Prediction of Preterm Birth by Maternal Characteristics and Medical History in the Brazilian Population. (25th September 2019)
- Record Type:
- Journal Article
- Title:
- Prediction of Preterm Birth by Maternal Characteristics and Medical History in the Brazilian Population. (25th September 2019)
- Main Title:
- Prediction of Preterm Birth by Maternal Characteristics and Medical History in the Brazilian Population
- Authors:
- Damaso, Enio Luis
Rolnik, Daniel Lober
Cavalli, Ricardo de Carvalho
Quintana, Silvana Maria
Duarte, Geraldo
da Silva Costa, Fabricio
Marcolin, Alessandra - Other Names:
- Saunders Cláudia Academic Editor.
- Abstract:
- Abstract : Objectives. The aim of this study was to assess the performance of a previously published algorithm for first-trimester prediction of spontaneous preterm birth (PTB) in a cohort of Brazilian women. Methods. This was a retrospective cohort study of women undergoing routine antenatal care. Maternal characteristics and medical history were obtained. The data were inserted in the Fetal Medicine Foundation (FMF) online calculator to estimate the individual risk of PTB. Univariate and multivariate logistic regression analyses were performed to determine the effects of maternal characteristics on the occurrence of PTB. A receiver-operating characteristics (ROC) curve was used to determine the detection rates and false-positive rates of the FMF algorithm in predicting PTB <34 weeks of gestation in our population. Results. In total, 1, 323 women were included. Of those, 23 (1.7%) had a spontaneous PTB before 34 weeks of gestation, 87 (6.6%) had a preterm birth between 34 and 37 weeks, and 1, 197 (91.7%) had a term delivery. Smoking and a previous history of recurrent PTB between 16 and 30 weeks of gestation without prior term pregnancy were significantly more common among women who delivered before 34 weeks of gestation compared to those who delivered at term were (39.1% vs. 12.0%, p = 0.001 and 8.7% vs. 0%, p < 0.001, respectively). Smoking and history of spontaneous PTB remained significantly associated with spontaneous PTB in the multivariate logistic regressionAbstract : Objectives. The aim of this study was to assess the performance of a previously published algorithm for first-trimester prediction of spontaneous preterm birth (PTB) in a cohort of Brazilian women. Methods. This was a retrospective cohort study of women undergoing routine antenatal care. Maternal characteristics and medical history were obtained. The data were inserted in the Fetal Medicine Foundation (FMF) online calculator to estimate the individual risk of PTB. Univariate and multivariate logistic regression analyses were performed to determine the effects of maternal characteristics on the occurrence of PTB. A receiver-operating characteristics (ROC) curve was used to determine the detection rates and false-positive rates of the FMF algorithm in predicting PTB <34 weeks of gestation in our population. Results. In total, 1, 323 women were included. Of those, 23 (1.7%) had a spontaneous PTB before 34 weeks of gestation, 87 (6.6%) had a preterm birth between 34 and 37 weeks, and 1, 197 (91.7%) had a term delivery. Smoking and a previous history of recurrent PTB between 16 and 30 weeks of gestation without prior term pregnancy were significantly more common among women who delivered before 34 weeks of gestation compared to those who delivered at term were (39.1% vs. 12.0%, p = 0.001 and 8.7% vs. 0%, p < 0.001, respectively). Smoking and history of spontaneous PTB remained significantly associated with spontaneous PTB in the multivariate logistic regression analysis. Significant prediction of PTB <34 weeks of gestation was provided by the FMF algorithm (area under the ROC curve 0.67, 95% CI 0.56–0.78, p = 0.005 ), but the detection rates for fixed false-positive rates of 10% and 20% were poor (26.1% and 34.8%, respectively). Conclusions. Maternal characteristics and history in the first trimester can significantly predict the occurrence of spontaneous delivery before 34 weeks of gestation. Although the predictive algorithm performed similarly to previously published data, the detection rates are poor and research on new biomarkers to improve its performance is needed. … (more)
- Is Part Of:
- Journal of pregnancy. Volume 2019(2019)
- Journal:
- Journal of pregnancy
- Issue:
- Volume 2019(2019)
- Issue Display:
- Volume 2019, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 2019
- Issue:
- 2019
- Issue Sort Value:
- 2019-2019-2019-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-09-25
- Subjects:
- Pregnancy -- Periodicals
Pregnancy -- Complications -- Periodicals
Pregnancy
Pregnancy Complications
Pregnancy
Pregnancy -- Complications
Electronic journals
Periodicals
Periodicals
618.2 - Journal URLs:
- https://www.hindawi.com/journals/jp/ ↗
http://bibpurl.oclc.org/web/45129 ↗
http://www.ncbi.nlm.nih.gov/pmc/journals/1493/ ↗
http://bibpurl.oclc.org/web/45127 ↗ - DOI:
- 10.1155/2019/4395217 ↗
- Languages:
- English
- ISSNs:
- 2090-2727
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 12000.xml