Recurrence of Ganglion Cysts Following Re-excision

Previous studies have examined the recurrence of ganglion cysts after surgical excision at a rate of 4 to 40%. However, recurrence after revision surgical excision is unknown. The purpose of this study was to define the incidence of recurrent ganglion cysts in patients who underwent a 2nd excisional procedure.https://jdc.jefferson.edu/cwicposters/1032/thumbnail.jp

Semi-supervised Quality Evaluation of Colonoscopy Procedures

Colonoscopy is the standard of care technique for detecting and removing polyps for the prevention of colorectal cancer. Nevertheless, gastroenterologists (GI) routinely miss approximately 25% of polyps during colonoscopies. These misses are highly operator dependent, influenced by the physician skills, experience, vigilance, and fatigue. Standard quality metrics, such as Withdrawal Time or Cecal Intubation Rate, have been shown to be well correlated with Adenoma Detection Rate (ADR). However, those metrics are limited in their ability to assess the quality of a specific procedure, and they do not address quality aspects related to the style or technique of the examination. In this work we design novel online and offline quality metrics, based on visual appearance quality criteria learned by an ML model in an unsupervised way. Furthermore, we evaluate the likelihood of detecting an existing polyp as a function of quality and use it to demonstrate high correlation of the proposed metric to polyp detection sensitivity. The proposed online quality metric can be used to provide real time quality feedback to the performing GI. By integrating the local metric over the withdrawal phase, we build a global, offline quality metric, which is shown to be highly correlated to the standard Polyp Per Colonoscopy (PPC) quality metric

Principal Uncertainty Quantification with Spatial Correlation for Image Restoration Problems

Uncertainty quantification for inverse problems in imaging has drawn much attention lately. Existing approaches towards this task define uncertainty regions based on probable values per pixel, while ignoring spatial correlations within the image, resulting in an exaggerated volume of uncertainty. In this paper, we propose PUQ (Principal Uncertainty Quantification) -- a novel definition and corresponding analysis of uncertainty regions that takes into account spatial relationships within the image, thus providing reduced volume regions. Using recent advancements in generative models, we derive uncertainty intervals around principal components of the empirical posterior distribution, forming an ambiguity region that guarantees the inclusion of true unseen values with a user-defined confidence probability. To improve computational efficiency and interpretability, we also guarantee the recovery of true unseen values using only a few principal directions, resulting in more informative uncertainty regions. Our approach is verified through experiments on image colorization, super-resolution, and inpainting; its effectiveness is shown through comparison to baseline methods, demonstrating significantly tighter uncertainty regions

Five-State Study of ACA Marketplace Competition

The health insurance marketplaces created by the Affordable Care Act (ACA) were intended to broaden health insurance coverage by making it relatively easy for the uninsured, armed with income-related federal subsidies, to choose health plans that met their needs from an array of competing options. The further hope was that competition among health plans on the exchanges would lead to lower costs and higher value for consumers, because inefficient, low-value plans would lose out in the competitive market place. This study sought to understand the diverse experience in five states under the ACA in order to gain insights for improving competition in the private health insurance industry and the implementation of the ACA.In spring 2016, the insurance marketplaces had been operating for nearly three full years. There were numerous press stories of plans' decisions to enter or leave selected states or market areas within states and to narrow provider networks by including fewer choices among hospitals, medical specialists, and other providers. There were also beginning to be stories of insurer requests for significant premium increases. However, there was no clear understanding of how common these practices were, nor how and why practices differed across carriers, markets, and state regulatory settings.This project used the ACA Implementation Research Network to conduct field research in California, Michigan, Florida, North Carolina, and Texas. In each state, expert field researchers engaged directly with marketplace stakeholders, including insurance carriers, provider groups, state regulators, and consumer engagement organizations, to identify and understand their various decisions. This focus included an effort to understand why carriers choose to enter or exit markets and the barriers they faced, how provider networks were built, and how state regulatory decisions affected decision-making. Ultimately, it sought to find where and why certain markets are successful and competitive and how less competitive markets might be improved.The study of five states was not intended to provide statistically meaningful generalizations about the functioning of the marketplace exchanges. Rather, it was intended to accomplish two other objectives. First, the study was designed to generate hypotheses about the development and evolution of the exchanges that might be tested with "harder" data from all the exchanges. Second, it sought to describe the potentially idiosyncratic nature of the marketplaces in each of the five states. Political and economic circumstances may differ substantially across markets. Policymakers and market participants need to appreciate the nuances of different local settings if programs are to be successful. What works in Michigan may not work in Texas and vice versa. Field research of this sort can give researchers and policymakers insight into how idiosyncratic local factors matter in practice.In brief, our five states had four years of experience in the open enrollment periods from 2014 through 2017. The states array themselves in a continuum of apparent success in enhancing and maintaining competition among insurers. California and Michigan appear to have had success in nurturing insurer competition, in at least the urban areas of their states. Florida, North Carolina, and Texas were less successful. This divergence is recent, however. As recently as the 2015 and 2016 open enrollment periods, all of the states had what appeared to be promising, if not always robust, insurance competition. Large changes occurred in the run-up to the 2017 open enrollment period

Visual Tracking by Affine Kernel Fitting Using Color and Object Boundary

Kernel-based trackers aggregate image features within the support of a kernel (a mask) regardless of their spatial structure. These trackers spatially fit the kernel (usually in location and in scale) such that a function of the aggregate is optimized. We propose a kernel-based visual tracker that exploits the constancy of color and the presence of color edges along the target boundary. The tracker estimates the best affinity of a spatially aligned pair of kernels, one of which is color-related and the other of which is object boundary-related. In a sense, this work extends previous kernel-based track-ers by incorporating the object boundary cue into the track-ing process and by allowing the kernels to be affinely trans-formed instead of only translated and isotropically scaled. These two extensions make for more precise target local-ization. Moreover, a more accurately localized target facil-itates safer updating of its reference color model, further enhancing the tracker’s robustness. The improved tracking is demonstrated for several challenging image sequences. 1

3D Human Body-Part Tracking and Action Classification Using a Hierarchical Body Model

This paper presents a framework for hierarchical 3D articulated human body-part tracking and action classification. We introduce a Hierarchical Annealing Particle Filter (H-APF) algorithm, which applies nonlinear dimensionality reduction of the high di-mensional data space to the low dimensional latent spaces combined with the dynamic motion model and the Hierarchical Human Body Model. The improved annealing ap-proach is used for the propagation between different body models and sequential frames. The tracking algorithm generates trajectories in the latent spaces, which provide low di-mensional representations of body poses, observed during the motion. These trajectories are used to classify human motions. The tracking and classification algorithms were checked on HumanEvaI, HumanEvaII, and other datasets, involving more complicated motion types and transitions and proved to be effective and robust. The comparison to other methods and the error calculations are provided.

Blind decomposition of transmission light microscopic hyperspectral cube using sparse representation

Abstract-In this paper, we address the problem of fully automated decomposition of hyperspectral images for transmission light microscopy. The hyperspectral images are decomposed into spectrally homogeneous compounds. The resulting compounds are described by their spectral characteristics and optical density. We present the multiplicative physical model of image formation in transmission light microscopy, justify reduction of a hyperspectral image decomposition problem to a blind source separation problem, and provide method for hyperspectral restoration of separated compounds. In our approach, dimensionality reduction using principal component analysis (PCA) is followed by a blind source separation (BSS) algorithm. The BSS method is based on sparsifying transformation of observed images and relative Newton optimization procedure. The presented method was verified on hyperspectral images of biological tissues. The method was compared to the existing approach based on nonnegative matrix factorization. Experiments showed that the presented method is faster and better separates the biological compounds from imaging artifacts. The results obtained in this work may be used for improving automatic microscope hardware calibration and computer-aided diagnostics

Why the fair innings argument is not persuasive

The fair innings argument (FIA) is frequently put forward as a justification for denying elderly patients treatment when they are in competition with younger patients and resources are scarce. In this paper I will examine some arguments that are used to support the FIA. My conclusion will be that they do not stand up to scrutiny and therefore, the FIA should not be used to justify the denial of treatment to elderly patients, or to support rationing of health care by age. There are six issues arising out of the FIA which are to be addressed. First, the implication that there is such a thing as a fair share of life. Second, whether it makes sense to talk of a fair share of resources in the context of health care and the FIA. Third, that 'fairness' is usually only mentioned with regard to the length of a person's life, and not to any other aspect of it. Fourth, if it is sensible to discuss the merits of the FIA without taking account of the 'all other things being equal' argument. Fifth, the difference between what is unfair and what is unfortunate. Finally, that it is tragic if a young person dies, but only unfortunate if an elderly person does

An Evaluation of Ultrasound-Guided Regional Block Anesthesia in Outpatient Hand Surgery

Introduction: The utilization of ultrasound-guided peripheral nerve blocks in orthopedic surgery has increased in popularity as the anesthesia of choice for the management of perioperative pain. Peripheral nerve blockade has been shown to increase overall surgical efficiency, improve patient satisfaction, reduce postoperative narcotic use, and decrease the duration of facility admissions, while increasing overall cost-effectiveness. To date, scant literature exists regarding the safety and efficacy of ultrasound-guided supraclavicular blocks used in common hand surgery procedures, and the rate of neurologic and vascular complications remains unknown. Objective: The purpose of this study was to examine the effectiveness and complication rate of supraclavicular nerve blocks in hand surgery. Methods: With institutional review board approval, 713 cases of outpatient upper extremity surgery, performed by three board certified orthopedic hand surgeons at a single ambulatory surgery center over a consecutive period of 2 years, were retrospectively reviewed. Adverse outcomes related to regional blocks were identified through reviewing the electronic medical record of the immediate 24-hour postoperative telephone call and the first postoperative visit note within two weeks of surgery. Results: 20 patients (2.8%) reported an excessively long block and 1 patient reported inadequate pain control in the PACU (0.1%), but no clinically significant pulmonary or neurovascular complications were identified. Conclusion: Ultrasound-guided supraclavicular block was associated with a high success rate and low complication rate. This technique as described may be safe for outpatients, although larger numbers of subjects will be required to make this statement with certainty

Evaluating the Efficacy of a Thermoresponsive Hydrogel for Delivering Anti-Collagen Antibodies to Reduce Posttraumatic Scarring in Orthopedic Tissues.

Excessive posttraumatic scarring in orthopedic tissues, such as joint capsules, ligaments, tendons, muscles, and peripheral nerves, presents a significant medical problem, resulting in pain, restricted joint mobility, and impaired musculoskeletal function. Current treatments for excessive scarring are often ineffective and require the surgical removal of fibrotic tissue, which can aggravate the problem. The primary component of orthopedic scars is collagen I-rich fibrils. Our research team has developed a monoclonal anti-collagen antibody (ACA) that alleviates posttraumatic scarring by inhibiting collagen fibril formation. We previously established the safety and efficacy of ACA in a rabbit-based arthrofibrosis model. In this study, we evaluate the utility of a well-characterized thermoresponsive hydrogel (THG) as a delivery vehicle for ACA to injury sites. Crucial components of the hydrogel included N-isopropylacrylamide, poly(ethylene glycol) diacrylate, and hyaluronic acid. Our investigation focused on in vitro ACA release kinetics, stability, and activity. Additionally, we examined the antigen-binding characteristics of ACA post-release from the THG in an in vivo context. Our preliminary findings suggest that the THG construct exhibits promise as a delivery platform for antibody-based therapeutics to reduce excessive scarring in orthopedic tissues