A Case Presentation of Pericarditis Associated with Haemophilus Influenzae Bacteremia

Acute pericarditis, or inflammation of the pericardial sac, is a clinical condition which can often be attributed to a variety of underlying etiologies, including infection, autoimmune disease, trauma, and malignancy. While viral infections are commonly implicated in the etiology of pericarditis, bacteria known to be associated with pericarditis include staphylococcus species, streptococcal species, tuberculosis, and in children, Haemophilus influenzae.1 Here we present a rare case of pericarditis in an adult male patient which occurred in association with Haemophilus influenzae bacteremia

From the Editors

We are honored to present the 24th Annual edition of The Medicine Forum to the Jefferson community. Over the years, it has been remarkable to see the quality and diversity of projects submitted to this forum, and this year is no exception. The Medicine Forum aims to celebrate the scholarly activity among physicians in training at our institution. We hope that this year\u27s edition will continue to honor this long standing tradition. Despite the uncertainties and stressors that are inherent to working in a hospital, our authors have found the time to produce scholarly work that will diversify and further medical knowledge. For this, we thank them. We also want to thank our supporters for making this journal possible and our readers for their continued interest. Editorial Board Harrison Bell, MD Akash Patel, DO Benjamin Tasevac, MD Editorial Staff Katherine Duffey, MD Michael Joseph, DO Louis Kishfy, MD Mark Mallozzi, MD Lindsey Morris, MD Jason Ojeda, MD Tal Zivan, MD Friends of the Forum Mark S. Berger, M

Management of Upper Aerodigestive Tract Bleeding in Patients on ECMO.

Introduction: Bleeding complications on Extracorporeal Membrane Oxygenation (ECMO) are often encountered. In a review of our own series, it was found that upper aero digestive tract bleeding was common and management was often difficult. We propose an algorithm to help manage upper aero digestive tract bleeding in the anticoagulated, ECMO patient. Hypothesis: Once an ECMO patient fails conservative management for upper aero digestive bleeding, more aggressive measures will prove successful, which will provide benefit to the patient. Methods: A retrospective chart review was performed of the patients who underwent venovenous or veno-arterial ECMO at our institution between July 2010 and July 2012. The patients that had upper aero digestive tract bleeding that required an Otolaryngology consultation were identified. They were further investigated to determine location of bleed and procedures performed to control the bleeding. Results: Among the 37 consecutive patients on ECMO, 11 (30%) had upper aero digestive tract bleeding events. Of these 11, 6 (55%) were secondary to an iatrogenic incident, such as placing a nasogastric tube or transesophageal echo probe. All 11 patients were treated at bedside with conservative management and 2 were treated in the operating room. 72.7 % of patients treated with conservative management required repeated procedures due to incomplete hemostasis, compared to 0% of patients once surgical intervention was complete. Conclusions: Approximately one third of the ECMO patients developed upper aero digestive tract bleeding. This bleeding should be controlled in a timely manner otherwise it may result in massive transfusions. Delaying intervention or conservative management may not be effective. We recommend surgical intervention if the initial conservative management failed and continued to bleed for more than 24-36 hours

Verification of User Interface Software: The Example of Use-Related Safety Requirements and Programmable Medical Devices

One part of demonstrating that a device is acceptably safe, often required by regulatory standards, is to show that it satisfies a set of requirements known to mitigate hazards. This paper is concerned with how to demonstrate that a user interface software design is compliant with use-related safety requirements. A methodology is presented based on the use of formal methods technologies to provide guidance to developers about addressing three key verification challenges: 1) how to validate a model, and show that it is a faithful representation of the device; 2) how to formalize requirements given in natural language, and demonstrate the benefits of the formalization process; and 3) how to prove requirements of a model using readily available formal verification tools. A model of a commercial device is used throughout the paper to demonstrate the methodology. A representative set of requirements are considered. They are based on US Food and Drug Administration (FDA) draft documentation for programmable medical devices, and on best practice in user interface design illustrated in relevant international standards. The methodology aims to demonstrate how to achieve the FDA's agenda of using formal methods to support the approval process for medical devices.This work was supported by the EPSRC research Grant EP/G059063/1: CHI+MED (Computer-Human Interaction for Medical Devices). The work of P. Masci and J.C. Campos was supported under Project NORTE-01-0145-FEDER-000016, financed by the North Portugal Regional Operational Programme (NORTE 2020), through the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF)

Machine Learning Approaches for Principle Prediction in Naturally Occurring Stories

Value alignment is the task of creating autonomous systems whose values align with those of humans. Past work has shown that stories are a potentially rich source of information on human values; however, past work has been limited to considering values in a binary sense. In this work, we explore the use of machine learning models for the task of normative principle prediction on naturally occurring story data. To do this, we extend a dataset that has been previously used to train a binary normative classifier with annotations of moral principles. We then use this dataset to train a variety of machine learning models, evaluate these models and compare their results against humans who were asked to perform the same task. We show that while individual principles can be classified, the ambiguity of what "moral principles" represent, poses a challenge for both human participants and autonomous systems which are faced with the same task.Comment: Nahian and Frazier contributed equally to this wor