OBJECTIVE: To develop a model for predicting premature delivery before 37 weeks' gestation based on maternal factors, obstetric history and biomarkers in the first trimester of pregnancy. STUDY DESIGN: Cohort study based on data collected prospectively between 1 January 2000 and 30 November 2011. Multivariate logistic regression was used to construct a model of the risk of premature delivery. RESULTS: 31,834 pregnancies were included, of which 1188 cases were spontaneous premature deliveries before 37 weeks (3.7%). We built a predictive model based on maternal age, body mass index, smoking status and previous obstetric history. This could identify 23.3% of premature deliveries in our study population, with a false positive rate of 10%. In the group of patients who had already had at least one pregnancy at or beyond 16 weeks, the detection level increased to 29.7%. The positive predictive value was 7.4 and 7.3% respectively, while negative predictive value was 97.2 and 97.9%. CONCLUSIONS: Predicting preterm delivery on the basis of maternal characteristics and obstetric history needs to be further improved. PAPP-A levels and ultrasonographic measurement of cervical length could not be integrated in the model but require further investigations.
OBJECTIVE: To develop a model for predicting premature delivery before 37 weeks' gestation based on maternal factors, obstetric history and biomarkers in the first trimester of pregnancy. STUDY DESIGN: Cohort study based on data collected prospectively between 1 January 2000 and 30 November 2011. Multivariate logistic regression was used to construct a model of the risk of premature delivery. RESULTS: 31,834 pregnancies were included, of which 1188 cases were spontaneous premature deliveries before 37 weeks (3.7%). We built a predictive model based on maternal age, body mass index, smoking status and previous obstetric history. This could identify 23.3% of premature deliveries in our study population, with a false positive rate of 10%. In the group of patients who had already had at least one pregnancy at or beyond 16 weeks, the detection level increased to 29.7%. The positive predictive value was 7.4 and 7.3% respectively, while negative predictive value was 97.2 and 97.9%. CONCLUSIONS: Predicting preterm delivery on the basis of maternal characteristics and obstetric history needs to be further improved. PAPP-A levels and ultrasonographic measurement of cervical length could not be integrated in the model but require further investigations.
Authors: Heleen J Schuster; Myrthe J C S Peelen; Petra J Hajenius; Monique D M van Beukering; Rik van Eekelen; Marit Schonewille; Henna Playfair; Joris A M van der Post; Marjolein Kok; Rebecca C Painter Journal: Health Sci Rep Date: 2022-05-24
Authors: Barbara J Stegmann; Mark Santillan; Benjamin Leader; Elaine Smith; Donna Santillan Journal: Fertil Steril Date: 2015-06-19 Impact factor: 7.329
Authors: Linda J E Meertens; Pim van Montfort; Hubertina C J Scheepers; Sander M J van Kuijk; Robert Aardenburg; Josje Langenveld; Ivo M A van Dooren; Iris M Zwaan; Marc E A Spaanderman; Luc J M Smits Journal: Acta Obstet Gynecol Scand Date: 2018-05-09 Impact factor: 3.636
Authors: Lisa Be Shields; Clayton Weymouth; Kevin L Bramer; Scott Robinson; Donna McGee; Lori Richards; Corey Ogle; Christopher B Shields Journal: SAGE Open Med Date: 2021-01-12