The field of medicine is undergoing a fundamental change, transforming towards a modern data-driven patient-oriented approach. This paradigm shift also affects perinatal medicine as predictive algorithms and artificial intelligence are applied to enhance and individualize maternal, neonatal and perinatal care. Here, we introduce a pharmacometrics-based mathematical-statistical computer program (PMX-based algorithm) focusing on hyperbilirubinemia, a medical condition affecting half of all newborns.
View Article and Find Full Text PDFBackground: Serum neurofilament light chain (sNfL) is an established biomarker of neuro-axonal damage in multiple neurological disorders. Raised sNfL levels have been reported in adults infected with pandemic coronavirus disease 2019 (COVID-19). Levels in children infected with COVID-19 have not as yet been reported.
View Article and Find Full Text PDFObjective: Neuroaxonal damage is reflected by serum neurofilament light chain (sNfL) values in a variety of acute and degenerative diseases of the brain. The aim of this study was to investigate the impact of febrile and epileptic seizures on sNfL, serum copeptin, and prolactin levels in children compared with children with febrile infections without convulsions.
Methods: A prospective cross-sectional study was performed in children aging 6 months to 5 years presenting with fever (controls, = 61), febrile seizures (FS, = 78), or epileptic seizures (ES, = 16) at our emergency department.
Background: Machine learning models may enhance the early detection of clinically relevant hyperbilirubinemia based on patient information available in every hospital.
Methods: We conducted a longitudinal study on preterm and term born neonates with serial measurements of total serum bilirubin in the first two weeks of life. An ensemble, that combines a logistic regression with a random forest classifier, was trained to discriminate between the two classes phototherapy treatment vs.
Vaginal birth prepares the fetus for postnatal life. It confers respiratory, cardiovascular and homeostatic advantages to the newborn infant compared with elective cesarean section, and is reported to provide neonatal analgesia. We hypothesize that infants born by vaginal delivery will show lower noxious-evoked brain activity a few hours after birth compared to those born by elective cesarean section.
View Article and Find Full Text PDFBackground & Aims: Almost all neonates show physiological weight loss and consecutive weight gain after birth. The resulting weight change profiles are highly variable as they depend on multiple neonatal and maternal factors. This limits the value of weight nomograms for the early identification of neonates at risk for excessive weight loss and related morbidities.
View Article and Find Full Text PDFPain is an unpleasant sensory and emotional experience. In non-verbal patients, it is very difficult to measure pain, even with pain assessment tools. Those tools are subjective or determine secondary physiological indicators which also have certain limitations particularly when exploring the effectiveness of analgesia.
View Article and Find Full Text PDFObjectives: To develop a mathematical, semimechanistic model characterizing physiological weight changes in term neonates, identify and quantify key maternal and neonatal factors influencing weight changes, and provide an online tool to forecast individual weight changes during the first week of life.
Study Design: Longitudinal weight data from 1335 healthy term neonates exclusively breastfed up to 1 week of life were available. A semimechanistic model was developed to characterize weight changes applying nonlinear mixed-effects modeling.