Fluid-structure interaction in abdominal aortic aneurysms: effects of asymmetry and wall thickness

BACKGROUND: Abdominal aortic aneurysm (AAA) is a prevalent disease which is of significant concern because of the morbidity associated with the continuing expansion of the abdominal aorta and its ultimate rupture. The transient interaction between blood flow and the wall contributes to wall stress which, if it exceeds the failure strength of the dilated arterial wall, will lead to aneurysm rupture. Utilizing a computational approach, the biomechanical environment of virtual AAAs can be evaluated to study the affects of asymmetry and wall thickness on this stress, two parameters that contribute to increased risk of aneurysm rupture. METHODS: Ten virtual aneurysm models were created with five different asymmetry parameters ranging from β = 0.2 to 1.0 and either a uniform or variable wall thickness to study the flow and wall dynamics by means of fully coupled fluid-structure interaction (FSI) analyses. The AAA wall was designed to have a (i) uniform 1.5 mm thickness or (ii) variable thickness ranging from 0.5 – 1.5 mm extruded normally from the boundary surface of the lumen. These models were meshed with linear hexahedral elements, imported into a commercial finite element code and analyzed under transient flow conditions. The method proposed was then compared with traditional computational solid stress techniques on the basis of peak wall stress predictions and cost of computational effort. RESULTS: The results provide quantitative predictions of flow patterns and wall mechanics as well as the effects of aneurysm asymmetry and wall thickness heterogeneity on the estimation of peak wall stress. These parameters affect the magnitude and distribution of Von Mises stresses; varying wall thickness increases the maximum Von Mises stress by 4 times its uniform thickness counterpart. A pre-peak systole retrograde flow was observed in the AAA sac for all models, which is due to the elastic energy stored in the compliant arterial wall and the expansion force of the artery during systole. CONCLUSION: Both wall thickness and geometry asymmetry affect the stress exhibited by a virtual AAA. Our results suggest that an asymmetric AAA with regional variations in wall thickness would be exposed to higher mechanical stresses and an increased risk of rupture than a more fusiform AAA with uniform wall thickness. Therefore, it is important to accurately reproduce vessel geometry and wall thickness in computational predictions of AAA biomechanics

Reconciling disparate prevalence rates of PTSD in large samples of US male Vietnam veterans and their controls

BACKGROUND: Two large independent studies funded by the US government have assessed the impact of the Vietnam War on the prevalence of PTSD in US veterans. The National Vietnam Veterans Readjustment Study (NVVRS) estimated the current PTSD prevalence to be 15.2% while the Vietnam Experience Study (VES) estimated the prevalence to be 2.2%. We compared alternative criteria for estimating the prevalence of PTSD using the NVVRS and VES public use data sets collected more than 10 years after the United States withdrew troops from Vietnam. METHODS: We applied uniform diagnostic procedures to the male veterans from the NVVRS and VES to estimate PTSD prevalences based on varying criteria including one-month and lifetime prevalence estimates, combat and non-combat prevalence estimates, and prevalence estimates using both single and multiple indicator models. RESULTS: Using a narrow and specific set of criteria, we derived current prevalence estimates for combat-related PTSD of 2.5% and 2.9% for the VES and the NVVRS, respectively. Using a more broad and sensitive set of criteria, we derived current prevalence estimates for combat-related PTSD of 12.2% and 15.8% for the VES and NVVRS, respectively. CONCLUSION: When comparable methods were applied to available data we reconciled disparate results and estimated similar current prevalences for both narrow and broad definitions of combat-related diagnoses of PTSD

New approaches to triglyceride reduction: Is there any hope left?

Triglycerides play a crucial role in the efficient storage of energy in the body. Mild and moderate hypertriglyceridemia (HTG) is a heterogeneous disorder with significant association with atherosclerotic cardiovascular disease (ASCVD), including myocardial infarction, ischemic stroke, and peripheral artery disease and represents an important component of the residual ASCVD risk in statin treated patients despite optimal low-density lipoprotein cholesterol reduction. Individuals with severe HTG (\u3e1,000 mg/dL) rarely develop atherosclerosis but have an incremental incidence of acute pancreatitis with significant morbidity and mortality. HTG can occur from a combination of genetic (both mono and polygenic) and environmental factors including poor diet, low physical activity, obesity, medications, and diseases like insulin resistance and other endocrine pathologies. HTG represents a potential target for ASCVD risk and pancreatitis risk reduction, however data on ASCVD reduction by treating HTG is still lacking and HTG-associated acute pancreatitis occurs too rarely to effectively demonstrate treatment benefit. In this review, we address the key aspects of HTG pathophysiology and examine the mechanisms and background of current and emerging therapies in the management of HTG

A Definitive Prognostication System for Patients With Thoracic Malignancies Diagnosed With Coronavirus Disease 2019: an update from the TERAVOLT registry

BACKGROUND: Patients with thoracic malignancies are at increased risk for mortality from Coronavirus disease 2019 (COVID-19) and large number of intertwined prognostic variables have been identified so far. METHODS: Capitalizing data from the TERAVOLT registry, a global study created with the aim of describing the impact of COVID-19 in patients with thoracic malignancies, we used a clustering approach, a fast-backward step-down selection procedure and a tree-based model to screen and optimize a broad panel of demographics, clinical COVID-19 and cancer characteristics. RESULTS: As of April 15, 2021, 1491 consecutive evaluable patients from 18 countries were included in the analysis. With a mean observation period of 42 days, 361 events were reported with an all-cause case fatality rate of 24.2%. The clustering procedure screened approximately 73 covariates in 13 clusters. A further multivariable logistic regression for the association between clusters and death was performed, resulting in five clusters significantly associated with the outcome. The fast-backward step-down selection then identified seven major determinants of death ECOG-PS (OR 2.47 1.87-3.26), neutrophil count (OR 2.46 1.76-3.44), serum procalcitonin (OR 2.37 1.64-3.43), development of pneumonia (OR 1.95 1.48-2.58), c-reactive protein (CRP) (OR 1.90 1.43-2.51), tumor stage at COVID-19 diagnosis (OR 1.97 1.46-2.66) and age (OR 1.71 1.29-2.26). The ROC analysis for death of the selected model confirmed its diagnostic ability (AUC 0.78; 95%CI: 0.75 - 0.81). The nomogram was able to classify the COVID-19 mortality in an interval ranging from 8% to 90% and the tree-based model recognized ECOG-PS, neutrophil count and CRP as the major determinants of prognosis. CONCLUSION: From 73 variables analyzed, seven major determinants of death have been identified. Poor ECOG-PS demonstrated the strongest association with poor outcome from COVID-19. With our analysis we provide clinicians with a definitive prognostication system to help determine the risk of mortality for patients with thoracic malignancies and COVID-19