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

Analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms

BACKGROUND: Ruptured abdominal aortic aneurysms (AAAs) are the 13(th )leading cause of death in the United States. While AAA rupture may occur without significant warning, its risk assessment is generally based on critical values of the maximum AAA diameter (>5 cm) and AAA-growth rate (>0.5 cm/year). These criteria may be insufficient for reliable AAA-rupture risk assessment especially when predicting possible rupture of smaller AAAs. METHODS: Based on clinical evidence, eight biomechanical factors with associated weighting coefficients were determined and summed up in terms of a dimensionless, time-dependent severity parameter, SP(t). The most important factor is the maximum wall stress for which a semi-empirical correlation has been developed. RESULTS: The patient-specific SP(t) indicates the risk level of AAA rupture and provides a threshold value when surgical intervention becomes necessary. The severity parameter was validated with four clinical cases and its application is demonstrated for two AAA cases. CONCLUSION: As part of computational AAA-risk assessment and medical management, a patient-specific severity parameter 0 < SP(t) < 1.0 has been developed. The time-dependent, normalized SP(t) depends on eight biomechanical factors, to be obtained via a patient's pressure and AAA-geometry measurements. The resulting program is an easy-to-use tool which allows medical practitioners to make scientific diagnoses, which may save lives and should lead to an improved quality of life

Customer emotions in service failure and recovery encounters

Emotions play a significant role in the workplace, and considerable attention has been given to the study of employee emotions. Customers also play a central function in organizations, but much less is known about customer emotions. This chapter reviews the growing literature on customer emotions in employee–customer interfaces with a focus on service failure and recovery encounters, where emotions are heightened. It highlights emerging themes and key findings, addresses the measurement, modeling, and management of customer emotions, and identifies future research streams. Attention is given to emotional contagion, relationships between affective and cognitive processes, customer anger, customer rage, and individual differences

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Assessing the validity and responsiveness of disease-specific quality of life instruments in intermittent claudication

PurposeTo recommend a suitable disease-specific quality of life (QOL) instrument for use in intermittent claudication (IC) based on validity and responsiveness.MethodsSeventy claudicants completed two generic (SF36 and EUROQOL) and three disease-specific (CLAUS, VASCUQOL and SIPIC) QOL instruments prior to and 6 months after treatment (angioplasty or conservative therapy). Ankle brachial pressure indices and treadmill walking distances were measured at each assessment and International Society of Cardiovascular Surgery (ISCVS) recommended outcome measures were used to stratify the results. Construct and convergent-divergent validity was assessed for the three disease-specific QOL instruments. Responsiveness was assessed using effect sizes (effect size &gt;0.5 is clinically significant).ResultsAll clinical indicators improved significantly following treatment. All five domains of CLAUS, the VASCUQOL and SIPIC showed highly significant spearman correlation with intermittent claudication distance (ICD) and maximum walking distance (MWD) (0.267-0.697, p=0.01), suggesting good construct validity. There was greater correlation between like domains of CLAUS and SF36 than non-like domains suggesting good convergent-divergent validity. Pain domain of CLAUS and VASCUQOL could detect mild clinical improvement significantly (effect sizes 0.55 and 0.67). Pain and everyday life domain of CLAUS and the VASCUQOL could detect moderate clinical improvement significantly (effect sizes 0.7, 0.74 and 0.56, respectively).ConclusionThe three disease-specific QOL instruments (CLAUS, VASCUQOL, SIPIC) showed a high degree of construct and convergent-divergent validity. Amongst the three disease-specific QOL instruments, the VASCUQOL was most responsive and we would recommend its use in clinical practice

Functional distributional clustering using spatio-temporal data

This paper presents a new method called the functional distributional clustering algorithm (FDCA) that seeks to identify spatially contiguous clusters and incorporate changes in temporal patterns across overcrowded networks. This method is motivated by a graph-based network composed of sensors arranged over space where recorded observations for each sensor represent a multi-modal distribution. The proposed method is fully non-parametric and generates clusters within an agglomerative hierarchical clustering approach based on a measure of distance that defines a cumulative distribution function over temporal changes for different locations in space. Traditional hierarchical clustering algorithms that are spatially adapted do not typically accommodate the temporal characteristics of the underlying data. The effectiveness of the FDCA is illustrated using an application to both empirical and simulated data from about 400 sensors in a 2.5 square miles network area in downtown San Francisco, California. The results demonstrate the superior ability of the the FDCA in identifying true clusters compared to functional only and distributional only algorithms and similar performance to a model-based clustering algorithm