Citations

INTRODUCTION: Endoscopic sleeve gastroplasty (ESG) has gained popularity over the past decade and has been adopted in both academic and private institutions globally. We present outcomes of the largest cohort of patients from the United States undergoing ESG and evaluate these according to obesity class. METHODS: We performed a retrospective analysis of adult patients who underwent ESG. Medical information was abstracted from the electronic record with weight records up to 2 years after ESG. Percent total body weight loss (%TBWL) at 6, 12, 18, and 24 months was calculated based on baseline weight at the procedure. SPSS (version 29.0) was used for all statistical analyses. RESULTS: A total of 1,506 patients from 7 sites were included (501 Class I obesity, 546 Class II, and 459 Class III). Baseline demographics differed according to obesity class due to differences in age, body mass index (BMI), height, sex distribution, and race. As early as 6 months post-ESG, mean BMI for each class dropped to the next lower class and remained there through 2 years. %TWBL achieved in the Class III group was significantly greater when compared with other classes at all time points. At 12 months, 83.2% and 60.9% of patients had ≥10% and ≥15% TBWL for all classes. There were no differences in adverse events between classes. DISCUSSION: Real-world data from a large cohort of patients of all BMI classes across the United States shows significant and sustained weight loss with ESG. ESG is safe to perform in a higher obesity class with acceptable midterm efficacy.

Abstract Vaccines to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induce antibody responses against the spike (S) protein. However, the continued emergence of variants such as Omicron (B.1.1.529), with 30 amino acid changes in the S protein, underscores the need to find conserved targets that induce adaptive immunity. Natural infection induces CD8+ T cell activation against the viral proteins S, membrane (M), and nucleocapsid (N) as well as NSPs (non-structural proteins). Our study seeks to find conserved and immunogenic MHC class I epitopes throughout the SARS-CoV-2 peptidome. We used Ensemble MHC, a novel consensus predictive algorithm to select highly immunogenic CD8+ T cell epitopes presented by 52 of the most common HLA-I alleles, covering > 98% of the world’s population. We selected 658 high confidence predicted peptides from the SARS-CoV-2 immunopeptidome and prioritized testing 108 structural epitopes derived from the S, M, N, and E proteins. We collected PBMCs from unexposed, healthy, and convalescent individuals (n=31) covering ~ 85% of HLA alleles in the population, and measured T cell immunity by IFNγ secretion ELISpot and Activation Induced Marker (AIM) flow cytometry. In convalescent individuals, all predicted epitopes tested so far (n=36) were immunogenic (IFNγ response >2 fold than background) but 3/19 tested donors were unreactive. Samples from pre-pandemic (2017–19) unexposed healthy donors are reactive to 42% of tested epitopes, which indicate cross-reactivity to common cold coronaviruses (CCC) and possibly pre-existing protection against SARS-CoV-2. In summary, we have identified 45 highly conserved and immunogenic SARS-CoV-2 CD8+ T cell epitopes as potential targets for vaccine design. Supported by a grant from the Arizona Department of Health Services (AZDHS)

We observe previously unknown interactions between clinically important adenovirus vector capsids, platelet factor 4, and CAR.

Introduction Diagnostic processes in the emergency department (ED) involve multiple interactions among individuals who interface with information systems to access and record information. A better understanding of diagnostic processes is needed to mitigate errors. This paper describes a study protocol to map diagnostic processes in the ED as a foundation for developing future error mitigation strategies. Methods and analysis This study of an adult and a paediatric academic ED uses a prospective mixed methods case study design informed by an ED-specific diagnostic decision-making model (the modified ED-National Academies of Sciences, Engineering and Medicine (NASEM) model) and two cognitive theories (dual process theory and distributed cognition). Data sources include audio recordings of patient and care team interactions, electronic health record data, observer field notes and stakeholder interviews. Multiple qualitative analysis methods will be used to explore diagnostic processes in situ, including systems information flow, human–human and human–system interactions and contextual factors influencing cognition. The study has three parts. Part 1 involves prospective field observations of patients with undifferentiated symptoms at high risk for diagnostic error, where each patient is followed throughout the entire care delivery process. Part 2 involves observing individual care team providers over a 4-hour window to capture their diagnostic workflow, team coordination and communication across multiple patients. Part 3 uses interviews with key stakeholders to understand different perspectives on the diagnostic process, as well as perceived strengths and vulnerabilities, in order to enrich the ED-NASEM diagnostic model. Ethics and dissemination The University of Michigan Institutional Review Board approved this study, HUM00156261. This foundational work will help identify strengths and vulnerabilities in diagnostic processes. Further, it will inform the future development and testing of patient, provider and systems-level interventions for mitigating error and improving patient safety in these and other EDs. The work will be disseminated through journal publications and presentations at national and international meetings.