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The step-by-step enforced strategies to prevent the spread of COVID-19, though not perfect, adequately reduced the risk of transmission of the highly contagious infectious disease in the hospital while maintaining the emergency medical system.

The step-by-step enforced strategies to prevent the spread of COVID-19, though not perfect, adequately reduced the risk of transmission of the highly contagious infectious disease in the hospital while maintaining the emergency medical system.

Topic identification can facilitate knowledge curation, discover thematic relationships, trends, and predict future direction. We aimed to determine through an unsupervised, machine learning approach to topic modeling the most common research themes in emergency medicine over the last 40years and summarize their trends and characteristics.

We retrieved the complete reference entries including article abstracts from Ovid for all original research articles from 1980 to 2019 within emergency medicine for six widely-cited journals. Abstracts were processed through a natural language pipeline and analyzed by a latent Dirichlet allocation topic modeling algorithm for unsupervised topic discovery. Topics were further examined through trend analysis, word associations, co-occurrence metrics, and two-dimensional embeddings.

We retrieved 47,158 articles during the defined time period that were filtered to 20,528 articles for further analysis. Forty topics covering methodologic and clinical areas were discovered. These topics separated into distinct clusters when embedded in two-dimensional space and exhibited consistent patterns of interaction. We observed the greatest increase in popularity in research themes involving risk factors (0.4% to 5.2%), health utilization (1.2% to 5.0%), and ultrasound (0.7% to 3.3%), and a relative decline in research involving basic science (8.9% to 1.1%), cardiac arrest (6.5% to 2.2%), and vitals (6.3% to 1.3%) over the past 40years. Our data show only very modest growth in mental health and substance abuse research (1.0% to 1.6%), despite ongoing crises.

Topic modeling via unsupervised machine learning applied to emergency medicine abstracts discovered coherent topics, trends, and patterns of interaction.

Topic modeling via unsupervised machine learning applied to emergency medicine abstracts discovered coherent topics, trends, and patterns of interaction.

To determine whether the combination of skin tapes and tissue adhesive is superior to either method alone for laceration repair.

This was a prospective, longitudinal experiment on six anesthetized swine. Thirty-six full-thickness linear wounds were created using a metal template, then closed using one of three methods skin tapes over benzoin, tissue adhesive, or a combination of both. The study was done in two parts. Group 1 (immediate excision) animals were euthanized at day zero for skin excision and tensile strength testing following wound repair. Group 2 (delayed excision) had initial wound repair; animals were euthanized at day 35 for skin excision and tensile strength testing.

In Group 1, the combination of skin tapes and tissue adhesive provided the strongest immediate wound closure. Average mean force for disruption immediately after wound repair was 19.9 lbs. for the tapes and tissue adhesive group compared to 9.6 lbs. for adhesive alone and 8.9 lbs. for tapes alone. The difference in mean forcither of these methods alone in a porcine model.

Initial recommendations discouraged high flow nasal cannula (HFNC) in COVID-19 patients, driven by concern for healthcare worker (HCW) exposure. Noting high morbidity and mortality from early invasive mechanical ventilation, we implemented a COVID-19 respiratory protocol employing HFNC in severe COVID-19 and HCW exposed to COVID-19 patients on HFNC wore N95/KN95 masks. Utilization of HFNC increased significantly but questions remained regarding HCW infection rate.

We performed a retrospective evaluation of employee infections in our healthcare system using the Employee Health Services database and unit records of employees tested between March 15, 2020 and May 23, 2020. We assessed the incidence of infections before and after the implementation of the protocol, stratifying by clinical or non-clinical role as well as inpatient COVID-19 unit.

During the study period, 13.9% (228/1635) of employees tested for COVID-19 were positive. Forty-six percent of infections were in non-clinical staff. After implementation of the respiratory protocol, the proportion of positive tests in clinical staff (41.5%) was not higher than that in non-clinical staff (43.8%). Of the clinicians working in the high-risk COVID-19 unit, there was no increase in infections after protocol implementation compared with clinicians working in COVID-19units that did not use HFNC.

We found no evidence of increased COVID-19 infections in HCW after the implementation of a respiratory protocol that increased use of HFNC in patients with COVID-19; however, these results are hypothesis generating.

We found no evidence of increased COVID-19 infections in HCW after the implementation of a respiratory protocol that increased use of HFNC in patients with COVID-19; however, these results are hypothesis generating.

To describe the effects of the COVID-19 pandemic on adults with T1D or T2D in the U.S.

Participants, recruited from the Taking Control of Your Diabetes Research Registry, were ≥19 years old and diagnosed with either T1D or T2D for ≥12 months. Participants completed an online survey on a HIPAA-protected platform.

Completed surveys were received from 763 T1Ds and 619 T2Ds. Average T1D age was 53.3 (SD = 15.3); average T2D age was 64.9 (SD = 10.3). Both samples were predominantly female, non-Hispanic white and well-educated. Average self-reported HbA1c was 6.9 (SD = 1.0; 52 mmol/mol) for T1Ds and 7.1 (SD = 1.1; 54 mmol/mol) for T2Ds. About 40% of respondents reported that all of their diabetes healthcare appointments at the time were cancelled or postponed, 40% reported a switch to telehealth appointments and almost half reported lower overall satisfaction with these visits (compared to pre-pandemic). CX-3543 datasheet There were widespread increases in general and diabetes-related stress and social isolation, and negative effects on disease management.

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