Risk of Epilepsy Following a First Posttraumatic Seizure: A Register-Based Study.

Background And Objectives: Traumatic brain injury (TBI) is a common cause of epilepsy, and the risk increases with injury severity. Whether a first posttraumatic seizure (PTS) represents epilepsy is a common clinical problem, but often unknown. Prognostication is important for providing correct patient information and consideration of antiseizure medication.

Respiratory support and bronchopulmonary dysplasia in infants born at 22-26 weeks gestation in Sweden, 2004-2007 and 2014-2016.

Aim: To evaluate if increased survival and new ventilation strategies were accompanied by a changed incidence of bronchopulmonary dysplasia (BPD) in Sweden over a decade.

Methods: Data from two Swedish population-based studies of live-born infants with gestational ages (GA) 22-26 weeks, born during 2004-2007 (n=702) and 2014-2016 (n=885), were compared for survival, any BPD, moderate BPD, severe BPD, and BPD/severe BPD or death at 36 weeks postmenstrual age (PMA). Ventilation strategies and interventions were analysed.

DSM 17938 Produce Bioactive Components during Formulation in Sucrose.

Improved efficacy of probiotics can be achieved by using different strategies, including the optimization of production parameters. The impact of fermentation parameters on bacterial physiology is a frequently investigated topic, but what happens during the formulation, i.e.

Centralisation of extremely preterm births and decreased early postnatal mortality in Sweden, 2004-2007 versus 2014-2016.

Aim: We evaluated the increased centralisation of extremely preterm (EPT) births in Sweden in relation to the changes in mortality and morbidity.

Methods: Population-based data covering Swedish live births from 22 + 0 to 26 + 6 weeks of gestation during 2004-2007 and 2014-2016 were analysed for associations between time-period, birth within (inborn) or outside (outborn) regional centres, and outcomes.

Results: Among 1626 liveborn infants, 703 were born in 2004-2007 and 923 in 2014-2016.

Data-driven prediction of spinal cord injury recovery: An exploration of current status and future perspectives.

Spinal Cord Injury (SCI) presents a significant challenge in rehabilitation medicine, with recovery outcomes varying widely among individuals. Machine learning (ML) is a promising approach to enhance the prediction of recovery trajectories, but its integration into clinical practice requires a thorough understanding of its efficacy and applicability. We systematically reviewed the current literature on data-driven models of SCI recovery prediction.