Prediction of spontaneous preterm delivery in the first trimester of pregnancy

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• 作者：Nicolas Sananes ; Nicolas Meyer ; Adrien Gaudineau ; Germain Aissi ; Eric Boudier ; Gabrielle Fritz ; Brigitte Viville ; Isra毛l Nis ; Bruno Langer ; Romain Favre
• 关键词：First-trimester ; Screening ; Preterm delivery
• 刊名：European Journal of Obstetrics and Gynecology and Reproductive Biology
• 出版年：November, 2013
• 年：2013
• 卷：171
• 期：1
• 页码：18-22
• 全文大小：440 K

文摘

Objective

To develop a model for predicting premature delivery before 37 weeks鈥?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.