Weight discordance and perinatal mortality in twin pregnancy: systematic review and meta‐analysis

Objectives The primary aim of this systematic review was to explore the strength of association between birth‐weight (BW) discordance and perinatal mortality in twin pregnancy. The secondary aim was to ascertain the contribution of gestational age and growth restriction in predicting mortality in growth‐discordant twins. Methods MEDLINE, EMBASE, CINAHL and ClinicalTrials.gov databases were searched. Only studies reporting on the risk of mortality in twin pregnancies affected compared with those not affected by BW discordance were included. The primary outcomes explored were incidence of intrauterine death (IUD), neonatal death (NND) and perinatal death. Outcome was assessed separately for monochorionic (MC) and dichorionic (DC) twin pregnancies. Analyses were stratified according to BW discordance cut‐off (≥ 15%, ≥ 20%, ≥ 25% and ≥ 30%) and selected gestational characteristics, including incidence of IUD or NND before and after 34 weeks' gestation, presence of at least one small‐for‐gestational age (SGA) fetus in the twin pair and both twins being appropriate‐for‐gestational age. Risk of mortality in the larger vs smaller twin was also assessed. Meta‐analyses using individual data random‐effects logistic regression and meta‐analyses of proportion were used to analyze the data. Results Twenty‐two studies (10 877 twin pregnancies) were included in the analysis. In DC pregnancies, a higher risk of IUD, but not of NND, was observed in twins with BW discordance ≥ 15% (odds ratio (OR) 9.8, 95% CI, 3.9–29.4), ≥ 20% (OR 7.0, 95% CI, 4.15–11.8), ≥ 25% (OR 17.4, 95% CI, 8.3–36.7) and ≥ 30% (OR 22.9, 95% CI, 10.2–51.6) compared with those without weight discordance. For each cut‐off of BW discordance explored in DC pregnancies, the smaller twin was at higher risk of mortality compared with the larger one. In MC twin pregnancies, excluding cases affected by twin–twin transfusion syndrome, twins with BW discordance ≥ 20% (OR 2.8, 95% CI, 1.3–5.8) or ≥ 25% (OR 3.2, 95% CI, 1.5–6.7) were at higher risk of IUD, compared with controls. MC pregnancies with ≥ 25% weight discordance were also at increased risk of NND (OR 4.66, 95% CI, 1.8–12.4) compared with those with concordant weight. The risk of IUD was higher when considering discordant pregnancies involving at least one SGA fetus. The overall risk of mortality in MC pregnancies was similar between the smaller and larger twin, except in those with BW discordance ≥ 20%. Conclusion DC and MC twin pregnancies discordant for fetal growth are at higher risk of IUD but not of NND compared with pregnancies with concordant BW. The risk of IUD in BW‐discordant DC and MC twins is higher when at least one fetus is SGA

ISUOG Practice Guidelines: role of ultrasound in screening for and follow-up of pre-eclampsia.

Hypertensive disease of pregnancy affects up to 10% of pregnant women1 and the pooled global incidence of pre-eclampsia (PE) is approximately 3%2. Significant variations between developed and developing countries can be attributed to true differences or differences arising from data acquisition. PE and its complications are a major contributor to maternal and perinatal morbidity and mortality worldwide1, 3. Given that timely and effective care can improve the outcome of PE3, the development of effective prediction and prevention strategies has been a major objective of prenatal care and of research.Full Tex

Second trimester inflammatory and metabolic markers in women delivering preterm with and without preeclampsia.

ObjectiveInflammatory and metabolic pathways are implicated in preterm birth and preeclampsia. However, studies rarely compare second trimester inflammatory and metabolic markers between women who deliver preterm with and without preeclampsia.Study designA sample of 129 women (43 with preeclampsia) with preterm delivery was obtained from an existing population-based birth cohort. Banked second trimester serum samples were assayed for 267 inflammatory and metabolic markers. Backwards-stepwise logistic regression models were used to calculate odds ratios.ResultsHigher 5-α-pregnan-3β,20α-diol disulfate, and lower 1-linoleoylglycerophosphoethanolamine and octadecanedioate, predicted increased odds of preeclampsia.ConclusionsAmong women with preterm births, those who developed preeclampsia differed with respect metabolic markers. These findings point to potential etiologic underpinnings for preeclampsia as a precursor to preterm birth

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

Serum screening with Down's syndrome markers to predict pre-eclampsia and small for gestational age: Systematic review and meta-analysis

<p>Abstract</p> <p>Background</p> <p>Reliable antenatal identification of pre-eclampsia and small for gestational age is crucial to judicious allocation of monitoring resources and use of preventative treatment with the prospect of improving maternal/perinatal outcome. The purpose of this systematic review was to determine the accuracy of five serum analytes used in Down's serum screening for prediction of pre-eclampsia and/or small for gestational age.</p> <p>Methods</p> <p>The data sources included Medline, Embase, Cochrane library, Medion (inception to February 2007), hand searching of relevant journals, reference list checking of included articles, contact with experts. Two reviewers independently selected the articles in which the accuracy of an analyte used in Downs's serum screening before the 25^thgestational week was associated with the occurrence of pre-eclampsia and/or small for gestational age without language restrictions. Two authors independently extracted data on study characteristics, quality and results.</p> <p>Results</p> <p>Five serum screening markers were evaluated. 44 studies, testing 169,637 pregnant women (4376 pre-eclampsia cases) and 86 studies, testing 382,005 women (20,339 fetal growth restriction cases) met the selection criteria. The results showed low predictive accuracy overall. For pre-eclampsia the best predictor was inhibin A>2.79MoM positive likelihood ratio 19.52 (8.33,45.79) and negative likelihood ratio 0.30 (0.13,0.68) (single study). For small for gestational age it was AFP>2.0MoM to predict birth weight < 10^thcentile with birth < 37 weeks positive likelihood ratio 27.96 (8.02,97.48) and negative likelihood ratio 0.78 (0.55,1.11) (single study). A potential clinical application using aspirin as a treatment is given as an example.</p> <p>There were methodological and reporting limitations in the included studies thus studies were heterogeneous giving pooled results with wide confidence intervals.</p> <p>Conclusion</p> <p>Down's serum screening analytes have low predictive accuracy for pre-eclampsia and small for gestational age. They may be a useful means of risk assessment or of use in prediction when combined with other tests.</p

Predicting stillbirth in a low resource setting

BACKGROUND: Stillbirth is a major contributor to perinatal mortality and it is particularly common in low- and middle-income countries, where annually about three million stillbirths occur in the third trimester. This study aims to develop a prediction model for early detection of pregnancies at high risk of stillbirth. METHODS: This retrospective cohort study examined 6,573 pregnant women who delivered at Federal Medical Centre Bida, a tertiary level of healthcare in Nigeria from January 2010 to December 2013. Descriptive statistics were performed and missing data imputed. Multivariable logistic regression was applied to examine the associations between selected candidate predictors and stillbirth. Discrimination and calibration were used to assess the model's performance. The prediction model was validated internally and over-optimism was corrected. RESULTS: We developed a prediction model for stillbirth that comprised maternal comorbidity, place of residence, maternal occupation, parity, bleeding in pregnancy, and fetal presentation. As a secondary analysis, we extended the model by including fetal growth rate as a predictor, to examine how beneficial ultrasound parameters would be for the predictive performance of the model. After internal validation, both calibration and discriminative performance of both the basic and extended model were excellent (i.e. C-statistic basic model = 0.80 (95 % CI 0.78-0.83) and extended model = 0.82 (95 % CI 0.80-0.83)). CONCLUSION: We developed a simple but informative prediction model for early detection of pregnancies with a high risk of stillbirth for early intervention in a low resource setting. Future research should focus on external validation of the performance of this promising model