Diagnostic accuracy of convolutional neural network algorithms to distinguish gastrointestinal obstruction on conventional radiographs in a pediatric population.

Purpose: Gastrointestinal (GI) dilatations are frequently observed in radiographs of pediatric patients who visit emergency departments with acute symptoms such as vomiting, pain, constipation, or diarrhea. Timely and accurate differentiation of whether there is an obstruction requiring surgery in these patients is crucial to prevent complications such as necrosis and perforation, which can lead to death. In this study, we aimed to use convolutional neural network (CNN) models to differentiate healthy children with normal intestinal gas distribution in abdominal radiographs from those with GI dilatation or obstruction.

Evaluation of the Association between Lumbar Spinal Stenosis and Lumbar Subcutaneous Fat Tissue Thickness by MRI: A Novel Perspective.

Objective: To evaluate whether lumbar subcutaneous fat tissue thickness (LSFTT) on midsagittal magnetic resonance imaging (MRI) is associated with lumbar spinal stenosis (LSS).

Study Design: Observational cross-sectional study.

Place And Duration Of Study: Department of Radiology and Neurosurgery, Istanbul Medeniyet University School of Medicine, Istanbul, Turkey between January 2018 and December 2020.

[Evaluation of Non-Pharmaceutical Interventions for Reducing Contact Rate in COVID-19 Pandemic: R0 Estimation and Modeling for Istanbul].

After the declaration of the coronavirus-2019 (COVID-19) pandemic and the detection of the COVID-19 case in Turkey, a series of non-pharmaceutical measures were implemented to reduce the number of contacts at the national level. The aim of this study was to determine the change in the epidemic reproduction rate (R0) with non-pharmaceutical interventions including curfews starting with the first reported case in Istanbul and to evaluate the effectiveness of interventions by estimating the number of cases and deaths using a dynamic compartmental model. While keeping transmission probability (beta) as 3% and incubation period as seven days, we developed five scenarios that represented nonpharmaceutical interventions The first scenario was "if nothing was done" and the last scenario was "curfew".

Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys.

Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions.

Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys.

Comparisons of the utility and accuracy of methods for measuring social interactions relevant to disease transmission are rare. To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area. Although the number and type of contacts recorded by each participant differed between the two methods, we found good correspondence between the two methods in aggregate measures of age-specific interactions.

Association between physician adoption of a new oral anti-diabetic medication and Medicare and Medicaid drug spending.

Background: In the United States, there is well-documented regional variation in prescription drug spending. However, the specific role of physician adoption of brand name drugs on the variation in patient-level prescription drug spending is still being investigated across a multitude of drug classes. Our study aims to add to the literature by determining the association between physician adoption of a first-in-class anti-diabetic (AD) drug, sitagliptin, and AD drug spending in the Medicare and Medicaid populations in Pennsylvania.

Anterior third ventricular height and infundibulochiasmatic angle: two novel measurements to predict clinical success of endoscopic third ventriculostomy in the early postoperative period.

Objective: The authors sought to develop a set of parameters that reliably predict the clinical success of endoscopic third ventriculostomy (ETV) when assessed before and after the operation, and to establish a plan for MRI follow-up after this procedure.

Methods: This retrospective study involved 77 patients who had undergone 78 ETV procedures for obstructive hydrocephalus between 2010 and 2015. Constructive interference in steady-state (CISS) MRI evaluations before and after ETV were reviewed, and 4 parameters were measured.

Ossicular chain erosion in chronic otitis media patients with cholesteatoma or granulation tissue or without those: analysis of 915 cases.

Purpose: The aim of this study was to evaluate the ossicular chain erosions (OCE) in chronic otitis media patients with cholesteatoma (COM-C) or without cholesteatoma (COM).

Materials And Methods: The OCE and preoperative hearing levels of a total of 915 patients were evaluated retrospectively. Patients were divided into three groups.

Influence of peer networks on physician adoption of new drugs.

Although physicians learn about new medical technologies from their peers, the magnitude and source of peer influence is unknown. We estimate the effect of peer adoption of three first-in-class medications (dabigatran, sitigliptin, and aliskiren) on physicians' own adoption of those medications. We included 11,958 physicians in Pennsylvania prescribing anticoagulant, antidiabetic, and antihypertensive medications.

Patterns and predictors of physician adoption of new cardiovascular drugs.

Background: Little is known about physicians' approaches to adopting new cardiovascular drugs and how adoption varies between drugs of differing novelty.

Methods: Using data on dispensed prescriptions from IMS Health's Xponent™ database, we created a cohort of all primary care physicians (PCPs) and cardiologists in Pennsylvania who regularly prescribed anticoagulants, antihypertensives and statins from 2007 to 2011. We examined prescribing of three new cardiovascular drugs of differing novelty: dabigatran, aliskiren and pitavastatin.

Impact on Primary Care Access Post-Disaster: A Case Study From the Rockaway Peninsula.

Objective: Assess Hurricane Sandy's impact on primary care providers' services in the Rockaways.

Methods: In-person surveys were conducted in 2014. A list of 46 health care sites in the area of interest was compiled and each site was called to offer participation in our survey.

Who Were the Early Adopters of Dabigatran?: An Application of Group-based Trajectory Models.

Background: Variation in physician adoption of new medications is poorly understood. Traditional approaches (eg, measuring time to first prescription) may mask substantial heterogeneity in technology adoption.

Objective: Apply group-based trajectory models to examine the physician adoption of dabigratran, a novel anticoagulant.

An Agent-Based Model for Addressing the Impact of a Disaster on Access to Primary Care Services.

Objective: Hurricane Sandy in the Rockaways, Queens, forced residents to evacuate and primary care providers to close or curtail operations. A large deficit in primary care access was apparent in the immediate aftermath of the storm. Our objective was to build a computational model to aid responders in planning to situate primary care services in a disaster-affected area.

Social Contact Networks and Mixing among Students in K-12 Schools in Pittsburgh, PA.

Students attending schools play an important role in the transmission of influenza. In this study, we present a social network analysis of contacts among 1,828 students in eight different schools in urban and suburban areas in and near Pittsburgh, Pennsylvania, United States of America, including elementary, elementary-middle, middle, and high schools. We collected social contact information of students who wore wireless sensor devices that regularly recorded other devices if they are within a distance of 3 meters.

State-level legal preparedness for nuclear and radiological emergencies in the U.S.: a network analysis of state laws and regulations.

Objective: This study explored if and to what extent the laws of U.S. states mirrored the U.

Aflatoxin regulations and global pistachio trade: insights from social network analysis.

Aflatoxins, carcinogenic toxins produced by Aspergillus fungi, contaminate maize, peanuts, and tree nuts in many regions of the world. Pistachios are the main source of human dietary aflatoxins from tree nuts worldwide. Over 120 countries have regulations for maximum allowable aflatoxin levels in food commodities.

FRED (a Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations.

Background: Mathematical and computational models provide valuable tools that help public health planners to evaluate competing health interventions, especially for novel circumstances that cannot be examined through observational or controlled studies, such as pandemic influenza. The spread of diseases like influenza depends on the mixing patterns within the population, and these mixing patterns depend in part on local factors including the spatial distribution and age structure of the population, the distribution of size and composition of households, employment status and commuting patterns of adults, and the size and age structure of schools. Finally, public health planners must take into account the health behavior patterns of the population, patterns that often vary according to socioeconomic factors such as race, household income, and education levels.

Global maize trade and food security: implications from a social network model.

In this study, we developed a social network model of the global trade of maize: one of the most important food, feed, and industrial crops worldwide, and critical to food security. We used this model to analyze patterns of maize trade among nations, and to determine where vulnerabilities in food security might arise if maize availability was decreased due to factors such as diversion to nonfood uses, climatic factors, or plant diseases. Using data on imports and exports from the U.

Aflatoxin regulations in a network of global maize trade.

Worldwide, food supplies often contain unavoidable contaminants, many of which adversely affect health and hence are subject to regulations of maximum tolerable levels in food. These regulations differ from nation to nation, and may affect patterns of food trade. We soughtto determine whether there is an association between nations' food safety regulations and global food trade patterns, with implications for public health and policymaking.

Modelling disease outbreaks in realistic urban social networks.

Most mathematical models for the spread of disease use differential equations based on uniform mixing assumptions or ad hoc models for the contact process. Here we explore the use of dynamic bipartite graphs to model the physical contact patterns that result from movements of individuals between specific locations. The graphs are generated by large-scale individual-based urban traffic simulations built on actual census, land-use and population-mobility data.