This study addresses the global issue of foodborne illness, specifically focusing on those resulting from the consumption of leafy green vegetables. It explores the rising trend of consuming minimally processed or raw foods and the imperative of maintaining safety standards starting at the preharvest stage to prevent pathogenic bacterial contamination. The study identifies soil and irrigation water as key sources of pathogens and emphasizes the need for strict preventive measures during production and preharvest.
View Article and Find Full Text PDFJ Microbiol Immunol Infect
January 2025
Respiratory syncytial virus (RSV) is the most common pathogen for young children hospitalized with bronchiolitis and pneumonia. Most infections occur below 1 year of age. RSV is also a significant viral pathogen for adults with respiratory tract infection.
View Article and Find Full Text PDFBackground: High-flow nasal cannula (HFNC) has emerged as a promising intervention for post-extubation oxygen therapy, with the potential to reduce the need for reintubation. However, it remains unclear whether using a higher flow setting provides better outcomes than the commonly used flow rate of 30-50 L/min.
Research Question: Does setting the flow rate of HFNC at 60 L/min versus 40 L/min for post-extubation care result in different extubation outcomes?
Study Design And Methods: This randomized controlled trial assigned intubated patients to receive HFNC at either a 60 L/min or 40 L/min flow rate following extubation.
We report the successful application of single pass albumin dialysis (SPAD) and hemoadsorption (HA) in two teenagers with amlodipine poisoning. A 16-year-old girl with amlodipine overdose developed refractory shock and lactic acidosis despite multiple inotropes, calcium, insulin, and glucagon infusion. SPAD was initiated 18 h after the incident for 21 h.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
December 2024
Background: We aimed to develop and validate models for predicting intensive care unit (ICU) mortality of critically ill adult patients as early as upon ICU admission.
Methods: Combined data of 79,657 admissions from two teaching hospitals' ICU databases were used to train and validate the machine learning models to predict ICU mortality upon ICU admission and at 24 h after ICU admission by using logistic regression, gradient boosted trees (GBT), and deep learning algorithms.
Results: In the testing dataset for the admission models, the ICU mortality rate was 7%, and 38.