Predicting Risk of Spontaneous Preterm Delivery in Women with a Singleton Pregnancy

Research output: Contribution to journalArticle

Abstract

BackgroundPrediction of a woman's risk of a spontaneous preterm delivery (PTD) 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 PTD (<37 weeks). MethodsA population-based register study of women born in Sweden with spontaneous onset of delivery was designed using Swedish Medical Birth Register data for 1992-2008. Predictive variables were identified by multiple logistic regression analysis, and outputs were used to calculate adjusted likelihood ratios in primiparous (n=199272) and multiparous (n=249580) singleton pregnant women. The predictive ability of each model was validated in a separate test sample for primiparous (n=190936) and multiparous (n=239203) women, respectively. ResultsFor multiparous women, the area under the ROC curve (AUC) 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 {AUC: 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 PTD, whereas more limited to predict pregnancies with 30% risk of spontaneous PTD. ConclusionsSpontaneous PTD 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.

Details

Authors
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Obstetrics, Gynecology and Reproductive Medicine

Keywords

  • predicting risk, spontaneous preterm delivery, singleton pregnancy
Original languageEnglish
Pages (from-to)11-22
JournalPaediatric and Perinatal Epidemiology
Volume28
Issue number1
StatePublished - 2014
Peer-reviewedYes