{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,11]],"date-time":"2026-10-11T17:52:31Z","timestamp":1791741151679,"version":"4.3.4"},"reference-count":60,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T00:00:00Z","timestamp":1643673600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["obgyn.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Ultrasound in Obstet &amp; Gyne"],"published-print":{"date-parts":[[2022,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>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\u2010analysis to assess their predictive performance.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>MEDLINE, EMBASE, DH\u2010DATA 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 <jats:italic>C<\/jats:italic>\u2010statistic, and calibration was assessed using calibration plots, calibration slope and calibration\u2010in\u2010the\u2010large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random\u2010effects meta\u2010analysis. Clinical utility was assessed using net benefit.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>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\u2010fifth (20%, 8\/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491\u2009201 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\u2010analysis, the models had summary <jats:italic>C<\/jats:italic>\u2010statistics 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>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. \u00a9 2021 The Authors. Ultrasound in Obstetrics &amp; Gynecology published by John Wiley &amp; Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.<\/jats:p><\/jats:sec>","DOI":"10.1002\/uog.23757","type":"journal-article","created":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T11:21:20Z","timestamp":1629285680000},"page":"209-219","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications (<scp>IPPIC<\/scp>) Network database: individual participant data meta\u2010analysis"],"prefix":"10.1002","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4134-6246","authenticated-orcid":false,"given":"J.","family":"Allotey","sequence":"first","affiliation":[{"name":"WHO Collaborating Centre for Global Women's Health, Institute of Metabolism and Systems Research University of Birmingham  Birmingham UK"},{"name":"Institute of Applied Health Research University of Birmingham  Birmingham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R.","family":"Whittle","sequence":"additional","affiliation":[{"name":"Centre for Prognosis Research, School of Medicine Keele University  Keele UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"K. 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E. P.","family":"Heazell","sequence":"additional","affiliation":[{"name":"Maternal and Fetal Health Research Centre, School of Medical Sciences, Faculty of Biology, Medicine and Health University of Manchester  Manchester UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"L.","family":"Magee","sequence":"additional","affiliation":[{"name":"Department of Women and Children's Health, School of Life Course Sciences King's College London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G. C. S.","family":"Smith","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynaecology, NIHR Biomedical Research Centre Cambridge University, Cambridge  UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J.","family":"Sandall","sequence":"additional","affiliation":[{"name":"Department of Women and Children's Health, School of Life Course Sciences King's College London  London UK"},{"name":"Health Service and Population Research Department, Centre for Implementation Science, Institute of Psychiatry, Psychology and Neuroscience King's College London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5531-4301","authenticated-orcid":false,"given":"B.","family":"Thilaganathan","sequence":"additional","affiliation":[{"name":"Fetal Medicine Unit, St George's University Hospitals NHS Foundation Trust University of London  London UK"},{"name":"Vascular Biology Research Centre, Molecular and Clinical Sciences Research Institute St George's University of London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J.","family":"Zamora","sequence":"additional","affiliation":[{"name":"WHO Collaborating Centre for Global Women's Health, Institute of Metabolism and Systems Research University of Birmingham  Birmingham UK"},{"name":"Clinical Biostatistics Unit Hospital Universitario Ram\u00f3n y Cajal (IRYCIS)  Madrid Spain"},{"name":"CIBER Epidemiology and Public Health (CIBERESP)  Madrid Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R. 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