19 research outputs found

    You See, I See, We All See UC

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    A 21 year old male with a six month history of biopsy-proven ulcerative colitis presented to Henry Ford with worsening abdominal pain and rectal bleeding despite steroid therapy. Upon CT evaluation, the patient was found to have a significant mass of the descending colon. Biopsy was completed and showed EBV+ B-cell lymphoma. The patient’s clinical course was complicated by bowel perforation, but he was ultimately able to receive chemotherapy and treatment.https://scholarlycommons.henryford.com/merf2020caserpt/1062/thumbnail.jp

    Medical Student Perspectives on Opioid Use Disorders: An Innovative MAT Waiver Training Integration during IM Clerkships

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    The opioid epidemic in the US has become a major issue in healthcare. In 2017, there was an estimated 72,306 drug overdose related deaths and Emergency Departments (ED) nationally saw a 30% increase in opioid related overdoses. Innovative programs can help ensure patients are offered optimal treatment options. Most primary care physicians self-report they lack the skills to identify and appropriately treat substance abuse disorders (SUDs). Studies have suggested that the best solution is to improve medical school curricula, which translates to better educated future physicians. Unfortunately, due to timing and exposure constraints, most medical school programs do not provide the necessary information to successfully manage and treat SUDs in practice. To prescribe buprenorphine, an 8-hour Medication Assisted Treatment (MAT) training must be completed. Only 35,604 of the approximate 800,000 US physicians (\u3c3%) are registered to prescribe buprenorphine. We implemented an innovative approach to provide students with the skills to understand how to prescribe buprenorphine and build confidence to medically manage opioid use disorders in the future. By completing the training students will be eligible for a their MAT waiver upon obtaining their permanent license. Prior to integrating the training into the internal medicine clerkship, a preliminary study similar in nature was performed that focused on first and second year medical students perspectives. The results were analyzed and presented, and based on the positive results of the study, it was decided to implement the study into the internal medicine clerkship during the third year of medical school

    Optics and Quantum Electronics

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    Contains table of contents on Section 3 and reports on nineteen research projects.Defense Advanced Research Projects Agency Grant F49620-96-0126Joint Services Electronics Program Grant DAAH04-95-1-0038National Science Foundation Grant ECS 94-23737U.S. Air Force - Office of Scientific Research Contract F49620-95-1-0221U.S. Navy - Office of Naval Research Grant N00014-95-1-0715Defense Advanced Research Projects Agency/National Center for Integrated Photonics TechnologyMultidisciplinary Research InitiativeU.S. Air Force - Office of Scientific ResearchNational Science Foundation/MRSECU.S. Navy - Office of Naval Research (MFEL) Contract N00014-91-J-1956National Institutes of Health Grant R01-EY11289U.S. Navy - Office of Naval Research (MFEL) Contract N00014-94-0717Defense Advanced Research Projects Agency Contract N66001-96-C-863

    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    Towards precision critical care management of blood pressure in hemorrhagic stroke patients using dynamic linear models.

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    Finding optimal blood pressure (BP) target and BP treatment after acute ischemic or hemorrhagic strokes is an area of controversy and a significant unmet need in the critical care of stroke victims. Numerous large prospective clinical trials have been done to address this question but have generated neutral or conflicting results. One major limitation that may have contributed to so many neutral or conflicting clinical trial results is the "one-size fit all" approach to BP targets, while the optimal BP target likely varies between individuals. We address this problem with the Acute Intervention Model of Blood Pressure (AIM-BP) framework: an individualized, human interpretable model of BP and its control in the acute care setting. The framework consists of two components: one, a model of BP homeostasis and the various effects that perturb it; and two, a parameter estimator that can learn clinically important model parameters on a patient by patient basis. By estimating the parameters of the AIM-BP model for a given patient, the effectiveness of antihypertensive medication can be quantified separately from the patient's spontaneous BP trends. We hypothesize that the AIM-BP is a sufficient framework for estimating parameters of a homeostasis perturbation model of a stroke patient's BP time course and the AIM-BP parameter estimator can do so as accurately and consistently as a state-of-the-art maximum likelihood estimation method. We demonstrate that this is the case in a proof of concept of the AIM-BP framework, using simulated clinical scenarios modeled on stroke patients from real world intensive care datasets

    Preexisting right ventricular systolic dysfunction in high-risk patients undergoing non.emergent open abdominal surgery: A retrospective cohort study.

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    BackgroundThe prognostic value of right ventricular systolic dysfunction in high-risk patients undergoing non-emergent open abdominal surgery is unknown. Here, we aim to evaluate whether presence of preexisting right ventricular systolic dysfunction in this surgical cohort is independently associated with higher incidence of postoperative major adverse cardiac events and all-cause in-hospital mortality.MethodsThis is a single-centered retrospective study. Patients identified as American Society Anesthesiology Classification III and IV who had a preoperative echocardiogram within 1 year of undergoing non-emergent open abdominal surgery between January 2010 and May 2017 were included in the study. Incidence of postoperative major cardiac adverse events and all-cause in-hospital mortality were collected. Multivariable logistic regression was performed in a step-wise manner to identify independent association between preexisting right ventricular systolic dysfunction with outcomes of interest.ResultsPreexisting right ventricular systolic dysfunction was not associated with postoperative major adverse cardiac events (P = 0.26). However, there was a strong association between preexisting right ventricular systolic dysfunction and all-cause in-hospital mortality (P = 0.00094). After multivariate analysis, preexisting right ventricular systolic dysfunction continued to be an independent risk factor for all-cause in-hospital mortality with an odds ratio of 18.9 (95' CI: 1.8-201.7; P = 0.015).ConclusionIn this retrospective study of high-risk patients undergoing non-emergent open abdominal surgery, preexisting right ventricular systolic dysfunction was found to have a strong association with all-cause in-hospital mortality
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