Show simple item record

A model to predict risk of postpartum infection after Caesarean delivery

dc.contributor.author Chagin, Kevin M
dc.contributor.author Goje, O
dc.contributor.author Jelovsek, John E
dc.contributor.author Lachiewicz, Mark
dc.contributor.author Moulton, LJ
dc.date.accessioned 2017-08-01T13:17:35Z
dc.date.available 2017-08-01T13:17:35Z
dc.date.issued 2017-07-12
dc.identifier.issn 1476-7058
dc.identifier.uri https://hdl.handle.net/10161/15108
dc.description.abstract The purpose of this study is to build and validate a statistical model to predict infection after caesarean delivery (CD). Methods: Patient and surgical variables within 30 d of CD were collected on 2419 women. Postpartum infection included surgical site infection, urinary tract infection, endomyometritis and pneumonia. The data were split into model development and internal validation (1 January–31 August; N = 1641) and temporal validation subsets (1 September–31 December; N = 778). Logistic regression models were fit to the data with concordance index and calibration curves used to assess accuracy. Internal validation was performed with bootstrapping correcting for bias. Results: Postoperative infection occurred in 8% (95% CI 7.3–9.9), with 5% meeting CDC criteria for surgical site infections (SSI) (95% CI 4.1–5.8). Eight variables were predictive for infection: increasing BMI, higher number of prior Caesarean deliveries, emergent Caesarean delivery, Caesarean for failure to progress, skin closure using stainless steel staples, chorioamnionitis, maternal asthma and lower gestational age. The model discriminated between women with and without infection on internal validation (concordance index = 0.71 95% CI 0.67–0.76) and temporal validation (concordance index = 0.70, 95% CI 0.62, 0.78). Conclusions: Our model accurately predicts risk of infection after CD. Identification of patients at risk for postoperative infection allows for individualized patient care and counseling.
dc.relation.ispartof Journal of Maternal-Fetal and Neonatal Medicine
dc.relation.isversionof 10.1080/14767058.2017.1344632
dc.title A model to predict risk of postpartum infection after Caesarean delivery
dc.type Journal article
pubs.begin-page 1
pubs.end-page 9
pubs.organisational-group Clinical Science Departments
pubs.organisational-group Duke
pubs.organisational-group Obstetrics and Gynecology
pubs.organisational-group Obstetrics and Gynecology, Urogynecology
pubs.organisational-group School of Medicine
pubs.publication-status Accepted
dc.identifier.eissn 1476-4954


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record