A proposed modification to the Kellgren and Lawrence classification for knee osteoarthritis using a compartment-specific approach.

Purpose: Since Kellgren and Lawrence (KL) originally classified knee osteoarthritis, several authors have reported varying levels of reliability and a lack of uniformity in the use of this classification system. We propose several modifications to the KL classification including the use of a compartment-specific approach that we hypothesize will lead to a better understanding of knee OA while maintaining an adequate interobserver and intraobserver reliability.

Methods: We propose the addition of the lateral and skyline-view radiographs to the standard anteroposterior (AP) and lateral projections in the evaluation.

COVSIM: A stochastic agent-based COVID-19 SIMulation model for North Carolina.

We document the evolution and use of the stochastic agent-based COVID-19 simulation model (COVSIM) to study the impact of population behaviors and public health policy on disease spread within age, race/ethnicity, and urbanicity subpopulations in North Carolina. We detail the methodologies used to model the complexities of COVID-19, including multiple agent attributes (i.e.

Evaluating the potential impact of rubella-containing vaccine introduction on congenital rubella syndrome in Afghanistan, Dem. Republic of Congo, Ethiopia, Nigeria, and Pakistan: A mathematical modeling study.

We assessed the potential impact of introducing rubella-containing vaccine (RCV) on congenital rubella syndrome (CRS) incidence in Afghanistan (AFG), Democratic Republic of Congo (COD), Ethiopia (ETH), Nigeria (NGA), and Pakistan (PAK). We simulated several RCV introduction scenarios over 30 years using a validated mathematical model. Our findings indicate that RCV introduction could avert between 86,000 and 535,000 CRS births, preventing 2.

Squamous Cell Carcinoma In Situ of the Breast With the Configuration of an Intraductal Papilloma.

A 64-year-old woman presented to our institution with a palpable and painful left breast mass. She denied any other breast symptoms. Subsequent imaging classified it as a US Breast Imaging-Reporting and Data System (BI-RADS) 4A lesion.

Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty.

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.

Quantifying association and disparities between diabetes complications and COVID-19 outcomes: A retrospective study using electronic health records.

Background: Despite established relationships between diabetic status and an increased risk for COVID-19 severe outcomes, there is a limited number of studies examining the relationships between diabetes complications and COVID-19-related risks. We use the Adapted Diabetes Complications Severity Index to define seven diabetes complications. We aim to understand the risk for COVID-19 infection, hospitalization, mortality, and longer length of stay of diabetes patients with complications.

Informing pandemic response in the face of uncertainty. .

Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible under defined scenarios that specify the future state of critical epidemic drivers, with the additional benefit that such scenarios can be used to anticipate the comparative effect of control measures. Since December 2020, the U.

Engaging stakeholders in the use of an interactive simulation tool to support decision-making about the implementation of colorectal cancer screening interventions.

Purpose: We aimed to understand how an interactive, web-based simulation tool can be optimized to support decision-making about the implementation of evidence-based interventions (EBIs) for improving colorectal cancer (CRC) screening.

Methods: Interviews were conducted with decision-makers, including health administrators, advocates, and researchers, with a strong foundation in CRC prevention. Following a demonstration of the microsimulation modeling tool, participants reflected on the tool's potential impact for informing the selection and implementation of strategies for improving CRC screening and outcomes.

Can vaccine prioritization reduce disparities in COVID-19 burden for historically marginalized populations?

SARS-CoV-2 vaccination strategies were designed to reduce COVID-19 mortality, morbidity, and health inequities. To assess the impact of vaccination strategies on disparities in COVID-19 burden among historically marginalized populations (HMPs), e.g.

Cerebral arteriopathy and ischemic stroke in a pediatric MYH11 patient.

Objectives: Mutations in the MYH11 gene result in smooth muscle cell dysfunction and are associated with familial thoracic aortic aneurysms and dissection. We describe a pediatric patient with a stroke and a pathogenic MYH11 IVS32G>A mutation, and a phenotype similar to ACTA2.

Methods: A proband girl with an acute ischemic stroke underwent genetic analysis and 7T high-resolution MRI.

Modeling the Impact of Nonpharmaceutical Interventions on COVID-19 Transmission in K-12 Schools.

Unlabelled: The novel coronavirus SARS-CoV-2 spread across the world causing many waves of COVID-19. Children were at high risk of being exposed to the disease because they were not eligible for vaccination during the first 20 mo of the pandemic in the United States. While children 5 y and older are now eligible to receive a COVID-19 vaccine in the United States, vaccination rates remain low despite most schools returning to in-person instruction.

Cross-sector decision landscape in response to COVID-19: A qualitative network mapping analysis of North Carolina decision-makers.

Introduction: The COVID-19 pandemic response has demonstrated the interconnectedness of individuals, organizations, and other entities jointly contributing to the production of community health. This response has involved stakeholders from numerous sectors who have been faced with new decisions, objectives, and constraints. We examined the cross-sector organizational decision landscape that formed in response to the COVID-19 pandemic in North Carolina.

Use of Modeling to Inform Decision Making in North Carolina during the COVID-19 Pandemic: A Qualitative Study.

Unlabelled: The COVID-19 pandemic has popularized computer-based decision-support models, which are commonly used to inform decision making amidst complexity. Understanding what organizational decision makers prefer from these models is needed to inform model development during this and future crises. We recruited and interviewed decision makers from North Carolina across 9 sectors to understand organizational decision-making processes during the first year of the COVID-19 pandemic ( = 44).

Vaccinating children against COVID-19 is crucial to protect schools and communities.

To evaluate the joint impact of childhood vaccination rates and school masking policies on community transmission and severe outcomes due to COVID-19, we utilized a stochastic, agent-based simulation of North Carolina to test 24 health policy scenarios. In these scenarios, we varied the childhood (ages 5 to 19) vaccination rate relative to the adult's (ages 20 to 64) vaccination rate and the masking relaxation policies in schools. We measured the overall incidence of disease, COVID-19-related hospitalization, and mortality from 2021 July 1 to 2023 July 1.

Assessing the impact of multicomponent interventions on colorectal cancer screening through simulation: What would it take to reach national screening targets in North Carolina?

Healthy People 2020 and the National Colorectal Cancer Roundtable established colorectal cancer (CRC) screening targets of 70.5% and 80%, respectively. While evidence-based interventions (EBIs) have increased CRC screening, the ability to achieve these targets at the population level remains uncertain.

When History and Heterogeneity Matter: A Tutorial on the Impact of Markov Model Specifications in the Context of Colorectal Cancer Screening.

Background: Markov models are used in health research to simulate health care utilization and disease states over time. Health phenomena, however, are complex, and the memoryless assumption of Markov models may not appropriately represent reality. This tutorial provides guidance on the use of Markov models of different orders and stratification levels in health decision-analytic modeling.

Generation 1.5: Years in the United States and Other Factors Affecting Smoking Behaviors Among Asian Americans.

Introduction: Generation 1.5, immigrants who moved to a different country before adulthood, are hypothesized to have unique cognitive and behavioral patterns. We examined the possible differences in cigarette smoking between Asian subpopulations who arrived in the United States at different life stages.

Vaccinating Children Against COVID-19 is Essential Prior to the Removal of Non-Pharmaceutical Interventions.

Objectivess: To evaluate the joint impact of childhood vaccination rates and masking policies, in schools and workplaces, on community transmission and severe outcomes due to COVID-19.

Study Design: We utilized a stochastic, agent-based simulation of North Carolina, to evaluate the impact of 24 health policy decisions on overall incidence of disease, COVID-19 related hospitalization, and mortality from July 1, 2021-July 1, 2023.

Results: Universal mask removal in schools in January 2022 could lead to a 38.

Mask Interventions in K12 Schools Can Also Reduce Community Transmission in Fall 2021.

The dominance of the COVID-19 Delta variant has renewed questions about the impact of K12 school policies, including the role of masks, on disease burden. A recent study showed masks and testing could reduce infections in students, but failed to address the impact on the community, while another showed masking is critical to slow disease spread in communities, but did not consider school openings under Delta. We project the impact of school-masking on the community, which can inform policy decisions, and support healthcare system planning.

The SMART Framework: Selection of Machine Learning Algorithms With ReplicaTions-A Case Study on the Microvascular Complications of Diabetes.

Over 34 million people in the US have diabetes, a major cause of blindness, renal failure, and amputations. Machine learning (ML) models can predict high-risk patients to help prevent adverse outcomes. Selecting the 'best' prediction model for a given disease, population, and clinical application is challenging due to the hundreds of health-related ML models in the literature and the increasing availability of ML methodologies.

Association of Simulated COVID-19 Vaccination and Nonpharmaceutical Interventions With Infections, Hospitalizations, and Mortality.

Importance: Vaccination against SARS-CoV-2 has the potential to significantly reduce transmission and COVID-19 morbidity and mortality. The relative importance of vaccination strategies and nonpharmaceutical interventions (NPIs) is not well understood.

Objective: To assess the association of simulated COVID-19 vaccine efficacy and coverage scenarios with and without NPIs with infections, hospitalizations, and deaths.

High-Quality Masks Reduce COVID-19 Infections and Deaths in the US.

Objectives: To evaluate the effectiveness of widespread adoption of masks or face coverings to reduce community transmission of the SARS-CoV-2 virus that causes COVID-19.

Methods: We created an agent-based stochastic network simulation using a variant of the standard SEIR dynamic infectious disease model. We considered a mask order that was initiated 3.

The Joint Impact of COVID-19 Vaccination and Non-Pharmaceutical Interventions on Infections, Hospitalizations, and Mortality: An Agent-Based Simulation.

Background: Vaccination against SARS-CoV-2 has the potential to significantly reduce transmission and morbidity and mortality due to COVID-19. This modeling study simulated the comparative and joint impact of COVID-19 vaccine efficacy and coverage with and without non-pharmaceutical interventions (NPIs) on total infections, hospitalizations, and deaths.

Methods: An agent-based simulation model was employed to estimate incident SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths over 18 months for the State of North Carolina, a population of roughly 10.