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BMC Nurs
January 2025
Faculty of Applied Medical Sciences in Alnamas, University of Bisha, 255, Al Nakhil, Al-Namas, 67714, Saudi Arabia.
Background: One of the best ways to impart important skills to trainees is through simulation-based training, which is more reliable than the conventional clinical examination method. It is used in pediatric nursing training to allow nurses to practice and improve their clinical and conversational skills during an actual child encounter. A heel-prick is a complex psychomotor task that requires skill and knowledge from the pediatric nurse performing the procedure while applying for the National Newborn Screening Program.
View Article and Find Full Text PDFNutr J
January 2025
Paediatrics, Nutrition and Development Research Unit, Universitat Rovira i Virgili. Reus, Tarragona, Spain.
Background & Aim: Metabolic and cardiovascular health outcomes are strongly influenced by diet. Dietary habits established in early childhood may persist into adulthood. This study aimed to examine the association between dietary patterns at both 2 and 8 years of age, explaining the maximum variability of high- and low-quality fats, sugars, and fibre, and cardiometabolic markers at age 8 years.
View Article and Find Full Text PDFBMC Public Health
January 2025
Division of General Medicine, University of Michigan Medical School, Ann Arbor, USA.
Background: Modeling studies suggest that hundreds of thousands of U.S. children have lost caregivers since the COVID-19 pandemic began.
View Article and Find Full Text PDFBMC Pediatr
January 2025
School of Nursing and Health Sciences, The College of New Jersey, Ewing Township, USA.
Background: Preterm infants may experience many health and developmental issues, which continue even after discharge from the neonatal intensive care unit. Once home, the mother, as a non-professional and the primary caregiver will be responsible for the essential care of her preterm infant.
Purpose: Understanding the take care ability in mothers with preterm infants.
BMC Pregnancy Childbirth
January 2025
Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of Utah Health, 30 N. Mario Capecchi Dr., Level 5 South, Salt Lake City, UT, 84132, USA.
Background: Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.
Methods: Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.
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