One-Year Analysis of the Prospective Multicenter SENTRY Clinical Trial: Safety and Effectiveness of the Novate Sentry Bioconvertible Inferior Vena Cava Filter

Purpose To prospectively assess the Sentry bioconvertible inferior vena cava (IVC) filter in patients requiring temporary protection against pulmonary embolism (PE). Materials and Methods At 23 sites, 129 patients with documented deep vein thrombosis (DVT) or PE, or at temporary risk of developing DVT or PE, unable to use anticoagulation were enrolled. The primary end point was clinical success, including successful filter deployment, freedom from new symptomatic PE through 60 days before filter bioconversion, and 6-month freedom from filter-related complications. Patients were monitored by means of radiography, computerized tomography (CT), and CT venography to assess filtering configuration through 60 days, filter bioconversion, and incidence of PE and filter-related complications through 12 months. Results Clinical success was achieved in 111 of 114 evaluable patients (97.4%, 95% confidence interval [CI] 92.5%–99.1%). The rate of freedom from new symptomatic PE through 60 days was 100% (n = 129, 95% CI 97.1%–100.0%), and there were no cases of PE through 12 months for either therapeutic or prophylactic indications. Two patients (1.6%) developed symptomatic caval thrombosis during the first month; neither experienced recurrence after successful interventions. There was no filter tilting, migration, embolization, fracture, or caval perforation by the filter, and no filter-related death through 12 months. Filter bioconversion was successful for 95.7% (110/115) at 6 months and for 96.4% (106/110) at 12 months. Conclusions The Sentry IVC filter provided safe and effective protection against PE, with a high rate of intended bioconversion and a low rate of device-related complications, through 12 months of imaging-intense follow-up

A Systematic Review on the Diagnosis of Pediatric Bacterial Pneumonia: When Gold Is Bronze

In developing countries, pneumonia is one of the leading causes of death in children under five years of age and hence timely and accurate diagnosis is critical. In North America, pneumonia is also a common source of childhood morbidity and occasionally mortality. Clinicians traditionally have used the chest radiograph as the gold standard in the diagnosis of pneumonia, but they are becoming increasingly aware that it is not ideal. Numerous studies have shown that chest radiography findings lack precision in defining the etiology of childhood pneumonia. There is no single test that reliably distinguishes bacterial from non-bacterial causes. These factors have resulted in clinicians historically using a combination of physical signs and chest radiographs as a 'gold standard', though this combination of tests has been shown to be imperfect for diagnosis and assigning treatment. The objectives of this systematic review are to: 1) identify and categorize studies that have used single or multiple tests as a gold standard for assessing accuracy of other tests, and 2) given the 'gold standard' used, determine the accuracy of these other tests for diagnosing childhood bacterial pneumonia.Search strategies were developed using a combination of subject headings and keywords adapted for 18 electronic bibliographic databases from inception to May 2008. Published studies were included if they: 1) included children one month to 18 years of age, 2) provided sufficient data regarding diagnostic accuracy to construct a 2x2 table, and 3) assessed the accuracy of one or more index tests as compared with other test(s) used as a 'gold standard'. The literature search revealed 5,989 references of which 256 were screened for inclusion, resulting in 25 studies that satisfied all inclusion criteria. The studies examined a range of bacterium types and assessed the accuracy of several combinations of diagnostic tests. Eleven different gold standards were studied in the 25 included studies. Criterion validity was calculated for fourteen different index tests using eleven different gold standards. The most common gold standard utilized was blood culture tests used in six studies. Fourteen different tests were measured as index tests. PCT was the most common measured in five studies each with a different gold standard.We have found that studies assessing the diagnostic accuracy of clinical, radiological, and laboratory tests for bacterial childhood pneumonia have used a heterogeneous group of gold standards, and found, at least in part because of this, that index tests have widely different accuracies. These findings highlight the need for identifying a widely accepted gold standard for diagnosis of bacterial pneumonia in children

Projection-based model reduction: Formulations for physics-based machine learning

This paper considers the creation of parametric surrogate models for applications in science and engineering where the goal is to predict high-dimensional output quantities of interest, such as pressure, temperature and strain fields. The proposed methodology develops a low-dimensional parametrization of these quantities of interest using the proper orthogonal decomposition (POD), and combines this parametrization with machine learning methods to learn the map between the input parameters and the POD expansion coefficients. The use of particular solutions in the POD expansion provides a way to embed physical constraints, such as boundary conditions and other features of the solution that must be preserved. The relative costs and effectiveness of four different machine learning techniques—neural networks, multivariate polynomial regression, k-nearest-neighbors and decision trees—are explored through two engineering examples. The first example considers prediction of the pressure field around an airfoil, while the second considers prediction of the strain field over a damaged composite panel. The case studies demonstrate the importance of embedding physical constraints within learned models, and also highlight the important point that the amount of model training data available in an engineering setting is often much less than it is in other machine learning applications, making it essential to incorporate knowledge from physical models

Using Midlevel Providers in Interventional Radiology

Developing and implementing clinical services, including consultations, rounds, and clinic, is time-consuming, and for the interventional radiologist this means time away from the interventional laboratory. Using a team approach to providing clinical services is logical, and the midlevel provider is a perfect fit for an interventional radiology team. Midlevel providers can be grouped into two categories, advanced practice nurses (APNs) and physician's assistants (PAs). Under the umbrella of APN are several specialties including the nurse practitioner (NP), clinical nurse specialist (CNS), certified nurse midwife, and certified nurse anesthetist. The midlevel providers that are particularly suited for interventional radiology are the NPs, CNSs, and PAs. This article discusses midlevel providers in-depth including skills, limitations, and expenses

Coding Issues for Interventional Radiology: Get Paid for What You Do!

As interventional radiology continues to evolve into a true clinical practice, more time will be spent on the clinical decision process; this time is reimbursable in the form of evaluation and management (E&M) services. Once assumed to be an inherent part of the procedure itself, we know many procedures now do not include follow-up E&M components. Unfortunately, E&M coding is somewhat complex and requires rigorous documentation. Below is a discussion of the fundamentals of E&M services, general principles of documentation, and the mechanics of coverage and reimbursement