{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T06:18:53Z","timestamp":1774505933668,"version":"3.50.1"},"reference-count":30,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2013,10,10]],"date-time":"2013-10-10T00:00:00Z","timestamp":1381363200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Paediatric Perinatal Epid"],"published-print":{"date-parts":[[2014,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Prediction of a woman's risk of a spontaneous preterm delivery (<jats:styled-content style=\"fixed-case\">PTD<\/jats:styled-content>) is a core challenge and an unresolved problem in today's obstetric practice. The objective of this study was to develop prediction models for spontaneous <jats:styled-content style=\"fixed-case\">PTD<\/jats:styled-content> (&lt;37 weeks).<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A population\u2010based register study of women born in <jats:styled-content style=\"fixed-case\">S<\/jats:styled-content>weden with spontaneous onset of delivery was designed using <jats:styled-content style=\"fixed-case\">S<\/jats:styled-content>wedish <jats:styled-content style=\"fixed-case\">M<\/jats:styled-content>edical <jats:styled-content style=\"fixed-case\">B<\/jats:styled-content>irth <jats:styled-content style=\"fixed-case\">R<\/jats:styled-content>egister data for 1992\u20132008. Predictive variables were identified by multiple logistic regression analysis, and outputs were used to calculate adjusted likelihood ratios in primiparous (<jats:italic>n<\/jats:italic>\u2009=\u2009199\u2009272) and multiparous (<jats:italic>n<\/jats:italic>\u2009=\u2009249\u2009580) singleton pregnant women. The predictive ability of each model was validated in a separate test sample for primiparous (<jats:italic>n<\/jats:italic>\u2009=\u2009190\u2009936) and multiparous (<jats:italic>n<\/jats:italic>\u2009=\u2009239\u2009203) women, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>For multiparous women, the area under the <jats:styled-content style=\"fixed-case\">ROC<\/jats:styled-content> curve (<jats:styled-content style=\"fixed-case\">AUC<\/jats:styled-content>) of 0.74 [95% confidence interval (CI) 0.73, 0.74] indicated a satisfying performance of the model, while for primiparous women, it was rather poor {<jats:styled-content style=\"fixed-case\">AUC<\/jats:styled-content>: 0.58 [95% CI 0.57, 0.58]}. For both primiparous and multiparous women, the prediction models were quite good for pregnancies with comparatively low risk for spontaneous <jats:styled-content style=\"fixed-case\">PTD<\/jats:styled-content>, whereas more limited to predict pregnancies with \u226530% risk of spontaneous <jats:styled-content style=\"fixed-case\">PTD<\/jats:styled-content>.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Spontaneous <jats:styled-content style=\"fixed-case\">PTD<\/jats:styled-content> is difficult to predict in multiparous women and nearly impossible in primiparous, by using this statistical method in a large and unselected sample. However, adding clinical data (like cervical length) may in the future further improve its predictive performance.<\/jats:p><\/jats:sec>","DOI":"10.1111\/ppe.12087","type":"journal-article","created":{"date-parts":[[2013,10,12]],"date-time":"2013-10-12T02:07:51Z","timestamp":1381543671000},"page":"11-22","source":"Crossref","is-referenced-by-count":37,"title":["Predicting Risk of Spontaneous Preterm Delivery in Women with a Singleton Pregnancy"],"prefix":"10.1111","volume":"28","author":[{"given":"Nils\u2010Halvdan","family":"Morken","sequence":"first","affiliation":[{"name":"Department of Global Public Health and Primary Care University of Bergen  Bergen Norway"},{"name":"National Institute of Environmental Health Sciences Epidemiology Branch  Durham NC"},{"name":"Department of Obstetrics and Gynecology Haukeland University Hospital  Bergen 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