Abstract
Objectives
Our aim was to study the association of clinical variables obtainable before delivery for severe neonatal outcomes (SNO) and develop a clinical tool to calculate the prediction probability of SNO in preterm prelabor rupture of membranes (PPROM).
Methods
This was a prospective study from October 2015 to May 2018. We included singleton pregnancies with PPROM and an estimated fetal weight (EFW) two weeks before delivery. We excluded those with fetal anomalies or fetal death. We examined the association between SNO and variables obtainable before delivery such as gestational age (GA) at PPROM, EFW, gender, race, body mass index, chorioamnioitis. SNO was defined as having at least one of the following: respiratory distress syndrome, intraventricular hemorrhage, necrotizing enterocolitis, neonatal sepsis, or neonatal death. The most parsimonious logistic regression models was constructed using the best subset selection model approach, and receiver operator curves were utilized to evaluate the prognostic accuracy of these clinical variables for SNO.
Results
We included 106 pregnancies, 42 had SNO (39.6%). The EFW (area under the receiver operating characteristic curve [AUC]=0.88) and GA at PPROM (AUC=0.83) were significant predictors of SNO. The addition of any of the other variables did not improve the predictive probability of EFW for the prediction of SNO.
Conclusions
The EFW had the strongest association with SNO in in our study among variables obtainable before delivery. Other variables had no significant effect on the prediction probability of the EFW. Our findings should be validated in larger studies.
Research funding: None declared.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Competing interests: Authors state no conflict of interest.
Informed consent: Informed consent was obtained from all individuals included in this study.
Ethical approval: We obtained approval from the University of Tennessee Health Science Center Institutional Review Board prior to recruitment (15-04083) on October 2015.
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