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Timing of delivery in a high-risk obstetric population: a clinical prediction model De Silva, Dane A.; Lisonkova, Sarka; von Dadelszen, Peter; Synnes, Anne; Magee, Laura A.

Abstract

Background: The efficacy of antenatal corticosteroid treatment for women with threatened preterm birth depends on timely administration within 7 days before delivery. We modelled the probability of delivery within 7 days of admission to hospital among women presenting with threatened preterm birth, using routinely collected clinical characteristics. Methods: Data from the Canadian Perinatal Network (CPN) were used, 2005–11, including women admitted to hospital with preterm labour, preterm pre-labour rupture of membranes, short cervix without contractions, or dilated cervix or prolapsed membranes without contractions at preterm gestation. Women with fetal anomaly, intrauterine fetal demise, twin-to-twin transfusion syndrome, and quadruplets were excluded. Logistic regression was undertaken to create a predictive model that was assessed for its calibration capacity, stratification ability, and classification accuracy (ROC curve). Results: We included 3012 women admitted at 24–28 weeks gestation, or readmitted at up to 34 weeks gestation, to 16 tertiary-care CPN hospitals. Of these, 1473 (48.9%) delivered within 7 days of admission. Significant predictors of early delivery included maternal age, parity, gestational age at admission, smoking, preterm labour, prolapsed membranes, preterm pre-labour rupture of membranes, and antepartum haemorrhage. The area under the ROC curve was 0.724 (95% CI 0.706–0.742). Conclusion: We propose a useful tool to improve prediction of delivery within 7 days after admission among women with threatened preterm birth. This information is important for optimal corticosteroid treatment.

Item Metadata

Title
Timing of delivery in a high-risk obstetric population: a clinical prediction model
Creator
De Silva, Dane A.; Lisonkova, Sarka; von Dadelszen, Peter; Synnes, Anne; Magee, Laura A.
Publisher
BioMed Central
Date Issued
2017-06-29
Description
Background: The efficacy of antenatal corticosteroid treatment for women with threatened preterm birth depends on timely administration within 7 days before delivery. We modelled the probability of delivery within 7 days of admission to hospital among women presenting with threatened preterm birth, using routinely collected clinical characteristics. Methods: Data from the Canadian Perinatal Network (CPN) were used, 2005–11, including women admitted to hospital with preterm labour, preterm pre-labour rupture of membranes, short cervix without contractions, or dilated cervix or prolapsed membranes without contractions at preterm gestation. Women with fetal anomaly, intrauterine fetal demise, twin-to-twin transfusion syndrome, and quadruplets were excluded. Logistic regression was undertaken to create a predictive model that was assessed for its calibration capacity, stratification ability, and classification accuracy (ROC curve). Results: We included 3012 women admitted at 24–28 weeks gestation, or readmitted at up to 34 weeks gestation, to 16 tertiary-care CPN hospitals. Of these, 1473 (48.9%) delivered within 7 days of admission. Significant predictors of early delivery included maternal age, parity, gestational age at admission, smoking, preterm labour, prolapsed membranes, preterm pre-labour rupture of membranes, and antepartum haemorrhage. The area under the ROC curve was 0.724 (95% CI 0.706–0.742). Conclusion: We propose a useful tool to improve prediction of delivery within 7 days after admission among women with threatened preterm birth. This information is important for optimal corticosteroid treatment.
Subject
Preterm birth; Prediction model; Antenatal corticosteroids
Genre
Article
Type
Text
Language
eng
Date Available
2018-05-15
Provider
Vancouver : University of British Columbia Library
Rights
Attribution 4.0 International (CC BY 4.0)
DOI
10.14288/1.0366847
URI
http://hdl.handle.net/2429/65909
Affiliation
Medicine, Faculty of; Non UBC; Obstetrics and Gynaecology, Department of; Pediatrics, Department of; Population and Public Health (SPPH), School of
Citation
BMC Pregnancy and Childbirth. 2017 Jun 29;17(1):202
Publisher DOI
10.1186/s12884-017-1390-9
Peer Review Status
Reviewed
Scholarly Level
Faculty
Copyright Holder
The Author(s).
Rights URI
http://creativecommons.org/licenses/by/4.0/
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Attribution 4.0 International (CC BY 4.0)