Mariella Mailath-Pokorny1, Stephan Polterauer2, Maria Kohl3, Verena Kueronyai1, Katharina Worda1, Georg Heinze3, Martin Langer1. 1. Department of Obstetrics and Gynecology, Medical University Vienna, Vienna, Austria. 2. Department of Obstetrics and Gynecology, Medical University Vienna, Vienna, Austria; Karl Landsteiner Institute for General Gynecology and Experimental Gynecologic Oncology, Vienna, Austria. Electronic address: stephan.polterauer@meduniwien.ac.at. 3. Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
Abstract
OBJECTIVES: To construct two prediction models for individualized assessment of preterm delivery risk within 48h and before completed 32 weeks of gestation and to test the validity of modified and previously published models. STUDY DESIGN: Data on 617 consecutive women with preterm labor transferred to a tertiary care center for threatened preterm delivery between 22 and 32 weeks of gestation were analysed. Variables predicting the risk of delivery within 48h and before completed 32 weeks of gestation were assessed and applied to previously published prediction models. Multivariate analyses identified variables that were incorporated into two modified models that were subsequently validated. RESULTS: Two modified prediction models were developed and internally validated, incorporating four and six of the following variables to predict the risk of delivery within 48h and before completed 32 weeks of gestation, respectively: presence of preterm premature rupture of membranes and/or vaginal bleeding, sonographic cervical length, week of gestation, fetal fibronectin, and serum C-reactive protein. The correspondence between the actual and the predicted preterm birth rates suggests excellent calibration of the models. Internal validation analyses for the modified 48h and 32 week prediction models revealed considerably high concordance-indices of 0.8 (95%CI: [0.70-0.81]) and 0.85 (95%CI: [0.82-0.90]), respectively. CONCLUSIONS: Two modified prediction models to assess the risk of preterm birth were constructed and validated. The models can be used for individualized prediction of preterm birth and allow more accurate risk assessment than based upon a single risk factor. An online-based risk-calculator was constructed and can be assessed through: http://cemsiis.meduniwien.ac.at/en/kb/science-research/software/clinical-software/prematurebirth/.
OBJECTIVES: To construct two prediction models for individualized assessment of preterm delivery risk within 48h and before completed 32 weeks of gestation and to test the validity of modified and previously published models. STUDY DESIGN: Data on 617 consecutive women with preterm labor transferred to a tertiary care center for threatened preterm delivery between 22 and 32 weeks of gestation were analysed. Variables predicting the risk of delivery within 48h and before completed 32 weeks of gestation were assessed and applied to previously published prediction models. Multivariate analyses identified variables that were incorporated into two modified models that were subsequently validated. RESULTS: Two modified prediction models were developed and internally validated, incorporating four and six of the following variables to predict the risk of delivery within 48h and before completed 32 weeks of gestation, respectively: presence of preterm premature rupture of membranes and/or vaginal bleeding, sonographic cervical length, week of gestation, fetal fibronectin, and serum C-reactive protein. The correspondence between the actual and the predicted preterm birth rates suggests excellent calibration of the models. Internal validation analyses for the modified 48h and 32 week prediction models revealed considerably high concordance-indices of 0.8 (95%CI: [0.70-0.81]) and 0.85 (95%CI: [0.82-0.90]), respectively. CONCLUSIONS: Two modified prediction models to assess the risk of preterm birth were constructed and validated. The models can be used for individualized prediction of preterm birth and allow more accurate risk assessment than based upon a single risk factor. An online-based risk-calculator was constructed and can be assessed through: http://cemsiis.meduniwien.ac.at/en/kb/science-research/software/clinical-software/prematurebirth/.