM. METHODS: We conducted a retrospective analysis of prospectively collected data of pregnancies between 2010 and 2019, HbA1c > 6% at 3 months prior to conception or during the first trimester. Outcomes of periconceptional HbA1c levels were compared. RESULTS: The cohort included 89 women: 49 with HbA1c 6-8%, 29 with HbA1c 8-10%, and 11 with HbA1c > 10%. Higher HbA1c levels were more prevalent in type 1 diabetics and were associated with increased end-organ damage risk. Women with elevated HbA1c levels tended toward unbalanced glucose levels during pregnancy. The cohort exhibited high rates of preterm delivery, hypertensive disorders, cesarean delivery, and neonatal intensive care unit admission. Overall live birth rate was 83%. While a significant correlation was found between HbA1c levels and preterm delivery, no consistent association was observed with other adverse outcomes. CONCLUSIONS: Periconceptional glycemic control in PGDM pregnancies is important. Elevated HbA1c levels are associated with increased risks of adverse outcomes. Beyond a certain HbA1c level, risks of complications may not proportionally escalate.

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.

When all computers shut down: the clinical impact of a major cyber-attack on a general hospital.

Importance: Healthcare organizations operate in a data-rich environment and depend on digital computerized systems; thus, they may be exposed to cyber threats. Indeed, one of the most vulnerable sectors to hacks and malware is healthcare. However, the impact of cyberattacks on healthcare organizations remains under-investigated. Objective: This study aims to describe a major attack on an entire medical center that resulted in a complete shutdown of all computer systems and to identify the critical actions required to resume regular operations. Setting: This study was conducted on a public, general, and acute care referral university teaching hospital. Methods: We report the different recovery measures on various hospital clinical activities and their impact on clinical work. Results: The system malfunction of hospital computers did not reduce the number of heart catheterizations, births, or outpatient clinic visits. However, a sharp drop in surgical activities, emergency room visits, and total hospital occupancy was observed immediately and during the first postattack week. A gradual increase in all clinical activities was detected starting in the second week after the attack, with a significant increase of 30% associated with the restoration of the electronic medical records (EMR) and laboratory module and a 50% increase associated with the return of the imaging module archiving. One limitation of the present study is that, due to its retrospective design, there were no data regarding the number of elective internal care hospitalizations that were considered crucial. Conclusions and relevance: The risk of ransomware cyberattacks is growing. Healthcare systems at all levels of the hospital should be aware of this threat and implement protocols should this catastrophic event occur. Careful evaluation of steady computer system recovery weekly enables vital hospital function, even under a major cyberattack. The restoration of EMR, laboratory systems, and imaging archiving modules was found to be the most significant factor that allowed the return to normal clinical hospital work.

Greater risk of type 2 diabetes progression in multifetal gestations with gestational diabetes: the impact of obesity.

BACKGROUND: The relationship between gestational diabetes mellitus and adverse outcomes in multifetal pregnancies is complex and controversial. Moreover, limited research has focused on the risk of gestational diabetes mellitus progression to type 2 diabetes mellitus specifically in multifetal pregnancies, resulting in conflicting results from existing studies. OBJECTIVE: This study aimed to assess the risk of gestational diabetes mellitus progression to type 2 diabetes mellitus between singleton and multifetal pregnancies in a large cohort of parturients with a 5-year follow-up. STUDY DESIGN: A retrospective study was conducted on a prospective cohort of pregnant individuals with pregnancies between January 1, 2017, and December 31, 2020, followed up to 5 years after delivery. Glucose levels during pregnancy were obtained from the Meuhedet Health Maintenance Organization laboratory system and cross-linked with the Israeli National Diabetes Registry. The cohort was divided into 4 groups: singleton pregnancy without gestational diabetes mellitus, singleton pregnancy with gestational diabetes mellitus, multifetal pregnancy without gestational diabetes mellitus, and multifetal pregnancy with gestational diabetes mellitus. Gestational diabetes mellitus was defined according to the American Diabetes Association criteria using the 2-step strategy. Univariate analyses, followed by survival analysis that included Kaplan-Meier hazard curves and Cox proportional-hazards models, were used to assess differences between groups and calculate the adjusted hazard ratios with 95% confidence intervals for progression to type 2 diabetes mellitus. RESULTS: Among 88,611 parturients, 61,891 cases met the inclusion criteria. The prevalence of type 2 diabetes mellitus was 6.5% in the singleton pregnancy with gestational diabetes mellitus group and 9.4% in the multifetal pregnancy with gestational diabetes mellitus group. Parturients with gestational diabetes mellitus, regardless of plurality, were older and had higher fasting plasma glucose levels in the first trimester of pregnancy. The rates of increased body mass index, hypertension, and earlier gestational age at delivery were significantly higher in the gestational diabetes mellitus group among patients with singleton pregnancies but not among patients with multifetal pregnancies. Survival analysis demonstrated that gestational diabetes mellitus was associated with adjusted hazard ratios of type 2 diabetes mellitus of 4.62 (95% confidence interval, 3.69-5.78) in singleton pregnancies and 9.26 (95% confidence interval, 2.67-32.01) in multifetal pregnancies (P<.001 for both). Stratified analysis based on obesity status revealed that, in parturients without obesity, gestational diabetes mellitus in singleton pregnancies increased the risk of type 2 diabetes mellitus by 10.24 (95% confidence interval, 6.79-15.44; P<.001) compared with a nonsignificant risk in multifetal pregnancies (adjusted hazard ratio, 9.15; 95% confidence interval, 0.92-90.22; P=.059). Among parturients with obesity, gestational diabetes mellitus was associated with an increased risk of type 2 diabetes mellitus for both singleton and multifetal pregnancies (adjusted hazard ratio, 3.66; [95% confidence interval, 2.81-4.67; P<.001] and 9.31 [95% confidence interval, 2.12-40.76; P=.003], respectively). CONCLUSION: Compared with gestational diabetes mellitus in singleton pregnancies, gestational diabetes mellitus in multifetal pregnancies doubles the risk of progression to type 2 diabetes mellitus. This effect is primarily observed in patients with obesity. Our findings underscore the importance of providing special attention and postpartum follow-up for patients with multifetal pregnancies and gestational diabetes mellitus, especially those with obesity, to enable early diagnosis and intervention for type 2 diabetes mellitus.

Same disease - different effect: maternal diabetes impact on birth weight stratified by fetal sex.

BACKGROUND: Male-sex is an independent risk factor for adverse perinatal outcomes. One example is gestational diabetes mellitus (GDM), which is associated with large gestational age neonates. It was previously described that fetal glucose metabolism is affected by fetal sex. PURPOSE: To examine whether the birth weight of neonates is affected differently by GDM according to fetal sex. METHODS: A retrospective normalized cohort analysis, using the open database of 2017 Natality Data from the National Vital Statistics System in the US. We compared the delta in neonatal birth weight, according to fetal sex, between pregnancies with or without GDM. Linear regression was used to take into consideration the effect of multiple confounders. For evaluation whether fetal sex is an independent risk factor for macrosomia (> 4000 and > 4500 g) following pregnancies complicated by GDM we used multivariate logistic regression. RESULTS: A significant relationship was found between the sex of the neonate and the delta in birth weight associated with GDM (P-value < 0.0001). The average weight gain in neonates to GDM pregnancies was 71 g in females, and 56 g in males. The prevalence of macrosomia above 4000 g and 4500 g that was attributed to GDM was higher in female-sex neonates compared to male-sex neonates (P < 0.05). CONCLUSION: According to our study results, female sex is associated with higher fetal weight gain in pregnancies complicated by GDM. Moreover, macrosomia's rate (> 4000 g and > 4500 g) attributed to GDM raised in a more significant manner in female-sex neonates.

Factors Associated with Progression to Preeclampsia with Severe Features in Pregnancies Complicated by Mild Hypertensive Disorders.

In this retrospective cohort study, we aimed to investigate the variables associated with progression to preeclampsia with severe features in parturients already diagnosed with mild hypertensive disorders of pregnancy. The study was conducted in a single university-affiliated medical center between 2018 and 2020. All women admitted due to hypertensive disorders were included. Data collected was compared between parturients who progressed and did not progress to preeclampsia with severe features. Among 359 women presenting without severe features, 18 (5%) developed severe features, delivered smaller babies at lower gestational age, and with higher rates of cesarean delivery (p < 0.001 for all). Chronic hypertension, maternal diabetes, any previous gestational hypertensive disorder, gestational diabetes, number of hospitalizations, earlier gestational age at initial presentation, and superimposed preeclampsia as the preliminary diagnosis were all associated with preeclampsia progression to severe features. Previous delivery within 2-5 years was a protective variable from preeclampsia progression. Following regression analysis and adjustment to confounders, only gestational age at initial presentation and superimposed preeclampsia remained significant variables associated with progression to severe features (aOR 0.74 (0.55-0.96) and 34.44 (1.07-1111.85), aOR (95% CI), respectively, p < 0.05 for both) with combined ROC-AUC prediction performance of 0.89, 95% CI 0.83-0.95, p < 0.001. In conclusion, according to our study results, early gestational age at presentation and superimposed preeclampsia as the preliminary diagnosis are the only independent factors that are associated with progression to severe features in women already diagnosed with mild hypertensive disorders during pregnancy.

Oral Glucose Tolerance Test Performed after 28 Gestational Weeks and Risk for Future Diabetes-A 5-Year Cohort Study.

Gestational diabetes mellitus (GDM) is diagnosed by an oral glucose tolerance test (oGTT), preferably performed at 24 + 0-28 + 6 gestational weeks, and is considered a risk factor for type 2 diabetes (T2DM). In this study, we aimed to evaluate the risk of T2DM associated with abnormal oGTT performed after 28 weeks. We conducted a retrospective cohort study that included parturients with available glucose levels during pregnancy and up to 5 years of follow-up after pregnancy. Data were extracted from the computerized laboratory system of Meuhedet HMO and cross-tabulated with the Israeli National Registry of Diabetes (INRD). The women were stratified into two groups: late oGTT (performed after 28 + 6 weeks) and on-time oGTT (performed at 24 + 0-28 + 6 weeks). The incidence of T2DM was evaluated and compared using univariate analysis followed by survival analysis adjusted to confounders. Overall, 78,326 parturients entered the analysis. Of them, 6195 (7.9%) performed on-time oGTT and 5288 (6.8%) performed late oGTT. The rest-66,846 (85.3%)-had normal glucose tolerance. Women who performed late oGTT had lower rates of GDM and T2DM. However, once GDM was diagnosed, regardless of oGTT timing, the risk of T2DM was increased (2.93 (1.69-5.1) vs. 3.64 (2.44-5.44), aHR (95% CI), late vs. on-time oGTT, p < 0.001 for both). Unlike in oGTT performed on time, one single abnormal value in late oGTT was not associated with an increased risk for T2DM.

Postpartum post-traumatic stress symptoms during the COVID-19 period: exposure and fear as mediating factors.

Background: Post-traumatic stress symptoms (PTSS) following childbirth are common within a stressful environment and are mitigated by social support. During the COVID-19 pandemic, an increase in such symptoms has been reported. The current study aims to longitudinally model the influence of general and pandemic-specific risk and protective factors on the temporal unfolding of symptoms among postpartum women.Methods: Participants were 226 women following a liveborn, term birth during the first lockdown in Israel. Participants completed questionnaires 10 weeks (T1) and 6 months (T2) after delivery. PATH analyses included predictors of symptoms in T1: demographics, exposure to traumatic events, medical complications during delivery or pregnancy, exposure to COVID-19-related events and their subjective impact, fear of COVID-19, and social support. Predictors of symptoms in T2 were: T1 predictors, both as direct effects and mediated by T1 PTSS, as well as predictors measured again in T2.Results: Results showed the suggested model fit the data. The effect of COVID-19-related fear and subjective impact at T1 on symptoms at T2 were fully mediated by PTSS in T1, as were the effects of marriage and high social support at T1. COVID-19-related fear at T2 positively predicted symptoms at T2, while social support at T2 had the opposite effect. Medical complications during pregnancy negatively predicted symptoms in T2 only.Discussion: Persistent fear appears to be a risk factor and supports a consistent buffer in postpartum PTSS during the COVID-19 pandemic. Medical complications during pregnancy served as a protective factor, possibly due to habituation to medical settings.

Post-traumatic stress symptoms (PTSS) following childbirth during the COVID-19 pandemic may unfold in a unique manner, relating to pandemic-related stressors and fears.Women who experience stressful pandemic-related events are not at heightened risk of developing PTSS within the six months following birth, but those reporting COVID-19 related fears are.Women who had medical complications during pregnancy, but not delivery, are at lower risk of developing subsequent PTSS, perhaps due to their ongoing contact with medical facilities despite the pandemic.

The Accuracy of Sonographically Estimated Fetal Weight and Prediction of Small for Gestational Age in Twin Pregnancy-Comparison of the First and Second Twins.

Accurate sonographic estimation of fetal weight is essential for every pregnancy, especially in twin gestation. We conducted a retrospective analysis of the sonographically estimated fetal weight (sEFW) of all twin gestations performed within 14 days of delivery in a single center that aimed to evaluate the accuracy of sEFW in predicting neonatal weight and small for gestational age (SGA) by comparing the first fetus to the second. A total of 190 twin gestations were evaluated for the study. There was no statistically significant difference in the sEFW between the first and the second twins, but the second twin had a statistically significant lower birth weight (2434 vs. 2351 g, p = 0.028). No difference was found in median absolute systematic error (p = 0.450), random error, or sEFW evaluations that were within 10% of the birth weight between the fetuses (65.3% vs. 67.9%, p = 0.587). Reliability analysis demonstrated an excellent correlation between the sEFW and the birth weight for both twins; however, the Euclidean distance was slightly higher for the first twin (12.21%). For SGA prediction, overall, there was a low sensitivity and a high specificity for all fetuses, with almost no difference between the first and second twins. We found that sEFW overestimated the birth weight for the second twin, with almost no other difference in accuracy measures or SGA prediction.

Unintended uterine extension at the time of cesarean delivery - risk factors and associated adverse maternal and neonatal outcomes.

OBJECTIVE: To identify risk factors, maternal and neonatal adverse outcomes related to unintended lower segment uterine extension during cesarean delivery (CD). METHODS: A retrospective cohort analysis in a single, university-affiliated medical center between 1 January 2018 and 31 December 2019. All singleton pregnancies delivered by CD were included. Univariate and multivariate analyses were performed to identify maternal and obstetrical predictors for uterine extension during CD. For secondary outcomes, we assessed the correlation between uterine extension and any adverse maternal or neonatal outcome. Risk factors were analyzed using ROC statistics to measure their prediction performance for a uterine extension. RESULTS: Overall, 1746 (19.3%) CDs were performed during the study period. Of them, 121 (6.9%) CDs were complicated by unintended uterine extension. There was no difference in maternal demographics and clinical data stratified by uterine extension at CD. Uterine extensions were significantly more common following induction of labor, intrapartum fever, premature rupture of membranes, a trial of labor after cesarean, advanced gestational age, emergent CD, and in particular CD during the second stage of labor (37.2% vs. 6.5%) and after failed vacuum extraction (6.6% vs. 1.1%), p < .05 for all. The incidence of postpartum hemorrhage and re-laparotomy did not differ between the groups. Most of the extensions were caudal-directed (40.4%), and were closed by a two-layer closure (92%). Mean extension size was 4.5 ± 1.7 cm. Using multivariable analysis, the only factor that remained significant was CD at the second stage of labor (adjusted odds ratio (aOR) 54.2, 95% CI 4.5-648.9, p = .002), with an area under the ROC curve 0.653 (95% CI 0.595-0.712, p < .001). Emergent CD, body mass index, birth weight, failed vacuum attempt, and trial of labor after cesarean were not significant. For secondary outcomes, an unintended uterine extension was associated with longer operation time, higher estimated blood loss, greater pre- to post-CD hemoglobin difference, increased blood products transfusion, puerperal fever, and longer hospital stay. No clinically significant neonatal adverse outcomes were observed. CONCLUSIONS: In our cohort, second-stage CD was the strongest predictor for an unintended uterine extension. Following uterine extension, women had increased infectious and blood-loss morbidity.

Single Sporadic Deceleration during Reactive Nonstress Test-Clinical Significance and Risk for Cesarean Delivery.

OBJECTIVE: Evidence regarding the clinical significance of a single sporadic variable deceleration (SSD) in reactive non-stress test (NST) is scarce, and optimal management has yet to be established. We aim to evaluate whether SSD during a reactive NST at term is associated with a higher risk for fetal heart rate decelerations during labor and the need for intervention. METHODS: This was a retrospective, case-control study of singleton term pregnancies at one university-affiliated medical center in 2018. The study group consisted of all pregnancies with an SSD in an otherwise reactive NST. For each case, two consecutive pregnancies without SSD were matched in a 1:2 ratio. The primary outcome was the rate of cesarean delivery (CD) due to non-reassuring fetal heart rate monitoring (NRFHRM). RESULTS: 84 women with an SSD were compared to 168 controls. SSD during antenatal fetal surveillance did not increase the rate of CD overall or for NRFHRM (17.9% vs. 13.7% and 10.7% vs. 7.7%, respectively, p > 0.05). Rates of assisted deliveries and maternal and neonatal complications were similar between the groups. CONCLUSIONS: SSD during a reactive NST in term pregnancies is not associated with an increased risk for adverse perinatal outcomes. SSD should not necessarily require induction of labor, and expectant management is a reasonable alternative.

When the lights go down in the delivery room: Lessons from a ransomware attack.

OBJECTIVE: To describe the challenges facing the obstetric division following a cyberattack and discuss ways of preparing for and overcoming another one. METHODS: A retrospective descriptive study conducted in a mid-sized medical center. Division activities, including the number of deliveries, cesarean sections, emergency room visits, admissions, maternal-fetal medicine department occupancy, and ambulatory encounters, from 2 weeks before the attack to 8 weeks following it (a total of 11 weeks), were compared with the retrospective period in 2019 (pre-COVID-19). In addition, we present the challenges and adaptation measures taken at the division and hospital levels leading up to the resumption of full division activity. RESULTS: On the day of the cyberattack, critical decisions were made. The media announced the event, calling on patients not to come to our hospital. Also, all elective activities other than cesarean deliveries were stopped. The number of deliveries, admissions, and both emergency room and ambulatory clinic visits decreased by 5%-10% overall for 11 weeks, reflecting the decrease in division activity. Nevertheless, in all stations, there were sufficient activities and adaptation measures to ensure patient safety, decision-making, and workflow of patients were accounted for. CONCLUSIONS: The risk of ransomware cyberattacks is growing. Healthcare systems at all levels should recognize this threat and have protocols for dealing with them once they occur.

External validation of vaginal birth after cesarean delivery calculator in Israeli cohort of parturients and construction of an improved model.

OBJECTIVE: To validate the Maternal Fetal Medicine Unit's (MFMU) vaginal birth after cesarean delivery (VBAC) calculator in an Israeli cohort, and to detect other variables associated with VBAC and construct an improved VBAC calculator. METHODS: A retrospective cohort study was performed at a single university-affiliated medical center. Women carrying a singleton, term, cephalic-presenting fetus, with previous one low transverse cesarean delivery who opted for trial of VBAC were included. Demographic and obstetric characteristics were incorporated into the MFMU's calculator, to predict probabilities of VBAC and compare prediction performance with the original publication utilizing receiver operating characteristic (ROC) statistics. Logistic regression analysis was used to investigate other variables and construct an improved model for success of VBAC. RESULTS: Of 490 parturients, 396 (80.8%) had a successful vaginal delivery. Compared to the original publication, the MFMU's calculator underperformed: area under the ROC curve (AUC) was 0.709 (95% confidence interval [CI] 0.652-0.766, P < 0.001). Sensitivity, specificity, positive and negative predictive values, and overall accuracy were 67.42%, 65.96%, 89.30%, 32.46%, and 32.46%, respectively. An improved model that included previous VBAC, prior vaginal delivery, spontaneous onset of delivery, and maternal diabetes resulted in improved prediction performance with an AUC of 0.771 (95% CI 0.723-0.82, P < 0.001). CONCLUSION: MFMU's VBAC calculator needs to be validated in different populations before implementation.