A Comprehensive Tool for Patient-Specific AAA Geometry and Biomechanics Assessment

Annual mortality from ruptured abdominal aortic aneurysm (AAA) in the United States alone is approximately 150,000, which is currently ranked as the 13th leading cause of death and the 10th leading cause of death in men over 55 years of age [1]. The vascular surgeon needs to weigh the risk of AAA rupture against the risk of surgical intervention to decide the best course of treatment. Several steps are involved when using computational techniques to evaluate risk of rupture [2], namely medical image segmentation, 3D reconstruction, finite element mesh generation, derivation of boundary conditions, specification of tissue material properties, etc. Currently, computational analysis of AAA biomechanics includes the use of multiple third-party commercial software tools to accomplish each of these steps, which makes its clinical implementation impractical, time-consuming and requiring to interface multiple software tools as this demands an engineering skill set. Additionally, the versatility of general purpose off-the-shelf software comes at the cost of simplifying assumptions regarding geometric modeling, limited user control and boundary conditions. This makes subsequent computational results vulnerable to inaccuracies. In this work, we describe the software tool AAAVASC, built on a MATLAB platform, with an integrated approach for image-based modeling and a novel pipeline that facilitates both geometry quantification and computational analysis of AAA biomechanics.

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On the Role and Effects of Uncertainties in Cardiovascular in silico Analyses

Frontiers in Medical Technology ◽

10.3389/fmedt.2021.748908 ◽

2021 ◽

Vol 3 ◽

Author(s):

Simona Celi ◽

Emanuele Vignali ◽

Katia Capellini ◽

Emanuele Gasparotti

Keyword(s):

Computational Analysis ◽

Rigid Wall ◽

Patient Specific ◽

Computational Techniques ◽

Error Sources ◽

Moving Wall ◽

Cardiovascular Hemodynamics ◽

Computational Fluid Dynamics Cfd ◽

Flow Pressure ◽

Different Levels

The assessment of cardiovascular hemodynamics with computational techniques is establishing its fundamental contribution within the world of modern clinics. Great research interest was focused on the aortic vessel. The study of aortic flow, pressure, and stresses is at the basis of the understanding of complex pathologies such as aneurysms. Nevertheless, the computational approaches are still affected by sources of errors and uncertainties. These phenomena occur at different levels of the computational analysis, and they also strongly depend on the type of approach adopted. With the current study, the effect of error sources was characterized for an aortic case. In particular, the geometry of a patient-specific aorta structure was segmented at different phases of a cardiac cycle to be adopted in a computational analysis. Different levels of surface smoothing were imposed to define their influence on the numerical results. After this, three different simulation methods were imposed on the same geometry: a rigid wall computational fluid dynamics (CFD), a moving-wall CFD based on radial basis functions (RBF) CFD, and a fluid-structure interaction (FSI) simulation. The differences of the implemented methods were defined in terms of wall shear stress (WSS) analysis. In particular, for all the cases reported, the systolic WSS and the time-averaged WSS (TAWSS) were defined.

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Commercial Fishing as an Occupational Determinant of Opioid Overdoses and Deaths of Despair in Two Massachusetts Fishing Ports, 2000–2014

NEW SOLUTIONS A Journal of Environmental and Occupational Health Policy ◽

10.1177/10482911211023476 ◽

2021 ◽

pp. 104829112110234

Author(s):

Scott Fulmer ◽

Shruti Jain ◽

David Kriebel

Keyword(s):

United States ◽

Cause Of Death ◽

Death Certificate ◽

The United States ◽

Opioid Overdose ◽

Commercial Fishing ◽

Opioid Epidemic ◽

Death Certificate Data ◽

Deaths Of Despair

The opioid epidemic has had disproportionate effects across various sectors of the population, differentially impacting various occupations. Commercial fishing has among the highest rates of occupational fatalities in the United States. This study used death certificate data from two Massachusetts fishing ports to calculate proportionate mortality ratios of fatal opioid overdose as a cause of death in commercial fishing. Statistically significant proportionate mortality ratios revealed that commercial fishermen were greater than four times more likely to die from opioid poisoning than nonfishermen living in the same fishing ports. These important quantitative findings suggest opioid overdoses, and deaths to diseases of despair in general, deserve further study in prevention, particularly among those employed in commercial fishing.

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Neurocognitive effects associated with proprotein convertase subtilisin-kexin type 9 inhibitor use: a narrative review

Therapeutic Advances in Drug Safety ◽

10.1177/2042098620959271 ◽

2021 ◽

Vol 12 ◽

pp. 204209862095927

Author(s):

Wei C. Yuet ◽

Didi Ebert ◽

Michael Jann

Keyword(s):

Cognitive Impairment ◽

Adverse Events ◽

The United States ◽

Narrative Review ◽

Lipid Lowering ◽

Patient Specific ◽

Proprotein Convertase ◽

Pcsk9 Inhibitors ◽

Pcsk9 Inhibitor ◽

Receptor Modulation

Neurocognitive adverse events have been observed with the widespread use of 3-hydroxy-3-methylglutaryl-CoA reductase inhibitors or “statins,” which reduce low-density lipoprotein cholesterol (LDL-C) levels and subsequently cardiovascular risk. The United States Food and Drug Association directed manufacturers of proprotein convertase subtilisin-kexin type 9 (PCSK9) inhibitors to monitor for neurocognitive adverse events due to their potent effects on LDL-C reduction, which is a proposed mechanism for neuronal cell dysfunction. Other proposed mechanisms for PCSK9 inhibitor-associated neurocognitive adverse events include N-methyl-d-aspartate receptor modulation, dysregulation of lipid and glucose metabolism, and patient-specific risk factors for cognitive impairment. The purpose of this narrative review article is to describe the proposed mechanisms, incidence of neurocognitive adverse events from phase II and III trials for PCSK9 inhibitors, neurocognitive assessments utilized in clinical trials, and clinical implications. Given the increasing prevalence of PCSK9 inhibitor use and the neurocognitive adverse events observed with prior lipid-lowering therapies, clinicians should be aware of the risks associated with PCSK9 inhibitors, especially when therapy is indicated for patients at high risk for cardiovascular events. Overall, the incidence of PCSK9 inhibitor-associated neurocognitive appears to be uncommon. However, additional prospective studies evaluating cognitive impairment may be beneficial to determine the long-term safety of these agents.

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Patient-Specific Predictive Antibiogram in Decision Support for Empiric Antibiotic Treatment

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.1205 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s521-s522

Author(s):

Debarka Sengupta ◽

Vaibhav Singh ◽

Seema Singh ◽

Dinesh Tewari ◽

Mudit Kapoor ◽

...

Keyword(s):

Machine Learning ◽

Antimicrobial Resistance ◽

Model Building ◽

Medical Center ◽

Bacterial Species ◽

Model Performance ◽

The United States ◽

Patient Specific ◽

Gradient Boosting ◽

Comparative Performance

Background: The rising trend of antibiotic resistance imposes a heavy burden on healthcare both clinically and economically (US$55 billion), with 23,000 estimated annual deaths in the United States as well as increased length of stay and morbidity. Machine-learning–based methods have, of late, been used for leveraging patient’s clinical history and demographic information to predict antimicrobial resistance. We developed a machine-learning model ensemble that maximizes the accuracy of such a drug-sensitivity versus resistivity classification system compared to the existing best-practice methods. Methods: We first performed a comprehensive analysis of the association between infecting bacterial species and patient factors, including patient demographics, comorbidities, and certain healthcare-specific features. We leveraged the predictable nature of these complex associations to infer patient-specific antibiotic sensitivities. Various base-learners, including k-NN (k-nearest neighbors) and gradient boosting machine (GBM), were used to train an ensemble model for confident prediction of antimicrobial susceptibilities. Base learner selection and model performance evaluation was performed carefully using a variety of standard metrics, namely accuracy, precision, recall, F1 score, and Cohen κ. Results: For validating the performance on MIMIC-III database harboring deidentified clinical data of 53,423 distinct patient admissions between 2001 and 2012, in the intensive care units (ICUs) of the Beth Israel Deaconess Medical Center in Boston, Massachusetts. From ~11,000 positive cultures, we used 4 major specimen types namely urine, sputum, blood, and pus swab for evaluation of the model performance. Figure 1 shows the receiver operating characteristic (ROC) curves obtained for bloodstream infection cases upon model building and prediction on 70:30 split of the data. We received area under the curve (AUC) values of 0.88, 0.92, 0.92, and 0.94 for urine, sputum, blood, and pus swab samples, respectively. Figure 2 shows the comparative performance of our proposed method as well as some off-the-shelf classification algorithms. Conclusions: Highly accurate, patient-specific predictive antibiogram (PSPA) data can aid clinicians significantly in antibiotic recommendation in ICU, thereby accelerating patient recovery and curbing antimicrobial resistance.Funding: This study was supported by Circle of Life Healthcare Pvt. Ltd.Disclosures: None

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Shooting from the ‘Scrip: Scope of Practice Laws and Access to Immunizations in the Pharmacy Setting

Vaccines ◽

10.3390/vaccines9050444 ◽

2021 ◽

Vol 9 (5) ◽

pp. 444

Author(s):

Charles Stoecker

Keyword(s):

Positive Impact ◽

National Level ◽

State Level ◽

The United States ◽

Scope Of Practice ◽

Patient Specific ◽

Behavioral Risk ◽

Influenza Immunization ◽

Immunization Rates ◽

The Impact

In the past two decades, most states in the United States have added authorization for pharmacists to administer some vaccinations. Expansions of this authority have also come with prescription requirements or other regulatory burdens. The objective of this study was to evaluate the impact of these expansions on influenza immunization rates in adults age 65 and over. A panel data, differences-in-differences regression framework to control for state-level unobserved confounders and shocks at the national level was used on a combination of a dataset of state-level statute and regulatory changes and influenza immunization data from the Behavioral Risk Factor Surveillance System. Giving pharmacists permission to vaccinate had a positive impact on adult influenza immunization rates of 1.4 percentage points for adults age 65 and over. This effect was diminished by the presence of laws requiring pharmacists to obtain patient-specific prescriptions. There was no evidence that allowing pharmacists to administer vaccinations led patients to have fewer annual check-ups with physicians or not have a usual source of health care. Expanding pharmacists’ scope of practice laws to include administering the influenza vaccine had a positive impact on influenza shot uptake. This may have implications for relaxing restrictions on other forms of care that could be provided by pharmacists.

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Changes in U.S. East Coast Cyclone Dynamics with Climate Change

Journal of Climate ◽

10.1175/jcli-d-14-00418.1 ◽

2015 ◽

Vol 28 (2) ◽

pp. 468-484 ◽

Cited By ~ 29

Author(s):

Christopher G. Marciano ◽

Gary M. Lackmann ◽

Walter A. Robinson

Keyword(s):

Climate Change ◽

Boundary Conditions ◽

Potential Vorticity ◽

East Coast ◽

The United States ◽

Sea Level Pressure ◽

Cyclone Intensity ◽

Field Amplification ◽

Lateral Boundary Conditions ◽

Relative Potential

Abstract Previous studies investigating the impacts of climate change on extratropical cyclones have primarily focused on changes in the frequency, intensity, and distribution of these events. Fewer studies have directly investigated changes in the storm-scale dynamics of individual cyclones. Precipitation associated with these events is projected to increase with warming owing to increased atmospheric water vapor content. This presents the potential for enhancement of cyclone intensity through increased lower-tropospheric diabatic potential vorticity generation. This hypothesis is tested using the Weather Research and Forecasting Model to simulate individual wintertime extratropical cyclone events along the United States East Coast in present-day and future thermodynamic environments. Thermodynamic changes derived from an ensemble of GCMs for the IPCC Fourth Assessment Report (AR4) A2 emissions scenario are applied to analyzed initial and lateral boundary conditions of observed strongly developing cyclone events, holding relative humidity constant. The perturbed boundary conditions are then used to drive future simulations of these strongly developing events. Present-to-future changes in the storm-scale dynamics are assessed using Earth-relative and storm-relative compositing. Precipitation increases at a rate slightly less than that dictated by the Clausius–Clapeyron relation with warming. Increases in cyclone intensity are seen in the form of minimum sea level pressure decreases and a strengthened 10-m wind field. Amplification of the low-level jet occurs because of the enhancement of latent heating. Storm-relative potential vorticity diagnostics indicate a strengthening of diabatic potential vorticity near the cyclone center, thus supporting the hypothesis that enhanced latent heat release is responsible for this regional increase in future cyclone intensity.

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Cyclic Breathing Simulations in Large Scale Models of the Lung Airway From the Oronasal Opening to the Terminal Bronchioles

Volume 2: Biomedical and Biotechnology ◽

10.1115/imece2012-88901 ◽

2012 ◽

Author(s):

D. Keith Walters ◽

Greg W. Burgreen ◽

Robert L. Hester ◽

David S. Thompson ◽

David M. Lavallee ◽

...

Keyword(s):

Steady State ◽

Boundary Conditions ◽

Large Scale ◽

Whole Body ◽

Patient Specific ◽

Cfd Simulations ◽

Reduced Order ◽

Scale Models ◽

Steady State Simulation ◽

Conducting Zone

Computational fluid dynamics (CFD) simulations were performed for unsteady periodic breathing conditions, using large-scale models of the human lung airway. The computational domain included fully coupled representations of the orotracheal region and large conducting zone up to generation four (G4) obtained from patient-specific CT data, and the small conducting zone (to G16) obtained from a stochastically generated airway tree with statistically realistic geometrical characteristics. A reduced-order geometry was used, in which several airway branches in each generation were truncated, and only select flow paths were retained to G16. The inlet and outlet flow boundaries corresponded to the oronasal opening (superior), the inlet/outlet planes in terminal bronchioles (distal), and the unresolved airway boundaries arising from the truncation procedure (intermediate). The cyclic flow was specified according to the predicted ventilation patterns for a healthy adult male at three different activity levels, supplied by the whole-body modeling software HumMod. The CFD simulations were performed using Ansys FLUENT. The mass flow distribution at the distal boundaries was prescribed using a previously documented methodology, in which the percentage of the total flow for each boundary was first determined from a steady-state simulation with an applied flow rate equal to the average during the inhalation phase of the breathing cycle. The distal pressure boundary conditions for the steady-state simulation were set using a stochastic coupling procedure to ensure physiologically realistic flow conditions. The results show that: 1) physiologically realistic flow is obtained in the model, in terms of cyclic mass conservation and approximately uniform pressure distribution in the distal airways; 2) the predicted alveolar pressure is in good agreement with previously documented values; and 3) the use of reduced-order geometry modeling allows accurate and efficient simulation of large-scale breathing lung flow, provided care is taken to use a physiologically realistic geometry and to properly address the unsteady boundary conditions.

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