Background: Preterm prelabour rupture of membranes (PPRoM) is commonly associated with preterm delivery and affects up to 3% of all pregnancies. It is associated with high rates of morbidity and mortality for the mother and the newborn.
Objectives: To identify risk factors for PPRoM and develop a model for first-trimester prediction of risk of PPRoM.
Methods: A retrospective analysis of a series of women who had first-trimester (11-13+6 weeks) screening for aneuploidy and pre-eclampsia and delivered in the same institution was performed. Univariate and multivariate logistic regression analyses were used to identify maternal and pregnancy factors and then develop a clinical prediction model for PPRoM.
Results: 10,280 women were screened between April 2010 and October 2016. 144 (1.4%) had PPRoM. Maternal factors predictive of PPRoM included nulliparity (parous women, OR 0.53; 95% CI 0.4-0.8), pre-existing diabetes mellitus (DM) (Type 1 DM, OR 6.7; 95% CI 2.3-19.4, Type 2 DM, OR 5.3; 95% CI 1.6-18.3), maternal age group (p = 0.004), and BMI category (p = 0.012). Uterine artery pulsatility index (UAPI) and biochemical parameters (PAPP-A, free βHCG) did not reach statistical significance. The predictive model had moderate efficacy with an area under the ROC curve of 0.67.
Conclusions: Several maternal characteristics collected during first-trimester screening predict PPRoM. Biomarkers currently measured during first-trimester screening (PAPP-A, βHCG, and UAPI) do not predict PPRoM. Whilst a predictive model can be generated with information currently collected at 11-13+6 weeks, this has only modest screening performance. First-trimester screening provides a structured framework where other predictors could improve model performance, and future studies should focus on the addition of other risk factors and biomarkers that may improve screening efficacy.
Keywords: First trimester; Prediction; Pregnancy; Preterm prelabour rupture of membranes; Risk factors.
© 2020 S. Karger AG, Basel.