Vasoactive Intestinal Peptide and Its Receptors in Human Ovarian Cortical Follicles

BACKGROUND: Ovarian cryopreservation is one option for fertility preservation in patients with cancer. The danger of reseeding malignancies could be eliminated by in vitro maturation of primordial follicles from the frozen-thawed tissue. However, the development of this system is hindered by uncertainties regarding factors that activate primordial follicles. Neuronal growth factors such as vasoactive intestinal peptide (VIP) play important roles in early mammalian folliculogenesis. There are no data on the expression of VIP and its vasoactive intestinal peptide pituitary adenylate cyclase 1 and 2 receptors (VPAC1-R and VPAC2-R) in human preantral follicles. METHODOLOGY/PRINCIPAL FINDINGS: Tissue samples from 14 human fetal ovaries and 40 ovaries from girls/women were prepared to test for the expression of VIP, VPAC1-R, and VPAC2-R on the protein (immunohistochemisty) and mRNA (reverse transcription polymerase chain reaction) levels. Immunohistochemistry staining was mostly weak, especially in fetal samples. The VIP protein was identified in oocytes and granulosa cells (GCs) in the fetal samples from 22 gestational weeks (GW) onwards. In girls/women, VIP follicular staining (oocytes and GCs) was identified in 45% of samples. VPAC1-R protein was identified in follicles in all fetal samples from 22GW onwards and in 63% of the samples from girls/women (GC staining only in 40%). VPAC2-R protein was identified in follicles in 33% of fetal samples and 47% of the samples from girls/women. The mRNA transcripts for VIP, VPAC1-R, and VPAC2-R were identified in ovarian extracts from fetuses and women. CONCLUSIONS: VIP and its two receptors are expressed in human ovarian preantral follicles. However, their weak staining suggests they have limited roles in early follicular growth. To elucidate if VIP activates human primordial follicles, it should be added to the culture medium

Risk factor screening to identify women requiring oral glucose tolerance testing to diagnose gestational diabetes : a systematic review and meta-analysis and analysis of two pregnancy cohorts

BACKGROUND: Easily identifiable risk factors including: obesity and ethnicity at high risk of diabetes are commonly used to indicate which women should be offered the oral glucose tolerance test (OGTT) to diagnose gestational diabetes (GDM). Evidence regarding these risk factors is limited however. We conducted a systematic review (SR) and meta-analysis and individual participant data (IPD) analysis to evaluate the performance of risk factors in identifying women with GDM. METHODS: We searched MEDLINE, Medline in Process, Embase, Maternity and Infant Care and the Cochrane Central Register of Controlled Trials (CENTRAL) up to August 2016 and conducted additional reference checking. We included observational, cohort, case-control and cross-sectional studies reporting the performance characteristics of risk factors used to identify women at high risk of GDM. We had access to IPD from the Born in Bradford and Atlantic Diabetes in Pregnancy cohorts, all pregnant women in the two cohorts with data on risk factors and OGTT results were included. RESULTS: Twenty nine published studies with 211,698 women for the SR and a further 14,103 women from two birth cohorts (Born in Bradford and the Atlantic Diabetes in Pregnancy study) for the IPD analysis were included. Six studies assessed the screening performance of guidelines; six examined combinations of risk factors; eight evaluated the number of risk factors and nine examined prediction models or scores. Meta-analysis using data from published studies suggests that irrespective of the method used, risk factors do not identify women with GDM well. Using IPD and combining risk factors to produce the highest sensitivities, results in low specificities (and so higher false positives). Strategies that use the risk factors of age (>25 or >30) and BMI (>25 or 30) perform as well as other strategies with additional risk factors included. CONCLUSIONS: Risk factor screening methods are poor predictors of which pregnant women will be diagnosed with GDM. A simple approach of offering an OGTT to women 25 years or older and/or with a BMI of 25kg/m2 or more is as good as more complex risk prediction models. Research to identify more accurate (bio)markers is needed. Systematic Review Registration: PROSPERO CRD42013004608

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis

Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe

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

Acardiac twin pregnancies part II: Fetal risk of chorangioma and sacrococcygeal teratoma predicted by pump/acardiac umbilical vein diameters

We recently published pump/acardiac umbilical venous diameter (UVD) ratios, representing the pump twin's excess cardiac output fraction, of 27 acardiac twin pregnancies. There was a clear separation between the 17 pump twins that had life-threatening complications and the 10 that did not. The hypothesis of this study is that placental chorangioma and sacrococcygeal teratoma (SCT), tumors whose perfusion also causes high-output complications, have the same fetal outcome as pump twins when perfusion of the tumor requires the same excess cardiac output fraction. We compared the three fetoplacental circulations. Fetuses with a placental chorangioma and acardiac twin pregnancies both have their feeding artery and draining vein located at the placental cord insertion. In contrast, SCT lacks a prescribed feeding artery and draining vein. We, therefore, had to modify our model to assume that the diameter of the hypothetical draining vein is related to the flow difference between inferior vena cava and superior vena cava. The latter flow has been estimated sonographically and is the same as the inferior vena cava flow in the absence of an SCT. Furthermore, a simple modification accounts for the different location of the tumor with respect to the placental cord insertion. We propose to apply the clinical pump/acardiac UVD ratios to pregnancies complicated by placental chorangiomas and the modified pump/acardiac UVD ratios for SCT. Risk prediction of these rare fetal tumors may be possible based on application of data on excess cardiac output fractions from pump/acardiac UVD ratios and will require future clinical validation. Birth Defects Research (Part A) 106:733-738, 2016. © 2016 Wiley Periodicals, In