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Can neonatal sepsis be predicted in late preterm premature rupture of membranes? Development of a prediction model

By David P. van der Ham, Sander van Kuijk, Brent C. Opmeer, Christine Willekes, Johannes J. van Beek, Antonius L. M. Mulder, Aren J. van Loon, Martiët Groenewout, Gerald D. Mantel, Kitty W. M. Bloemenkamp, Martina Porath, Anneke Kwee, Bettina M. C. Akerboom, Dimitri N. M. Papatsonis, Godfried C. H. Metz, Jan G. Nijhuis and Ben W. J. Mol

Abstract

Women with late preterm premature rupture of membranes (PROM) have an increased risk that their child will develop neonatal sepsis. We evaluated whether neonatal sepsis can be predicted from antepartum parameters in these women. We used multivariable logistic regression to develop a prediction model. Data were obtained from two recent randomized controlled trials on induction of labor versus expectant management in late preterm PROM (PPROMEXIL trials, (ISRCTN29313500 and ISRCTN05689407). Data from randomized as well as non-randomized women, who consented to the use of their medical data, were used. We evaluated 13 potential antepartum predictors for neonatal sepsis. Missing data were imputed. Discriminative ability of the model was expressed as the area under the receiver operating characteristic (ROC) curve and a calibration with both a calibration plot and the Hosmer and Lemeshow goodness-of-fit test. Overall performance of the prediction model was quantified as the scaled Brier score. We studied 970 women. Thirty-three (3.4%) neonates suffered neonatal sepsis. Maternal age (OR 1.09 per year), maternal CRP level (OR 1.01 per mmol/l), maternal temperature (OR 1.80 per °C) and positive GBS culture (OR 2.20) were associated with an increased risk of neonatal sepsis. The model had an area under the ROC-curve of 0.71. The model had both a good calibration and accuracy. Antepartum parameters aid in the more precise prediction of the risk of neonatal sepsis in women with late preterm PPRO

Year: 2014
DOI identifier: 10.1016/j.ejogrb.2014.02.003
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Provided by: NARCIS
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