bluuebunny/crossref_metadata_2025_split huggingface dataset:
443. Comparison of Clinical Characteristics of Endemic vs. SARS-CoV-2 Coronavirus Infection in Patients Admitted to a Community Teaching Hospital
Authors: Politis Paula Ann , Oravec Michael J , Hoisington Lisa , Tan Michael , Agarwal Shanu , Agarwal Shanu , England Matthew , File Thomas M , File Thomas M 
Published: January 2021

Abstract

Background
Endemic coronaviruses [EC] (NL63, 229E, OC43, HKU1) have been identified in humans since the 1960s. Most are associated with mild upper respiratory tract infections (RTIs) but can be associated serious disease. More recently, novel coronaviruses associated with SARS, MERS, and COVID-19 caused by SARS-CoV-2 have emerged and are often associated with serious disease and death. With this report, we compare presenting clinical characteristics and some outcomes of patients hospitalized with RTIs caused by ECs or by SARS-CoV-2 (COVID-19).

Methods
Patients admitted to the Summa Health System with RTIs associated with EC were identified via multiplex PCR method (BioFire™). Patients admitted with COVID-19 were identified by real-time, reverse transcriptase-PCR method using one of several platforms. Patients were selected from two existing quality improvement registries encompassing EC and COVID-19 cases. We compared clinical characteristics and outcomes of EC patients to those of COVID-19 patients using chi-squared tests for proportions and independent samples t-tests for means.

Results
Shown in Table 1. Significant differences in patient characteristics with EC vs. COVID-19 included: older age, primarily Caucasian, smoking history, requiring O2 supplementation on admission, and having chronic heart, lung, or renal disease. Significant differences in patient characteristics with COVID-19 vs. EC included: admission from extended care facility, obesity, presenting with fever, gastrointestinal symptoms and/or myalgia, presence of radiographic infiltrates, abnormal liver tests, and longer length of stay (LOS). A non-significant difference was noted in 30 day mortality rates. Coronavirus OC43 accounted for 54% of EC strains.

Conclusion
There were significant differences in clinical characteristics between the two groups with EC patients more likely to have lung disease (often COPD) and requiring admission for need of O2 supplementation. COVID-19 patients were more likely to present with a febrile illness associated with pneumonia and require longer LOS (often requiring O2 supplementation later in hospitalization). Patients admitted with COVID-19 present with different clinical characteristics than those with EC with numerically higher mortality rate.

Disclosures
All Authors: No reported disclosures
446. COVID 19 Pandemicity: a global situation report as of June 9, 2020
Authors: Sanyaolu Adekunlle , Okorie Chuku , Hosein Zaheeda , Patidar Risha , Desai Priyank , Prakash Stephanie , Jaferi Urooj , Mangat Jasmine , Marinkovic Aleksandra 
Published: January 2021

Abstract

Background
The World Health Organization (WHO) declared severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) a pandemic on March 11, 2020. This report takes a closer look at the cases, fatalities, and recoveries in different regions of the world with details regarding the geographic scale of SARS-CoV-2 spread, risks, and the subsequent impact on the countries affected. Also, this report discusses some effective measures that were carried out by some countries that helped them to mitigate the pandemic and flatten the curve of COVID-19 spread as early as possible.

Methods
Our research was conducted via an electronic literature review on PubMed, Google Scholar, and MedLine Plus. Data were then collected from peer-reviewed articles that included applicable keywords and published between January 1, 2020, and June 9, 2020

Results
The rapid spread of infection has impacted over 200 countries and territories to date. As of June 9, 2020, there were 7,039,918 confirmed cases and 404,396 deaths globally. The USA is the North American country with the highest number of confirmed COVID 19 cases with 1,993,560. In South America, total confirmed cases in Brazil are 691,758. The most affected country in the African region is South Africa with 50,879. In Europe, the Russian Federation top with 485,253 confirmed cases. China with 84,638 is still the Western Pacific country with the most confirmed COVID 19 cases. India had 266,598 total confirmed cases and Australia reported 7,265 confirmed cases. Fatalities recorded similar patterns regionally except in Europe where the UK recorded the highest number of fatalities with 40,597 deaths and Iran had the highest number of fatalities with 5,957 cases in Asia. The goal of the practice “slowing the spread” is to prevent hospital systems from being strained beyond their capacity, thus resulting in less mortality. Countries yet to see the peak would benefit substantially by implementing aggressive social distancing, self-isolation, closure of schools and other institutions, encouraging working from home, and/or placing hard limits on the size of crowds at events.
Confirmed cases of COVID-19 globally, as of June 9, 2020.

Confirmed fatalities due to COVID-19 globally, as of June 9, 2020.

Conclusion
As the number of cases increases, an immediate need to “flatten the curve” is essential to avoid catastrophic overwhelming of hospital systems across the affected countries.

Disclosures
All Authors: No reported disclosures
447. COVID-19 Prevalence Among COVID-19 Exposed Health Care Workers at a Tertiary Care Center in San Bernardino County, Ca
Authors: Valenzuela Kathleen Louise , Veltman Jennifer , Wilson April 
Published: January 2021

Abstract

Background
We studied the prevalence of positive SARS-CoV2 antibody and positive SARS-CoV2 antigen among high risk health care workers at Loma Linda University Health System (LLUHS) who voluntarily obtained SARS-CoV2 antibody testing, and if indicated, antigen testing. The study determined that there is a significant decrease in the prevalence of SARS-CoV2 antigen among employees at LLUH compared to the community.

Methods
Employee Health and Occupational Medicine offered antibody testing to employees who were considered high risk, primarily working in the Coronavirus Disease 19 (COVID-19) designated units. We tested 658 subjects’ serum for the presence of IgM and IgG antibodies via the Nirmidas Qualitative SARS-CoV2 test. 29 subjects with a positive antibody test were subsequently tested for the presence of serum SARS-CoV2 antigen via PCR.

Results
There were 31 subjects who tested positive for IgM or IgG antibodies. 11 subjects had positive IgM with negative IgG. 3 subjects had negative IgM with positive IgG. 15 patients had positive IgM and positive IgG. 2 subjects had positive IgM with negative IgG, were subsequently retested, and then found to have positive IgM and positive IgG.
Of those 31 subjects with a positive antibody test, 2 were not tested for the COVID-19 antigen, 1 had an inconclusive test, 23 tested negative, and 5 tested positive. Of those 5 positive for the antigen, 2 had symptoms and 3 did not report symptoms or did not use the symptom questionnaire.
The community prevalence of positive SARS-CoV2 antigen in San Bernardino is 0.37%, as of June 16. The prevalence of positive SARS-CoV2 antigen among LLUH employees is 0.03% and the prevalence of positive antibody is 0.18%. The value of z is -7.3206, p is &lt; .00001. Thus, the result is significant at p &lt; .01.

Conclusion
The results of this testing supports the efficacy of the early protective measures that LLUHS implemented in preparation for the pandemic. Such protective measures include: mandated face masks, symptoms screening, testing for SARS-CoV2 antibody or antigen on patients admitted, a dedicated COVID-19 section of the emergency department as well as inpatient units, etc. Given the statistical significance of this study, the protective bundle can be used as a template for preventative measures for future pandemics.

Disclosures
All Authors: No reported disclosures
454. Healthcare Workers with COVID-19 infection: Experience from a Designated COVID-19 Clinic
Authors: Arya Radhika , Tran Jennifer , Foroughi Negar , Oluigbo Nnenna , Barbhaya Dweep , Neupane Rabin , Franco Stephanie M , Gandhi Kejal D , Fishbein Dawn 
Published: January 2021

Abstract

Background
Healthcare workers (HCW) are at the frontline of the COVID-19 pandemic, risking infection through hospital contacts. Data regarding predisposing factors in the healthcare field is limited. In this study, we characterized presenting symptoms, occupation and hospitalizations for HCW who tested COVID-19 positive.

Methods
This is a retrospective study of HCW who presented for screening to a designated COVID-19 clinic at the largest hospital in Washington, DC between 3/13/20 - 5/28/20. Variables extracted included profession, exposure, presenting symptoms, past medical history and outcomes. Univariate analysis was performed using Fischer’s exact tests, with significance defined as p &lt; 0.05. IRB approval was obtained.

Results
There were a total of 881 HCW who presented for COVID-19 testing: 316 (35.8%) tested positive; 216 (68.4%) were female, mean age was 39. Cough was the most common presenting symptom (92.7%), followed by subjective fever (63.3%), myalgia (57.9%), and chills (46.8%)(Fig 1). RNs [110 (34.8%)] and physicians [39 (12.3%)] accounted for nearly 50% of cases. Hospitalizations occurred in 22(6.9%); 2(0.6%) died from COVID-19. See Fig 2 for symptoms associated with hospitalizations. African Americans (OR 4.52, CI95 1.54–12.50), and those with hypertension (3.14, 1.32–7.23) and obesity (2.98, 1.25–6.89) were more likely to be hospitalized.
Figure 1

Figure 2

Conclusion
HCW remain at risk for COVID-19 infection with respiratory and constitutional symptoms as the most common presentation. RNs were among the most affected. This study supports other reports that African Americans and those with pre-existing comorbidities have greater morbidity with COVID-19 – we have documented that these inequities are also prevalent amongst HCW. This should be considered when testing for and implementing practices to avoid risk of COVID-19 among HCW.

Disclosures
All Authors: No reported disclosures
460. Point-of-Care, In-Home SARS-CoV-2 IgG Antibody Testing to Assess Seroprevalence in At-Risk Health Care Workers
Authors: Meissner Eric G , Litwin Christine , Crocker Tricia , Mack Elizabeth , Card Lauren 
Published: January 2021

Abstract

Background
Health care workers are at significant risk for infection with the novel coronavirus SARS-CoV-2.

Methods
We utilized a point-of-care, lateral flow SARS-CoV-2 IgG immunoassay (RayBiotech) to conduct a seroprevalence study in a cohort of at-risk health care workers (n=339) and normal-risk controls (n=100) employed at an academic medical center. To minimize exposure risk while conducting the study, consents were performed electronically, tests were mailed and then self-administered at home using finger stick blood, and subjects uploaded a picture of the test result while answering an electronic questionnaire. We also validated the assay using de-identified serum samples from patients with PCR-proven SARS-CoV-2 infection.

Results
Between April 14th and May 6th 2020, 439 subjects were enrolled. Subjects were 68% female, 93% white, and most were physicians (38%) and nurses (27%). In addition, 37% had at least 1 respiratory symptom in the prior month, 34% had cared for a patient with known SARS-CoV-2 infection, 57% and 23% were worried about exposure at work or in the community, respectively, and 5 reported prior documented SARS-CoV-2 infection. On initial testing, 3 subjects had a positive IgG test, 336 had a negative test, and 87 had an inconclusive result. Of those with an inconclusive result who conducted a repeat test (85%), 96% had a negative result. All 3 positive IgG tests were in subjects reporting prior documented infection. Laboratory validation showed that of those with PCR-proven infection more than 13 days prior, 23/30 were IgG positive (76% sensitivity), whereas 1/26 with a negative prior PCR test were seropositive (95% specificity). Repeat longitudinal serologic testing every 30 days for up to 4 times is currently in progress.

Conclusion
We conducted a contact-free study in the setting of a pandemic to assess SARS-CoV-2 seroprevalence in an at-risk group of health care workers. The only subjects found to be IgG positive were those with prior documented infection, even though a substantial proportion of subjects reported significant potential occupational or community exposure and symptoms that were potentially compatible with SARS-COV-2 infection.

Disclosures
All Authors: No reported disclosures
464. Rapid whole genome sequence typing reveals multiple waves of SARS-CoV-2 spread
Authors: Moustafa Ahmed M , Planet Paul J , Planet Paul J 
Published: January 2021

Abstract

Background
As the pandemic SARS-CoV-2 virus has spread globally its genome has diversified and distinct clones can now be recognized, tracked, and traced. Identifying clonal groups allows for assessment of geographic spread, transmission events, and identification of more virulent or transmissible emerging strains.

Methods
All SARS-CoV-2 genomes (n=17,504) that are complete and high coverage were downloaded from GISAID on May 17th 2020. We developed a GNU-based Virus IDentification (GNUVID) tool that implements a whole genome multilocus sequence typing (wgMLST) scheme composed of all ten ORFs in the SARS-CoV-2 genome. The 10,422 genomes that passed our quality check were fed to the GNUVID tool, which assigned a ST profile to each genome. Global optimum eBURST was then used to cluster the STs in clonal complexes (CCs).

Results
Our ST/CC analysis uncovered strong associations of ST/CCs with certain geographical regions but also dynamic local changes in ST/CC prevalence. We also identified several unexpected putative global transmission events (e.g., from the US to the Middle East and reintroduction to China later in the pandemic). We have made our tool (GNUVID) available so that new WG sequences can be rapidly assigned to an ST/CC (https://github.com/ahmedmagds/GNUVID).

Conclusion
Our sequence typing system uncovered previously unappreciated transmission events and waves of expansion and replacement of SARS-CoV-2 STs and CCs in different geographical locations, suggesting complex dynamics in viral populations that previously seemed monomorphic. Because, our tool can be rapidly updated with new sequencing data it can track emerging clones and identifying new hotspots.

Disclosures
All Authors: No reported disclosures
465. Risk Factors Associated with Critical COVID-19 Requiring Mechanical Ventilation
Authors: Chris Robert B , Khalid Rabeeya , Ravichandran Urmila , Acree Mary Ellen , Grant Jennifer , Muthiah Chethra , Shah Nirav 
Published: January 2021

Abstract

Background
Mechanical ventilation of patients with COVID-19 is associated with high mortality. Understanding risk factors for developing mechanical ventilation may allow for more targeted monitoring and therapeutics that may improve outcomes.

Methods
We performed a retrospective case series of all patients admitted within thirty days of a positive Sars CoV-2 test to an integrated health system near Chicago, Illinois between March 12 and May 31, 2020. Covariates evaluated included demographics, symptoms on admission, vital signs, medications, comorbidities, census tract data and social history. Univariable analysis was performed and variables with an alpha of 0.05 or less were included in multivariable regression modeling to identify factors associated with mechanical ventilation. The area under the curve (AUC) was used to assess performance of the model.

Results
Of 990 patients admitted with COVID-19 12.6% (125) were mechanically ventilated. The median age was 68 (interquartile range 55–82), 48.4% (479) were female and 49.6% (491) were Caucasian. Independent factors associated with mechanical ventilation included female sex (Adjusted OR [AOR] 0.621, Confidence Interval [CI] 0.427–0.903; p=0.0363), body mass index (BMI) (AOR 1.035, CI 1.011–1.060; p=0.0175), percent of english speaking population within patient’s census tract (AOR 0.989, CI 0.979–0.998; p=0.0454), respiratory rate (AOR 1.054, CI 1.027–1.083; p=0.0011), oxygen saturation (AOR 0.922, CI 0.901–0.943; p&lt; 0.0001), cerebrovascular accident (CVA) (AOR 0.176, CI 0.051–0.605; p=0.0207) and hematologic malignancy (AOR 3.668, CI 1.403–9.590; p=0.0261). AUC of the model was 0.8 (0.75–0.84).
Characteristics of patients admitted with COVID-19

Multivariable logistic regression to identify risk factors associated with mechanical ventilation

Conclusion
Risk factors associated with mechanical ventilation included male gender, elevated BMI, census tract with lower percentage of english speakers, increased respiratory rate, low oxygen saturation, hematologic malignancy and not having a CVA. We suspect that history of CVA may have been associated with overall patient debility in which aggressive measures such as intubation were not deemed appropriate. Identifying patients with risk factors associated with mechanical ventilation may allow for early and targeted interventions to improve outcomes.

Disclosures
All Authors: No reported disclosures
467. Spatial-Temporal Prediction Model of COVID-19 Mortality across 62 Counties in New York State
Authors: Xiao Yunyu , Zeng Chengbo 
Published: January 2021

Abstract

Background
COVID-19 pandemic has resulted in considerable morbidity and mortality. New York State (NY) is the hotspot with most coronavirus cases, while there are spatial/temporal variations. Yet, few examined county-level factors of mortality in COVID-19 patients in NY. Based on the sociological framework in health, this study links large and representative public data to understand COVID-19 mortality in NY over different stages of pandemic.

Methods
Mortality cases were from Mar 17 (state of emergency; 0.1 per 100,000), Apr 18 (coronavirus peak; 87.4), Apr 25 (expand testing; 108.7), and May 11 (daily reduced to original; 137.6). Three domains (compositional, contextual, and collective) and 28 county-level predictors of mortality were extracted from American Community Survey, Area Health Resources, US Crime Data, and Religious Data systems for each county. Compositional domain covered socio-demographic characteristics in local areas (e.g., age, sex, race/ethnicity, housing). Contextual domain covered include social and physical opportunities (e.g., health insurance coverage, transportation, mental health providers). Collective domain covered neighborhood safety and religious adherents. Mixed effect regression with the least absolute shrinkage selection operator (LASSO) was used to select the predictors and estimate the parameters after adjusting the time effect and cumulative prevalence of COVID-19.
有道词典
; 0.1 per 100,000 people
详细X
;每100000人0.1

Results
NYC and the nearby boroughs (i.e., Bronx, Kings, Manhattan, Queens) had the highest cumulative mortality (231.69 per 100,000 people). Counties far from New York Cities (e.g., Allegany, Cortland, Delaware) had the lowest cumulative mortality. Spatial variation showed counties with larger population density (β=.01, p=.022) and/or higher proportion of people with at least high school education (β=227.24, p=.03) were at risk of higher cumulative mortality in COVID-19.

Conclusion
Unique spatial clustering mortality risk of COVID-19s was detected, highlighting important but understudied roles of contextual and collective factors. Tailored policy efforts shall be designed to support counties with large population density and high levels of education to prevent the mortality related to COVID-19 infection in NY.

Disclosures
All Authors: No reported disclosures
470. The Effects of Arrival Quarantine on Subsequent COVID-19 Testing in a Cohort of Military Basic Trainees
Authors: Marcus Joseph E , Frankel Dianne , Pawlak Mary , Casey Theresa , Enriquez Erin , Yun Heather 
Published: January 2021

Abstract

Background
The COVID-19 pandemic has been associated with significant spread in congregate settings and various forms of non-pharmaceutical interventions (NPI) have been implemented to prevent spread. Basic Military Training at Joint Base-San Antonio is the entrance to the US Air Force and has been associated with respiratory outbreaks in the past. A two-week arrival quarantine was implemented in March 2020. Effects on subsequent testing for COVID-19 after an arrival quarantine is unknown.

Methods
The first four weekly cohorts of trainees who underwent an arrival quarantine between March 16-April 13 were monitored during their 7 week training for COVID-19 symptoms. Symptoms, medical testing, and days removed from training were collected on every patient with possible COVID-19 symptoms including cough, shortness of breath, or fever. Testing during the two-week arrival quarantine were compared to the subsequent five weeks of training. Nominal variables were compared by chi squared or Fisher’s exact test as appropriate. Continuous variables were compared by Mann-Whitney U Test.

Results
A total of 2,573 started training during study period, 89 (3.4%) had symptoms concerning for COVID-19 and were tested. 5 (6%) patients tested positive, all of whom in the arrival quarantine. Compared to patients who completed quarantine (n=29), patients in the arrival quarantine who tested negative for COVID-19 (n=54) were tested more often (26 trainees a week vs. 5.8 later in training, p=&lt; 0.0001), and received more rapid flu tests (74% vs. 38%, p=0.001) and multiplex respiratory PCR (15% vs. 0%, p=0.05). Trainees in quarantine were isolated longer for symptoms than patients who completed quarantine (median 3 vs. 2, p=0.01). There was no difference in presenting symptoms for trainees in quarantine or after quarantine.

Conclusion
Arrival quarantine appears to be an effective NPI, which in conjunction with other interventions prevented any COVID-19 transmission after quarantine completion. For those who went through arrival quarantine, there was more intense initial testing and initial longer symptomatic patient isolation, this was balanced by fewer symptomatic patients, less testing, and shorter isolations later in training.

Disclosures
All Authors: No reported disclosures