{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T12:48:14Z","timestamp":1793364494289,"version":"4.5.0"},"reference-count":97,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2024,5,2]],"date-time":"2024-05-02T00:00:00Z","timestamp":1714608000000},"content-version":"vor","delay-in-days":1,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["obgyn.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Ultrasound in Obstet &amp; Gyne"],"published-print":{"date-parts":[[2024,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This systematic review and meta\u2010analysis aimed to evaluate the performance of existing externally validated prediction models for pre\u2010eclampsia (PE) (specifically, any\u2010onset, early\u2010onset, late\u2010onset and preterm\u00a0PE).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A systematic search was conducted in five databases (MEDLINE, EMBASE, Emcare, CINAHL and Maternity\u2009&amp;\u2009Infant Care Database) and using Google Scholar\/reference search to identify studies based on the Population, Index prediction model, Comparator, Outcome, Timing and Setting (PICOTS) approach until 20 May 2023. We extracted data using the CHARMS checklist and appraised the risk of bias using the PROBAST tool. A meta\u2010analysis of discrimination and calibration performance was conducted when appropriate.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Twenty\u2010three studies reported 52 externally validated prediction models for PE (one preterm, 20 any\u2010onset, 17 early\u2010onset and 14 late\u2010onset PE models). No model had the same set of predictors. Fifteen any\u2010onset PE models were validated externally once, two were validated twice and three were validated three times, while the Fetal Medicine Foundation (FMF) competing\u2010risks model for preterm PE prediction was validated widely in 16 different settings. The most common predictors were maternal characteristics (prepregnancy body mass index, prior PE, family history of PE, chronic medical conditions and ethnicity) and biomarkers (uterine artery pulsatility index and pregnancy\u2010associated plasma protein\u2010A). The FMF model for preterm PE (triple test plus maternal factors) had the best performance, with a pooled area under the receiver\u2010operating\u2010characteristics curve (AUC) of 0.90 (95% prediction interval (PI), 0.76\u20130.96), and was well calibrated. The other models generally had poor\u2010to\u2010good discrimination performance (median AUC, 0.66 (range, 0.53\u20130.77)) and were overfitted on external validation. Apart from the FMF model, only two models that were validated multiple times for any\u2010onset PE prediction, which were based on maternal characteristics only, produced reasonable pooled AUCs of 0.71 (95%\u2009PI, 0.66\u20130.76) and 0.73 (95% PI, 0.55\u20130.86).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      Existing externally validated prediction models for any\u2010, early\u2010 and late\u2010onset PE have limited discrimination and calibration performance, and include inconsistent input variables. The triple\u2010test FMF model had outstanding discrimination performance in predicting preterm PE in numerous settings, but the inclusion of specialized biomarkers may limit feasibility and implementation outside of high\u2010resource settings. \u00a9 2023 The Authors.\n                      <jats:italic>Ultrasound in Obstetrics &amp; Gynecology<\/jats:italic>\n                      published by John Wiley &amp; Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/uog.27490","type":"journal-article","created":{"date-parts":[[2023,9,19]],"date-time":"2023-09-19T06:54:19Z","timestamp":1695106459000},"page":"592-604","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["Externally validated prediction models for pre\u2010eclampsia: systematic review and meta\u2010analysis"],"prefix":"10.1002","volume":"63","author":[{"given":"S. A.","family":"Tiruneh","sequence":"first","affiliation":[{"name":"Monash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences Monash University  Melbourne VIC Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C. T.","family":"Vu","sequence":"additional","affiliation":[{"name":"Monash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences Monash University  Melbourne VIC Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"L. J.","family":"Moran","sequence":"additional","affiliation":[{"name":"Monash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences Monash University  Melbourne VIC Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"E. J.","family":"Callander","sequence":"additional","affiliation":[{"name":"Monash Centre for Health Research and Implementation, Faculty of Medicine, Nursing and Health Sciences Monash University  Melbourne VIC Australia"},{"name":"School of Public Health, Faculty of Health University of Technology Sydney  Sydney NSW Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4134-6246","authenticated-orcid":false,"given":"J.","family":"Allotey","sequence":"additional","affiliation":[{"name":"World Health Organization (WHO) Collaborating Centre for Global Women's Health, Institute of Metabolism and Systems Research University of Birmingham  Birmingham UK"},{"name":"NIHR Birmingham Biomedical Research Centre University Hospitals Birmingham NHS Foundation Trust and University of Birmingham  Birmingham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S.","family":"Thangaratinam","sequence":"additional","affiliation":[{"name":"World Health Organization (WHO) Collaborating Centre for Global Women's Health, Institute of Metabolism and Systems Research University of Birmingham  Birmingham UK"},{"name":"NIHR Birmingham Biomedical Research Centre University Hospitals Birmingham NHS Foundation Trust and University of Birmingham  Birmingham UK"},{"name":"Birmingham Women's and Children's NHS Foundation Trust  Birmingham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"D. 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