The Influence Of Regional Health System Characteristics On The Management Of Glioblastoma Multiforme

THE INFLUENCE OF REGIONAL HEALTH SYSTEM CHARACTERISTICS ON THE MANAGEMENT OF GLIOBLASTOMA MULTIFORME. Dhruv Khullar, Sanjay Aneja, James B. Yu. Department of Therapeutic Radiology, Yale University, School of Medicine, New Haven, CT. Despite a known optimal treatment protocol for the management of glioblastoma multiforme (GBM), many patients fail to receive complete surgical resection or post-operative radiation therapy (PORT). The underlying reasons behind this disparity are unclear. We hypothesize that regional health system resources influence the surgical management and PORT in patients with GBM. Surgical intervention, PORT receipt, and patient data for patients diagnosed with GBM from 2004 to 2008 were obtained from the NCI Surveillance, Epidemiology, and End Results (SEER) database and combined with the health system data from the Area Resource File. Health system characteristics studied included radiation oncologist density, neurosurgeon density, primary care provider (PCP) density, general radiation therapy (RT) and/or medical oncology (MO) equipped hospital density, and median household income. The geographic units of analysis were NCI-defined Health Service Areas (HSA) within the SEER registry. Four logistic models were constructed to test the effect of health system characteristics on surgical treatment choice and PORT receipt. Of the 8,337 patients in our sample that were diagnosed with GBM, 71.45% received PORT. We found that younger, married patients in HSAs with higher median incomes were significantly more likely to receive both gross total resection (p \u3c .001, p \u3c .001, p = 0.002) and PORT (p \u3c .001, p \u3c .001, p = .008). For every $10,000 increase in the median income of a HSA, a patient\u27s likelihood of receiving gross resection and PORT increased by 7% and 6.3%, respectively. The density of primary care providers and radiation oncology equipped hospitals were also significant predictors of PORT receipt (p = .024, p = .002). Patient race, radiation oncologist, and neurosurgeon densities were not associated with likelihood to receive PORT Our findings suggest that regional variations in neuro-oncology services and income may have impact on GBM management. The presence of hospitals with oncology services within an HSA was more predictive of PORT receipt than the density of radiation oncologists and neurosurgeons themselves, suggesting that hospital-level infrastructure is needed to optimize care of GBM, independent of physician staffing levels. Policies aimed at narrowing disparities in treatment may need to focus on addressing regional variations in oncology resources

The Problems of NATO's R2P Implementation in Libya: Has the international Community Learnt its Lesson?

The international community’s speedy and decisive response to Gaddafi’s brutal oppression of innocent civilians raised new optimism for effective cooperation in humanitarian protection. However, as the situation unravelled it became clear that the way Responsibility to Protect (R2P) was implemented in Libya it appeared to have confirmed the long-standing suspicions of several non-western nations, who often perceived that the doctrine may be used as a pretext for regime change. The crisis also highlighted the problem of the United Nation’s decision making process regarding the use of coercive action and the consequences of not assuming post-intervention Responsibility to Rebuild in conflict prone areas. This thesis evaluates the problems associated with NATO’s military intervention in Libya to draw upon the lessons that can be learnt for the doctrine of R2P. In addition, it also analyses how the international community has moved forward with these lessons. By examining the ‘Responsibility while Protecting’ and the ‘Code of Conduct’, the thesis argues that even though these two initiatives were significant developments, the international community has not yet learnt their lessons regarding R2P’s proper implementation for humanitarian protection missions. The thesis concludes with the suggestion that the use of force in global politics can sometimes be necessary and hence, future military interventions for humanitarian protection must be based on the criterions provided by the Just War Tradition (as specified in the original ICISS report), which will strengthen and legitimise R2P’s present framework

Combatting the privilege of attending elite institutions

Education privilege, both in terms of the level of qualifications attained and where these were attained, still permeates the workplace, despite there being insufficient links to better performance. Ipsitaa Khullar explores how education privilege interacts with social privilege, impacting income and social mobility. Moving forward, recruitment processes and internships must allow for success beyond education indicators

Combatting the privilege of attending elite institutions

Education privilege, both in terms of the level of qualifications attained and where these were attained, still permeates the workplace, despite there being insufficient links to better performance. Ipsitaa Khullar explores how education privilege interacts with social privilege, impacting income and social mobility. Moving forward, recruitment processes and internships must allow for success beyond education indicators

The Potential Adverse Reactions of Administering Combination Therapy in Covid-19 Patients

A definite treatment modality for coronavirus disease 2019 (COVID-19) has still not come into picture. With the rise of COVID-19 pandemic, a few drugs have come into light as empirical treatment for this infection. This review focusses on existing approaches to the treat COVID-19 patients with antimalarial drugs and antibiotics analyzing the adverse reactions and interactions of concomitantly administering these drugs. We will also discuss the possibilities of alternate methods to treat this disease

Beta thalassemia-induced osteoporosis: evaluating current and novel therapeutic options

Osteopenia and/or Osteoporosis (OOS) is becoming an increasingly prevalent chronic disease among Beta Thalassemia Major (BTM) patients, especially now that life expectancy in these patients has considerably improved through regular blood transfusions and iron chelation therapy. With several, complex genetic and acquired factors involved in its pathogenesis, coupled with the heterogeneity in the clinical response of BTM patients to different pharmacological agents, OOS has proven to be particularly difficult to treat. The great majority of treatment options currently available are not curative, but instead are aimed towards managing the symptoms and progression of the disease in patients. General preventative measures, such as iron chelation therapy and hormonal replacement therapy (HRT), are instrumental aspects of the treatment plan; however, the incredible complexity of OOS necessitates an individualized, multidisciplinary approach to management, with a principal therapy that is safe and effective in patients, and that is accompanied by these other supportive measures. This review, through a comprehensive analysis of current literature, includes data from randomized, placebo-controlled trials, double blind and observational clinical studies, and suggests optimal therapeutic interventions for first-line management of OOS. It also addresses treatment options for BTM patients in whom resistance to the recommended first-line therapy develops, or who display secondary endocrine conditions contributing to OOS. In addition to providing a current synopsis of OOS management and the potential of emerging treatment options, this analysis highlights some of the limitations of traditional therapies. In this way, the paper effectively illustrates the current status of TM-induced OOS; it describes what is or isn’t working, as well as underscores the diagnostic and therapeutic challenges continually faced by patients, researchers and clinicians

Development and Implementation of Novel Bristle Tool for Surface Treatment of Metallic Components

Despite advances in paints and coatings technology, protective coatings are prone to eventual corrosion, degradation and/or failure. Consequently, a corrosive layer will develop that can undermine the performance and integrity of structural components. Therefore, both the corrosive layer and defunct coating must be periodically removed, and an acceptable level of surface cleanliness and texture must be obtained prior to the reapplication of new paint. Currently, an array of processes and equipment are used for efficiently cleaning and conditioning metallic surfaces, such as grit blasting, needle guns, and a variety of non-woven and coated abrasive tools. This research investigates the method termed the bristle blasting process. The process utilizes a specially designed rotary bristle tool, which is dynamically tuned to a power tool spindle that operates at approximately 2,500 rpm. The present research suggests that the repeated collision of hardened bristle tips with a corroded steel surface results in both the removal of a friable corrosive layer and simultaneous exposure of fresh subsurface material. Surfaces generated by the bristle blast process are shown to mimic the visual cleanliness and anchor profile that is characteristic of grit blasting processes. One particular application evaluated during this research was offshore pipeline refurbishment and pre-treatment of weld seams prior to the application of protective coatings. Comparative analysis was done with conventional methods of surface treatment on the basis of visual cleanliness, surface profile generation and coating adhesion strength. The results obtained suggest that this novel technology performs better than the existing conventional power tool methods and is on an equal par with grit blasting methods. Moreover, the bristle blasting process is eco-friendly and does not use or generate hazardous waste, thereby providing a green approach to corrosion removal and surface preparation of steel components

A Better Looking Brain: Image Pre-Processing Approaches for fMRI Data

Researchers in the field of functional neuroimaging have faced a long standing problem in pre-processing low spatial resolution data without losing meaningful details within. Commonly, the brain function is recorded by a technique known as echo-planar imaging that represents the measure of blood flow (BOLD signal) through a particular location in the brain as an array of intensity values changing over time. This approach to record a movie of blood flow in the brain is known as fMRI. The neural activity is then studied from the temporal correlation patterns existing within the fMRI time series. However, the resulting images are noisy and contain low spatial detail, thus making it imperative to pre-process them appropriately to derive meaningful activation patterns. Two of the several standard preprocessing steps employed just before the analysis stage are denoising and normalization. Fundamentally, it is difficult to perfectly remove noise from an image without making assumptions about signal and noise distributions. A convenient and commonly used alternative is to smooth the image with a Gaussian filter, but this method suffers from various obvious drawbacks, primarily loss of spatial detail. A greater challenge arises when we attempt to derive average activation patterns from fMRI images acquired from a group of individuals. The brain of one individual differs from others in a structural sense as well as in a functional sense. Commonly, the inter-individual differences in anatomical structures are compensated for by co-registering each subject\u27s data to a common normalization space, known as spatial normalization. However, there are no existing methods to compensate for the differences in functional organization of the brain. This work presents first steps towards data-driven robust algorithms for fMRI image denoising and multi-subject image normalization by utilizing inherent information within fMRI data. In addition, a new validation approach based on spatial shape of the activation regions is presented to quantify the effects of preprocessing and also as a tool to record the differences in activation patterns between individual subjects or within two groups such as healthy controls and patients with mental illness. Qualititative and quantitative results of the proposed framework compare favorably against existing and widely used model-driven approaches such as Gaussian smoothing and structure-based spatial normalization. This work is intended to provide neuroscience researchers tools to derive more meaningful activation patterns to accurately identify imaging biomarkers for various neurodevelopmental diseases and also maximize the specificity of a diagnosis

Automatic multi-resolution spatio-frequency mottle metric (sfmm) for evaluation of macrouniformity

Evaluation of mottle is an area of on-going research in print quality assessment. We propose an unsupervised evaluation technique and a metric that measures mottle in a hard-copy laser print. The proposed algorithm uses a scanned image to quantify the low frequency variation or mottle in what is supposed to be a uniform field. `Banding\u27 and `Streaking\u27 effects are explicitly ignored and the proposed algorithm scales the test targets from Flat print (Good) to Noisy print (Bad) based on mottle only. The evaluation procedure is modeled as feature computation in different combinations of spatial, frequency and wavelet domains. The model is primarily independent of the nature of the input test target, i.e. whether it is chromatic or achromatic. The algorithm adapts accordingly and provides a mottle metric for any test target. The evaluation process is done using three major modules: (1) Pre-processing Stage, which includes acquisition of the test target and preparing it for processing; (2) Spatio-frequency Parameter Estimation where different features characterizing mottle are calculated in spatial and frequency domains; (3) Invalid Feature Removal Stage, where the invalid or insignificant features (in context to mottle) are eliminated and the dataset is ranked relatively. The algorithm was demonstrated successfully on a collection of 60 K-Only printed images spread over 2 datasets printed on 3 different faulty printers and 4 different media Also, it was tested on 5 color targets for the color version of the algorithm printed using 2 different printers and 5 different media, provided by Hewlett Packard Company