Background. The aim of the current study was to demonstrate the neonatal outcomes of infants born to mothers with early-onset preeclampsia (EP) and late-onset preeclampsia (LP), and compare the neonatal outcomes before and after 34 weeks of gestation in EP group. Methods. In this retrospective study, we evaluated preeclamptic mother and child pairs who were followedup at Hacettepe University Hospital between the years 2010 and 2017. The pregnant women were classified as having EP if diagnosed before 34 weeks of gestation (n=91) and LP if diagnosed after 34 weeks of gestation (n=34). The women in the EP group were further divided into subgroups according to the gestational week at birth, including those who gave birth before 34 weeks of gestation (early birth; n=57) and after 34 weeks of gestation (late birth; n=34). Necessary clinical and demographic data were withdrawn from the electronic registry and patient files. Results. Neonates in the EP/late birth subgroup had significantly lower gestational age and birthweight. Small for gestational age (SGA) frequency was higher in the early-onset subgroup born after 34 weeks' gestation compared to the late-onset preeclampsia group (p= 0,016). The incidence of neutropenia was significantly higher in the EP/late birth subgroup than in the LP group (p= 0.002). After correcting for gestational week and birth weight, neutrophil count was still significantly lower in the EP/late birth subgroup (p= 0.002). EP/late birth subgroup and LP group had comparable outcomes regardless of neutrophil count and SGA rate. Conclusions. Close follow up and postponing delivery in stable and appropriate pregnant women with preeclampsia would be beneficial for neonates.
Background. Multiple sclerosis (MS) is a disease that predominantly affects the young female population. It is important for an obstetrician to know the effects of pregnancy on MS, and vice versa. Objective. To demonstrate the impact of MS on pregnancy outcomes. Methods. We retrospectively evaluated demographic features, clinical characteristics, and obstetric outcomes of 47 pregnancies in 24 patients with MS, between January 2007 and December 2016. Results. Patients were divided into three groups: (i) 35 pregnancies in patients with MS who were in remission at the beginning of pregnancy; (ii) 10 pregnancies in patients with MS whose disease was exacerbated at the beginning of pregnancy; and (iii) 2 pregnancies in patients with active MS whose symptoms were relieved after becoming pregnant. The overall early pregnancy loss rate was 36.2%, whereas it was 60% and 31.4% in the exacerbation and remission groups, respectively; and the overall preterm delivery rate was 30%, while it was 29.1% and 50% in the remission and exacerbation groups, respectively. Conclusion. Miscarriage and preterm delivery seem to be significant obstetric complications in pregnant women with MS.
ObjectivesTo demonstrate immature granulocyte (IG) count and delta neutrophil index (DNI) values (novel potential predictive marker for neonatal sepsis) for neonates.MethodsThis prospective controlled clinical study was consisted of 208 patients (77 in the study group and 131 in the control group) who were delivered between January 2016 and January 2018 at the Hacettepe University Neonatal Intensive Care Unit in Ankara, Turkey. In this study, we evaluated value of DNI in diagnosing neonatal sepsis by comparing the DNI values in culture positive septic neonates with healthy neonates.ResultsIn our study, the median interquartile range (IQR = 25–75%) DNI was 0.1% (0.0–0.3%) in the control group and 1.5% (1.0–2.45%) in the sepsis group (p < 0.05). In our ROC curve analysis, the cut-off value for the DNI as a sepsis marker was 0.65%, with 96.2% specificity and 97.4% sensitivity. Those patients with gram-negative isolates had significantly higher DNI and IG counts when compared to those patients with gram-positive bacteria (p < 0.05).ConclusionsOur findings indicated that the DNI counts are significant diagnostic biomarkers for neonatal sepsis. They may also have utility in determining the sepsis etiology (differentiating between gram-positive and gram-negative agents).
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