Background: Bias from data missing not at random (MNAR) is a persistent concern in health-related research. A bias analysis quantitatively assesses how conclusions change under different assumptions about missingness using bias parameters that govern the magnitude and direction of the bias. Probabilistic bias analysis specifies a prior distribution for these parameters, explicitly incorporating available information and uncertainty about their true values.
View Article and Find Full Text PDFMacrophages exhibit diverse phenotypes and respond flexibly to environmental cues through metabolic remodeling. In this study, we present a comprehensive multi-omics dataset integrating intra- and extracellular metabolomes with transcriptomic data to investigate the metabolic impact on human macrophage function. Our analysis establishes a metabolite-gene correlation network that characterizes macrophage activation.
View Article and Find Full Text PDFBackground: Two common indications for pediatric heart transplantation are congenital heart disease and cardiomyopathy. Prior studies suggest differences in chronotropy on cardiopulmonary exercise testing outcomes depending on indication for heart transplantation. We aimed to determine whether the number of pretransplant sternotomies is associated with differences in heart rate response during exercise testing.
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September 2024
Studies have suggested that pediatric patients with heart transplants (HT) due to congenital heart disease (CHD) perform differently on cardiopulmonary exercise testing compared to pediatric patients with HT due to cardiomyopathy (CM). However, it is not known if this relationship changes over time. The aim of this study was to examine the differences in cardiopulmonary exercise test (CPET) parameters over time between patients with HT due to CHD versus CM.
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