In this paper a prospective study of the association between maternal smoking and neonatal morbidity variables is presented. Caucasian nulliparous women (n = 115)were studied throughout pregnancy, childbirth and puerperal period. Birthweight(-centiles), Apgar scores, mode of delivery, umbilical arterial and venous blood gas analyses, admission incidence to the neonatal ward and neurological examnination according to Prechtl were considered to be representatives for the starting condition of the newborns. The babies of smokers were statistically significantly at a disadvantage compared to babies of non-smokers for birthweight(-centiles), pH of the umbilical vein (medians): smokers 7.29, non-smokers 7.30) and the score of the neurological examnination (medians: smokers 57, non-smokers 58).
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Blood draws for laboratory investigations are essential for patient management in neonatal intensive care units (NICU). When blood samples clot before analysis, they are rejected, which delays treatment decisions and necessitates repeated sampling.
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Background: Post-term pregnancy, a pregnancy exceeding 294 days or 42 completed weeks, is associated with increased perinatal morbidity and mortality and is considered a high-risk condition which requires specialist surveillance and induction of labour. However, there is uncertainty on the policy concerning the timing of induction for post-term pregnancy or impending post-term pregnancy, leading to practice variation between caregivers. Previous studies on induction at or beyond 41 weeks versus expectant management showed different results on perinatal outcome though conclusions in meta-analyses show a preference for induction at 41 weeks. However, interpretation of the results is hampered by the limited sample size of most trials and the heterogeneity in design. Most control groups had a policy of awaiting spontaneous onset of labour that went far beyond 42 weeks, which does not reflect usual care in The Netherlands where induction of labour at 42 weeks is the regular policy. Thus leaving the question unanswered if induction at 41 weeks results in better perinatal outcomes than expectant management until 42 weeks. Methods/design: In this study we compare a policy of labour induction at 41 + 0/+1 weeks with a policy of expectant management until 42 weeks in obstetrical low risk women without contra-indications for expectant management until 42 weeks and a singleton pregnancy in cephalic position. We will perform a multicenter randomised controlled clinical trial. Our primary outcome will be a composite outcome of perinatal mortality and neonatal morbidity. Secondary outcomes will be maternal outcomes as mode of delivery (operative vaginal delivery and Caesarean section), need for analgesia and postpartum haemorrhage (≥1000 ml). Maternal preferences, satisfaction, wellbeing, pain and anxiety will be assessed alongside the trial. Discussion: his study will provide evidence for the management of pregnant women reaching a gestational age of 41 weeks.
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Het aantal alarmen dat afgaat op een Neonatale Intensive Care Unit (NICU) is hoog omdat de vitale fysiologische parameters van de neonaten als vanzelfsprekend continu gemonitord worden door medische apparatuur. Dit leidt tot een enorme alarmdruk bij NICU-verpleegkundigen, want elk alarm moet beoordeeld worden. Echter, slechts 20% van de klinische alarmen is relevant, wat niet alleen leidt tot inefficiënte werkprocessen, maar ook tot alarmmoeheid en daarmee bedreiging van patiëntveiligheid. Literatuur- en praktijkonderzoek door studenten HBO-ICT en onderzoekers van het lectoraat ICT-innovaties in de Zorg (Hogeschool Windesheim) op de NICU van Isala ziekenhuis in Zwolle laat zien dat er winst lijkt te behalen in het slim combineren van alarmen en het aanpassen van grenswaarden. Hier kan uiteraard niet zomaar mee geëxperimenteerd worden in de werkelijke klinische setting. Isala heeft daarom behoefte aan een testomgeving waarin de impact van alarmaanpassingen op alarmreductie gemeten kan worden zonder dat patiëntveiligheid daarmee in gevaar komt. Een digital twin kan hier een oplossing bieden. Dit is een replica van de fysieke, dynamische NICU-setting waarin data van patiënten, apparaten en hun onderlinge interacties gesimuleerd kunnen worden en artificial intelligence voorspellingen kan doen over de impact van veranderingen. In de gezondheidszorg wordt de potentie van digital twins de laatste twee jaar gezien en het aantal publicaties en best practices neemt toe, maar toepassingen op de intensive care-setting zijn nog dun gezaaid. Dit project, waarvoor Windesheim, Isala en data science agency Little Rocket de krachten bundelen, levert hier een bijdrage aan
