THE UNIVERSITY OF VERMONT COLLEGE OF MEDICINE DEPARTMENT OF SURGERY FORTY-FIFTH ANNUAL SURGERY SENIOR MAJOR SCIENTIFIC PROGRAM THURSDAY – MAY 7, 2015 AUSTIN AUDITORIUM, Shep 488 UVM MEDICAL CENTER CAMPUS 7:30AM

Introduction: Traumatic injury is a leading cause of morbidity and mortality throughout the world, and its management is often challenging. When performed by an experienced provider, the extended focused assessment with sonography in trauma (eFAST) is highly sensitive for the detection of thoracic and abdominal injury. Its low cost and good safety profile makes it ideal for use in resource poor settings where access to cross-sectional imaging and highly trained personnel is limited. In order to maximize the utility of eFAST in these settings, we developed a protocol to standardize the collection of ultrasound images based on external anatomic land marks (modified eFAST; mEFAST) and transmit them to experienced radiologists for interpretation in near-real time. The purpose of this study is to correlate findings between diagnostic imaging and mEFAST performed by non-physicians. Methods: Non-physicians trained in the mEFAST protocol performed scans on patients who underwent diagnostic imaging during their normal course of care. The cine loops were compressed and transmitted to board certified radiologists who interpreted the images. Images were evaluated based on the radiologists’ confidence in their ability to visualize the structures and potential spaces utilizing a 5 point modified Likert scale which was used to generate a mean quality assessment (MQA) score, as well as correlation of findings with diagnostic imaging. Results: The study was approved by the University of Vermont Institutional Review Board, and a workflow was developed to facilitate patient identification. A pilot study demonstrated MQA scores> 3.5 for all views. Conclusions: The current workflow and scanning protocol yield high quality ultrasound images that can be used to further assess the scanning and data handling protocols. Characterizing the United States Cancer Patient Experience through Social Media: A National pattern-matched Twitter analysis of cancer-patient sentiments W. Christian Crannell Eric Clark MSc PhD-candidate, Jesse Moore MD, Ted James MD, Chris Jones PhD1 1. University of Vermont 2. UVM Cancer Center