Prediction of Stillbirth: An Umbrella Review of Evaluation of Prognostic Variables

Townsend, Rosemary; Sileo, Filomena Giulia; Allotey, John; Dodds, Jodi; Heazell, Alexander; Jørgensen, Lars N.; Kim, V. B.; Magee, Laura A.; Mol, Ben W.; Sandall, Jane; Smith, Gordon C. S.; Thilaganathan, B.; Vondadelszen, P; Thangaratinam, Shakila; Khalil, A.

doi:10.1097/ogx.0000000000000937

Cited by 10 publications

(24 citation statements)

References 37 publications

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“…25 The study reported that no marker had useful screening performance, but maternal age, body mass index and history of previous adverse pregnancy outcomes had a more convincing association than the best performing tests, which were PAPP-A, placental growth factor and UtA-PI. 25 Such types of publications that do not recognise the fact that the causes of stillbirth are heterogeneous could not advance the development of strategies for prediction and prevention of stillbirth.…”

Section: Comparison With Results Of Previous Studiesmentioning

confidence: 98%

“…In a series of previous first‐ and second‐trimester studies for the prediction of stillbirth we highlighted that the causes of this adverse event are heterogeneous and that the focus of research should be placental dysfunction related stillbirths because they are relatively common and, to a great extent, potentially preventable 19–24 . However, a systematic review of 69 previous systematic reviews that aimed to identify variables that could be relevant to the development of a clinical prediction model for stillbirth treated this adverse event as a homogeneous condition 25 . The study reported that no marker had useful screening performance, but maternal age, body mass index and history of previous adverse pregnancy outcomes had a more convincing association than the best performing tests, which were PAPP‐A, placental growth factor and UtA‐PI 25 .…”

Section: Discussionmentioning

confidence: 99%

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Predictive performance for placental dysfunction related stillbirth of the competing risks model for small‐for‐gestational‐age fetuses

Nicolaides

Papastefanou

Syngelaki

et al. 2022

BJOG

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Objectives: To examine the predictive performance for placental dysfunction related stillbirths of the competing risks model for small-for-gestational-age (SGA) fetuses based on a combination of maternal risk factors, estimated fetal weight (EFW) and uterine artery pulsatility index (UtA-PI); and second, to compare the performance of this model with that of a stillbirth-specific model using the same biomarkers and with the Royal College of Obstetricians and Gynecologists (RCOG) guideline for the investigation and management of the SGA fetus.Design: Prospective observational study. Setting: Two UK maternity hospitals.Population: A total of 131 514 women with singleton pregnancies attending for routine ultrasound examination at 19-24 weeks of gestation. Methods:The predictive performance for stillbirth achieved by three models was compared.Main Outcome Measure: Placental dysfunction related stillbirth.Results: At 10% false-positive rate, the competing risks model predicted 59%, 66% and 71% of placental dysfunction related stillbirths, at any gestation, at <37 weeks and at <32 weeks, respectively, which were similar to the respective figures of 62%, 70% and 73% for the stillbirth-specific model. At a screen positive rate of 21.8%, as defined by the RCOG guideline, the competing risks model predicted 71%, 76% and 79% of placental dysfunction related stillbirths at any gestation, at <37 weeks and at <32 weeks, respectively, and the respective figures for the RCOG guideline were 40%, 44% and 42%. Conclusion:The predictive performance for placental dysfunction related stillbirths by the competing risks model for SGA was similar to that of the stillbirth-specific model and superior to that of the RCOG guideline.

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Section: Comparison With Results Of Previous Studiesmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Predictive performance for placental dysfunction related stillbirth of the competing risks model for small‐for‐gestational‐age fetuses

Nicolaides

Papastefanou

Syngelaki

et al. 2022

BJOG

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Section: Recommendations For Further Researchmentioning

confidence: 99%

“…Systematic reviews using aggregate data meta-analysis currently represent the best available evidence on predictors of stillbirth and have proposed several risk factors to categorize women as high risk 41 . However, they are limited by heterogeneity among the primary studies, such as in the definition of stillbirth 41 . Existing primary studies are often small, with imprecise estimates and are inconsistent in the confounding factors adjusted for in 28 (St George's dataset 42 ).…”

Section: Recommendations For Further Researchmentioning

confidence: 99%

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

Allotey

Whittle

Snell

et al. 2022

Ultrasound in Obstet & Gyne

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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. © 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gyne...

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“…27 Another limitation may be failure to control for other maternal co-morbidities known to be associated with stillbirth, such as sickle-cell disease or antiphospholipid syndrome, in the general population. 34 Although we observed a temporal reduction of nicotine consumption in the general population, which is known to be a very important measure in reducing stillbirth, 35 we acknowledge that smoking history TA B L E 2 Sample characteristics of the stillbirth cohort (N = 2579) in non-anomalous pregnancies ≥24 +0 gestational weeks before ("pre-GDM screening," i.e., January 2008 to December 2010) and after ("GDM screening," i.e., January 2011 to December 2019) implementation of the universal gestational diabetes screening program in Austria b Missing values N = 959. BMI categories: underweight (≤18.5 kg/m 2 ), normal (18.6-24.9 kg/m 2 ), pre-obesity (25.0-29.9 kg/m 2 ), obesity (≥30.0 kg/m 2 ).…”

Section: One Example Of Such Data Is the Midlands And North Of Englandmentioning

confidence: 99%

Universal gestational diabetes screening and antepartum stillbirth rates in Austria—A population‐based study

Muin

Pfeifer

Helmer

et al. 2022

Acta Obstet Gynecol Scand

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Introduction Occult or untreated gestational diabetes (GDM) is a well‐known risk factor for adverse perinatal outcomes and may contribute to antepartum stillbirth. We assessed the impact of screening for GDM on the rate of antepartum stillbirths in non‐anomalous pregnancies by conducting a population‐based study in 974 889 women in Austria. Material and Methods Our database was derived from the Austrian Birth Registry. Inclusion criteria were singleton live births and antepartum stillbirths ≥24+0 gestational weeks, excluding fetal congenital malformations, terminations of pregnancy and women with pre‐existing type 1 or 2 diabetes. Main outcome measures were (a) overall stillbirth rates and (b) stillbirth rates in women at high risk of GDM (i.e., women with a body mass index ≥30 kg/m2, history of previous intrauterine fetal death, GDM, previous macrosomic offspring) before (2008–2010, “phase I”) and after (2011–2019, “phase II”) the national implementation of universal GDM screening with a 75 g oral glucose tolerance test in Austrian pregnant women by 2011. Results In total, 940 373 pregnancies were included between 2008 and 2019, of which 2579 resulted in intrauterine fetal deaths at 33.51 ± 5.10 gestational weeks. After implementation of the GDM screening, a statistically significant reduction in antepartum stillbirth rates among non‐anomalous singletons was observed only in women at high risk for GDM (4.10‰ [95% confidence interval (CI) 3.09–5.43] in phase I vs. 2.96‰ [95% CI 2.57–3.41] in phase II; p = 0.043) but not in the general population (2.76‰ [95% CI 2.55–2.99] in phase I vs. 2.74‰ [95% CI 2.62–2.86] in phase II; p = 0.845). The number needed to screen with the oral glucose tolerance test to subsequently prevent one case of (non‐anomalous) intrauterine fetal death was 880 in the high‐risk and 40 000 in the general population. Conclusions The implementation of a universal GDM screening program in Austria in 2011 has not led to any significant reduction in antenatal stillbirths among non‐anomalous singletons in the general population. More international data are needed to strengthen our findings.

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Prediction of Stillbirth: An Umbrella Review of Evaluation of Prognostic Variables

Cited by 10 publications

References 37 publications

Predictive performance for placental dysfunction related stillbirth of the competing risks model for small‐for‐gestational‐age fetuses

Predictive performance for placental dysfunction related stillbirth of the competing risks model for small‐for‐gestational‐age fetuses

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

Universal gestational diabetes screening and antepartum stillbirth rates in Austria—A population‐based study

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