COVID-19 media fatigue: predictors of decreasing interest and avoidance of COVID-19-related news.

OBJECTIVES: COVID-19-related news is important for adherence to public health measures. We examined predictors of interest and avoidance of COVID-19 news in Lithuania. STUDY DESIGN: This is an online survey. METHODS: An online survey was conducted between October and December 2020 targeting the general population in Lithuania. Participants rated their interest and avoidance of news about the COVID-19 pandemic, with possible answers ranging from 'completely agree' to 'completely disagree'. The participants were also evaluated for symptoms of depression (Patient Health Questionnaire-8), anxiety (Generalized Anxiety Disorder-7), post-traumatic stress (Impact of Event Scale-Revised) and COVID-19 fear (COVID-19 Fears Questionnaire). RESULTS: In total, 1036 participants (83% women) completed the survey. The results indicated that 37% of participants were losing interest in COVID-19 news, 32% had started avoiding COVID-19 news and 26% had stopped following news about COVID-19. In the multivariate regression analyses, younger age, greater post-traumatic stress symptoms, less fear of COVID-19 and less frequent use of healthcare professionals for COVID-19 information were independent predictors of decreasing/diminished interest and avoidance of COVID-19 news (all P-values <0.005). More frequent use of friends/relatives for COVID-19 information was associated with increasing avoidance and diminished interest in news about COVID-19, while more frequent use of internet news portals for COVID-19 information predicted decreasing/diminished interest in news about COVID-19, independently from other factors considered in this study. CONCLUSIONS: Decreasing/diminished interest and avoidance of news about COVID-19 are common and are associated with younger age, greater post-traumatic stress symptoms, less fear of COVID-19 and less frequent use of healthcare professionals for COVID-19 information.

Preliminary Results Comparing Thin Plate Splines with Finite Element Methods for Modeling Brain Deformation during Neurosurgery using Intraoperative Ultrasound.

Brain shift compensation attempts to model the deformation of the brain which occurs during the surgical removal of brain tumors to enable mapping of presurgical image data into patient coordinates during surgery and thus improve the accuracy and utility of neuro-navigation. We present preliminary results from clinical tumor resections that compare two methods for modeling brain deformation, a simple thin plate spline method that interpolates displacements and a more complex finite element method (FEM) that models physical and geometric constraints of the brain and its material properties. Both methods are driven by the same set of displacements at locations surrounding the tumor. These displacements were derived from sets of corresponding matched features that were automatically detected using the SIFT-Rank algorithm. The deformation accuracy was tested using a set of manually identified landmarks. The FEM method requires significantly more preprocessing than the spline method but both methods can be used to model deformations in the operating room in reasonable time frames. Our preliminary results indicate that the FEM deformation model significantly out-performs the spline-based approach for predicting the deformation of manual landmarks. While both methods compensate for brain shift, this work suggests that models that incorporate biophysics and geometric constraints may be more accurate.

Cognitive function in patients with coronary artery disease: A literature review.

Objective Cognitive function impairment is a well-documented complication of cerebrovascular disease (CBVD). Less is known about what factors affect the deterioration of cognitive function in patients with coronary artery disease (CAD). The aim of this review is to explore recent studies investigating factors associated with cognitive function in patients with CAD. Methods Studies published from 2010 to 2016 were identified through a systematic search of MEDLINE/PubMed and were included if they addressed factors affecting cognitive function in the CAD population. Results Of the 227 publications identified, 32 were selected for the review. Five factors tentatively affecting cognitive function in patients with CAD were identified: coronary artery bypass grafting (CABG) surgery, apolipoprotein E4 (APOE4) genotype, left ventricular ejection fraction (LVEF), medication use, and various hormones and biomarkers. Conclusion New techniques in CABG surgery have proven to alleviate postoperative cognitive decline. Researchers are still debating the effects of APOE4 genotype, LVEF, and the use of cardiovascular medications on cognitive function. Thyroid hormones and biomarkers are associated with cognitive function, but the exact nature of the association is debatable. Longitudinal studies should clarify those associations. In addition, cross-sectional studies addressing other causes of cognitive decline in patients with CAD are warranted.