Coordinated Strategy for a Model-Based Decision Support Tool for Coronavirus Disease,Utah, USA

The coronavirus disease pandemic has highlighted the key role epidemiologic models play in supporting public health decision-making. In particular, these models provide estimates of outbreak potential when data are scarce and decision-making is critical and urgent. We document the integrated modeling response used in the US state of Utah early in the coronavirus disease pandemic, which brought together a diverse set of technical experts and public health and healthcare officials and led to an evidence-based response to the pandemic. We describe how we adapted a standard epidemiologic model; harmonized the outputs across modeling groups; and maintained a constant dialogue with policymakers at multiple levels of government to produce timely, evidence-based, and coordinated public health recommendations and interventions during the first wave of the pandemic. This framework continues to support the state’s response to ongoing outbreaks and can be applied in other settings to address unique public health challenges.     

Effects of Posterior Tibial Slope on a Posterior Cruciate Retaining Total Knee Arthroplasty Kinematics and Kinetics

BackgroundIt has been hypothesized that increasing posterior tibial slope can influence condylar rollback and play a role in increasing knee flexion. However, the effects of tibial slope on knee kinematics are not well studied. The objective of this study is to assess the effects of tibial slope on femorotibial kinematics and kinetics for a posterior cruciate retaining total knee arthroplasty design.MethodsA validated forward solution model of the knee was implemented to predict the femorotibial biomechanics of a posterior cruciate retaining total knee arthroplasty with varied posterior slopes of 0°-8° at 2° intervals. All analyses were conducted on a weight-bearing deep knee bend activity.ResultsIncreasing the tibial slope shifted the femoral component posteriorly at full extension but decreased the overall femoral rollback throughout flexion. With no tibial slope, the lateral condyle contacted the polyethylene 6 mm posterior of the midline, but as the slope increased to 8°, the femur shifted an extra 5 mm, to 11 mm posterior of the tibial midline. Similar shifts were observed for the medial condyle, ranging from 7 mm posterior to 13 mm posterior, respectively. Increasing posterior slope decreased the posterior cruciate ligament tension and femorotibial contact force.ConclusionThe results of this study revealed that, although increasing the tibial slope shifted the femur posteriorly at full extension and maximum flexion, it reduced the amount of femoral rollback. Despite the lack of rollback, a more posterior location of condyles suggests lower chances of bearing impingement of the posterior femur and may explain why increasing slope may lead to higher knee flexion.     

Understanding the Main Predictors of Length of Stay After Total Hip Arthroplasty: Patient-Related or Procedure-Related Risk Factors?

BackgroundRemoving total hip arthroplasty (THA) from the Centers for Medicare & Medicaid Services (CMS) inpatient-only list allows Medicare to cover outpatient THA, driving hospitals to recommend outpatient surgery for appropriate patients and raising safety concerns over which patients’ admissions should remain inpatient. Thus, we aimed to determine the influence of patient-related and procedure-related risk factors as predictors of >1-day Length of Stay (LOS) after THA.MethodsA prospective cohort of 5281 patients underwent primary THA from 2016 to 2019. Risk factors were categorized as patient-related or procedure-related. Multivariable cumulative link models identified significant predictors for 1-day, 2-day, and ≥3-day LOS. Discriminating 1-day LOS from >1-day LOS, we compared performance between two regression models.ResultsA>1-day LOS was significantly associated with age, female gender, higher body mass index, higher Charlson Comorbidity Index, Medicare status, and higher Hip disability and Osteoarthritis Outcome Physical Function Shortform(HOOS-PS) and lower Veterans RAND12 Mental Component (VR-12 MCS) scores via the initial regression model that contained patient factors only. A second regression model included procedure-related risk factors and indicated that procedure-related risk factors explain LOS more effectively than patient-related risk factors alone, as Akaike information criterion (AIC) increased by approximately 1100 units upon removal from the model.ConclusionAlthough patient-related risk factors alone provide predictive value for LOS following THA, procedure-related risk factors remain the main drivers of predicting LOS. These findings encourage examination of which specific procedural risk factors should be targeted to optimize LOS when choosing between inpatient and outpatient THA, especially within a Medicare population.     

Methods to address metal artifacts in post-processed CT images – A do-it-yourself guide for orthopedic surgeons

Computed tomography (CT) scans are often used for postoperative imaging in orthopedics. In the presence of metallic hardware, artifacts are generated, which can hamper visualization of the CT images, and also render the study ineffective for 3-D printing. Various solutions are available to minimize metal artifacts, and radiologists can employ these before or after processing the CT study. However, the orthopedic surgeon may be faced with situations where the metal artifacts were not addressed. To counter such problems, we present three do-it-yourself (DIY) techniques that can be used to manage metal artifacts.     

Protocolo del Estudio Poblacional Multinivel de las Desigualdades Socioeconómicas en la Distribución Geográfica de la Incidencia,la Mortalidad y la Supervivencia Neta del Cáncer en España: Estudio DESOCANES

Incidence and mortality provide information on the burden of cancer morbidity and the potential years of life lost due to cancer. The Spanish Deprivation Index (SDI) has been developed as a standardized measure to study socioeconomic deprivation in Spain at the census tract level. In addition, SDI information can be combined with ecological variables at the population level and data from the High-Resolution European Studies in Cancer. The aim of this study is to characterize socioeconomic inequalities in incidence, excess mortality, premature mortality and net survival for three of the most incident cancers (lung, colon-rectum and breast) in Spain using the SDI. This national population-based study will assess the impact of socioeconomic inequalities using a multilevel modelling approach. Spatial analysis, multilevel modeling, net survival and economic impact assessment will be used. The results will be useful for supporting decision-making, planning, and management of public health interventions aimed at reducing the impact of socioeconomic inequalities in the diagnosis and prognosis of cancer patients in Spain.     

Estimating the number of averted illnesses and deaths as a result of vaccination against an influenza pandemic in nine low- and middle-income countries

BackgroundDuring the 2009 influenza A(H1N1)pdm09 pandemic, 77 countries received donated monovalent A(H1N1)pdm09 vaccine through the WHO Pandemic Influenza A(H1N1) Vaccine Deployment Initiative. However, 47% did not receive their first shipment until after the first wave of virus circulation, and 8% did not receive their first shipment until after the WHO declared the end of the pandemic. Arguably, these shipments were too late into the pandemic to have a substantial effect on virus transmission or disease burden during the first waves of the pandemic.ObjectivesIn order to evaluate the potential benefits of earlier vaccine availability, we estimated the number of illnesses and deaths that could be averted during a 2009-like influenza pandemic under five different vaccine-availability timing scenarios.MethodsWe adapted a model originally developed to estimate annual influenza morbidity and mortality burden averted through US seasonal vaccination and ran it for five vaccine availability timing scenarios in nine low- and middle-income countries that received donated vaccine.ResultsAmong nine study countries, we estimated that the number of averted cases was 61–216,197 for actual vaccine receipt, increasing to 2,914–283,916 had vaccine been available simultaneously with the United States.ConclusionsEarlier delivery of vaccines can reduce influenza case counts during a simulated 2009-like pandemic in some low- and middle-income countries. For others, increasing the number of cases and deaths prevented through vaccination may be dependent on factors other than timely initiation of vaccine administration, such as distribution and administration capacity.     

Clinical prediction models to predict the risk of multiple binary outcomes: a comparison of approaches

Clinical prediction models (CPMs) can predict clinically relevant outcomes or events. Typically, prognostic CPMs are derived to predict the risk of a single future outcome. However, there are many medical applications where two or more outcomes are of interest, meaning this should be more widely reflected in CPMs so they can accurately estimate the joint risk of multiple outcomes simultaneously. A potentially naïve approach to multi‐outcome risk prediction is to derive a CPM for each outcome separately, then multiply the predicted risks. This approach is only valid if the outcomes are conditionally independent given the covariates, and it fails to exploit the potential relationships between the outcomes. This paper outlines several approaches that could be used to develop CPMs for multiple binary outcomes. We consider four methods, ranging in complexity and conditional independence assumptions: namely, probabilistic classifier chain, multinomial logistic regression, multivariate logistic regression, and a Bayesian probit model. These are compared with methods that rely on conditional independence: separate univariate CPMs and stacked regression. Employing a simulation study and real‐world example, we illustrate that CPMs for joint risk prediction of multiple outcomes should only be derived using methods that model the residual correlation between outcomes. In such a situation, our results suggest that probabilistic classification chains, multinomial logistic regression or the Bayesian probit model are all appropriate choices. We call into question the development of CPMs for each outcome in isolation when multiple correlated or structurally related outcomes are of interest and recommend more multivariate approaches to risk prediction.     

Modeling Deformation-Induced Fluid Flow in Cortical Bone’s Canalicular–Lacunar System

To explore the potential role that load-induced fluid flow plays as a mechano–transduction mechanism in bone adaptation, a lacunar–canalicular scale bone poroelasticity model is developed and implemented. The model uses micromechanics to homogenize the pericanalicular bone matrix, a system of straight circular cylinders in the bone matrix through which bone fluids can flow, as a locally anisotropic poroelastic medium. In this work, a simplified two-dimensional model of a periodic array of lacunae and their surrounding systems of canaliculi is used to quantify local fluid flow characteristics in the vicinity of a single lacuna. When the cortical bone model is loaded, microscale stress, and strain concentrations occur in the vicinity of individual lacunae and give rise to microscale spatial variations in the pore fluid pressure field. Furthermore, loading of the bone matrix containing canaliculi generates fluid pressures in the contained fluids. Consequently, loading of cortical bone induces fluid flow in the canaliculi and exchange of fluid between canaliculi and lacunae. For realistic bone morphology parameters, and a range of loading frequencies, fluid pressures and fluid–solid drag forces in the canalicular bone are computed and the associated energy dissipation in the models compared to that measured in physical in vitro experiments on human cortical bone. The proposed model indicates that deformation-induced fluid pressures in the lacunar–canalicular system have relaxation times on the order of milliseconds as opposed to the much shorter times (hundredths of milliseconds) associated with deformation-induced pressures in the Haversian system.     

An image-based modeling framework for patient-specific computational hemodynamics

We present a modeling framework designed for patient-specific computational hemodynamics to be performed in the context of large-scale studies. The framework takes advantage of the integration of image processing, geometric analysis and mesh generation techniques, with an accent on full automation and high-level interaction. Image segmentation is performed using implicit deformable models taking advantage of a novel approach for selective initialization of vascular branches, as well as of a strategy for the segmentation of small vessels. A robust definition of centerlines provides objective geometric criteria for the automation of surface editing and mesh generation. The framework is available as part of an open-source effort, the Vascular Modeling Toolkit, a first step towards the sharing of tools and data which will be necessary for computational hemodynamics to play a role in evidence-based medicine.     

The major T cell epitope on type II collagen is glycosylated in normal cartilage but modified by arthritis in both rats and humans

Type II collagen (CII) is a target for autoreactive T cells in both rheumatoid arthritis and the murine model collagen-induced arthritis. The determinant core of CII has been identified as CII260-270, and the alteration of this T cell epitope by posttranslational modifications is known to be critical for development of arthritis in mice. Using CII-specific T cell hybridomas we have now shown that the immunodominant T cell epitope in the normal (healthy) human and rat joint cartilage is O-glycosylated at the critical T cell receptor recognition position 264 with a mono- or di-saccharide attached to a hydroxylysine. In contrast, in the arthritic human and rat joint cartilage there are both glycosylated and non-glycosylated CII forms. Glycosylated CII from normal cartilage could not be recognized by T cells reactive to peptides having only lysine or hydroxylysine at position 264, showing that antigen-presenting cells could not degrade the O-linked carbohydrate. Thus, the variable forms of the glycosylated epitope are determined by the structures present in cartilage, and these vary during the disease course. We conclude that the chondrocyte determines the structures presented to the immune system and that these structures are different in normal versus arthritic states.