bluuebunny/crossref_metadata_2025_split huggingface dataset:
Balancing Scarce Hospital Resources During a Pandemic: A Case-Study of COVID-19 at Addenbrooke’s Hospital (UK)
Authors: Melman George J. , Parlikad Ajith K. , Cameron Ewen A.B. 
Published: October 2020

Abstract
COVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke's hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.
Reducing the use of empiric antibiotic therapy in patients on admission to the hospital with COVID-19
Authors: Pettit Natasha N. , Nguyen Cynthia T. , Lew Alison , Bhagat Palak B. , Nelson Allison , Olson Gregory , Ridgway Jessica , Pho Mai T. , Pagkas-Bather Jade 
Published: October 2020

Abstract
Background: Empiric antibiotics for community acquired bacterial pneumonia (CABP) are often prescribed to patients with COVID-19, despite a low reported incidence of co-infections. Stewardship interventions targeted at facilitating appropriate antibiotic prescribing for CABP among COVID-19 patients are needed. We developed a guideline for antibiotic initiation and discontinuation for CABP in COVID-19 patients. The purpose of this study was to assess the impact of this intervention on the duration of empiric CABP antibiotic therapy among patients with COVID-19.Methods: This was a single-center, retrospective, quasi-experimental study of adult patients admitted between 3/1/2020 to 4/25/2020 with COVID-19 pneumonia, who were initiated on empiric CABP antibiotics. Patients were excluded if they were initiated on antibiotics >48hours following admission or if another infection was identified. The primary outcome was the duration of antibiotic therapy (DOT) prior to the guideline (March 1 to March27, 2020) and after guideline implementation (March 28 to April 25, 2020). We also evaluated the clinical outcomes (mortality, readmissions, length of stay) among those initiated on empiric CABP antibiotics.Results: A total of 506 patients with COVID-19 were evaluated, 102 pre-intervention and 404 post-intervention. Prior to the intervention, 74.5% (n=76) of patients with COVID-19 received empiric antibiotics compared to only 42% of patients post-intervention (n=170), p<0.001. The median DOT in the post-intervention group was 1.3 days shorter (p<0.001) than the pre-intervention group, and atypical antibiotic DOT was reduced by 2.8 days (p<0.001). More patients in the post-intervention group were initiated on antibiotics based on criteria consistent with our guideline (68% versus 87%, p=0.001). There were no differences between groups in terms of clinical outcomes.Conclusion: Following the implementation of a guideline outlining recommendations for initiating and discontinuing antibiotics for CABP among COVID-19 inpatients, we observed a reduction in antibiotic prescribing and DOT. The guideline also resulted in a significant increase in the rate of guideline-congruent empiric antibiotic initiation.
Identification of potential biomarkers and inhibitors in SARS-CoV-2 infected macaques
Authors: Gu Hanming , Wang Wei , Yuan Gongsheng 
Published: October 2020

Abstract
The COVID-19 pandemic caused by the infection with SARS-CoV-2 has overwhelmed many health systems globally. Our study is to identify differentially expressed genes (DEGs) and the associated biological pathways of COVID-19 to elucidate the potential pathogenesis and metabolism. The gene expression profile of the GSE155363 dataset was originally produced using the high-throughput Illumina HiSeq 4000 (Macaca mulatta). Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed to discover their functional categories and biochemical pathways. The results suggested that four biological pathways: Fatty acid elongation, Biosynthesis of unsaturated fatty acids, Fatty acid metabolism, and Ribosome were mostly involved in the macaques with COVID-19. Thus, our study provides novel insights into the underlying pathogenesis of COVID-19.
Can Cytokines be used as an Activation Marker in Rheumatoid Arthritis?
Authors: Kaya Fatih Öner , Ceylan Yeşim , İpek Belkız Öngen , Özünal Zeynep Güneş , Sezgin Gülbüz , Nalbant Selim 
Published: October 2020

Aims:
The etiopathogenesis of Rheumatoid Arthritis (RA) is not clearly understood.
However, the role of the cytokines play an important part in this mechanism. We aimed to bring a
new approach to the concept of 'remission' in patients with RA.

Background:
RA is a chronic, autoimmune, inflammatory disease that involves small joints in the
form of symmetrical polyarthritis and progresses with exacerbations and remissions. Pain,
swelling, tenderness and morning stiffness are typical of the joints involved. Although it is approached
as primary joint disease, a wide variety of extra-articular involvements may also occur. It
is an interesting pathophysiological process, the exact cause of which is still unknown, with many
environmental, genetic and potentially undiscovered possible factors in a chaotic manner.

Objective:
In this cross-sectional study, sedimentation rate (ESR), C- Reactive protein (CRP), Tumor
necrosis factor (TNF)-α, soluble-TNF-α receptor (TNF-R), Interleukin (IL)-1B and IL-10
were measured in three groups which were healthy volunteers, patients with RA in the active period,
and patients with RA in remission. Disease activity score-28 (DAS-28) was calculated in active
RA and RA in remission.

Methods:
This study included 20 healthy volunteers, 20 remission patients with RA and 20 active
RA patients. Venous blood samples were collected from patients in both healthy and RA groups.

Results:
RA group consisted 43 (71.6%) female and 17 (28.4%) male. Control group consisted 11
(55%) female and 9 (45%) male. TNF-R was significantly high only in the active group according
to the healthy group (p=0.002). IL-10 was significantly high in active RA, according to RA in remission
(p=0.03). DAS-28 was significantly high in active RA, according to RA in remission
(p=0.001).

:
In the active RA group, ESR and TNF-R had a positive correlation (r:0.442; p=0.048). In the active
RA group, there was also a positive correlation between TNF-R and CRP (r:0.621; p=0,003). Both
healthy and active RA group had significant positive correlation between ESR and CRP (r: 0.481;
p=0.032 and r: 0,697; p=0,001 respectively).

Conclusion:
TNF-R can be the main pathophysiological factor and a marker showing activation.
TNF-R can be very important in revealing the effect of TNF on the disease and the value of this effect
in the treatment and ensuring the follow-up of the disease with CRP instead of ESR in activation.
A Study on Diverse Methods and Performance Measures in Sentiment Analysis
Authors: Sumathy Subramanian , Rani Meesala Shobha 
Published: October 2020

:
With the vast development of internet technology 2.0, millions of people are sharing their opinions on different
social networking sites. To obtain the necessary information from the huge volume of user-generated data, the attention on
sentiment analysis among the research community is growing. Growth and prominence of sentiment analysis is
synchronized with an increase in social media and networking sites. Users generally use natural language for speaking,
writing, and expressing their views based on various sentiment orientations, ratings, and the features of different products,
topics, and issues. This helps to produce ambiguity at the end of the customer's decision based on criticism to form an
opinion based on such comments. To overcome the challenges of user-generated content such as noisy, irrelevant
information and fake reviews, there is a significant demand for an effective methodology that emphasizes the need for
sentiment analysis. This study presents an exhaustive survey of the existing methodologies and highlights the challenges
and performance factors of various approaches of sentiment analysis including text preprocessing, opinion spam detection,
and aspect level sentiment analysis.

Background:
User-generated content is growing all over the globe and people more eagerly express their views on social
media towards various aspects. The opinionated text is difficult to interpret and arrive at a conclusion based on the feedback
gathered from reviews on various sites. Hence, the significance of sentiment analysis is growing to analyze the usergenerated data.

Objective:
The paper presents an exhaustive review that provides an overview of the pros and cons of the existing techniques
and highlights the current techniques in sentiment analysis namely text pre-processing, opinion spam detection, and aspect
level sentiment analysis based on machine learning and deep learning. This will be useful to researchers who focus on the
challenges very specifically and identify the most common challenges to work forward for a new solution.
Longitudinal Analysis of HIV Disclosure Intention: The Implication of Duration of Diagnosis Knowledge and CD4 Counts Among Asymptomatic Treatment-seeking People Living with HIV/AIDS
Authors: Olaseni A. O. 
Published: October 2020

Introduction:
The spate of non-disclosure among individuals diagnosed with Human-Immunodeficiency-Virus and Acquired-Immune-Deficiency-Syndrome (HIV/AIDS) has continually been a primary global concern, especially in developing countries. Meta-analysis findings in Nigeria reported poor disclosure rates of 12.5% - 39.5%, which were far below the average disclosure benchmark of 79.0% standard stipulated for developing nations by the World Health Organization. There is no consensus regarding the roles of CD4 counts in disclosure intention. In Nigeria, there is a paucity of literature providing detailed understanding of the predictors of disclosure intention by the duration of diagnosis knowledge and CD4 counts.

Methods:
This study, therefore, investigated the implication of duration of diagnosis knowledge and CD4 counts in the prediction of HIV disclosure intention among people seeking HIV treatment. Longitudinal survey research designs were adopted. 390 participants were purposively selected to respond to HIV Self-Disclosure Intention Index (α=0.92), while information on CD4 counts and Duration of Diagnosis Knowledge was obtained from the selected respondents’ case files periodically. Binomial logistic regression analysis was used to analyze data at 0.05. Respondents’ mean age was 39.5±10.5 years.

Results:
Findings revealed that the duration of diagnosis knowledge and CD4 counts interactively predicted the outcome of disclosure intention among treatment-seeking PLHIV. (χ2 = 12.78, df = 2, p < 0.001) and further showed that the likelihood of disclosing HIV positive status increases by 13% between Time 1 (OR = -0.49, p < 0.01; 95%CI = 01.14-12.74) and Time 2 (OR = -0.36, p < 0.05; 95%CI = 01.11-10.93). Increase in CD4 counts was also found to increase the likelihood of HIV self-disclosure by 15% between Time 1 (OR = - 0.84, p < 0.01; 95%CI = 01.09-03.06) and Time 2 (OR = - 0.99, p < 0.01; 95%CI = 00.29-03.06).

Conclusion:
It was concluded that the duration of diagnosis knowledge and CD4 counts have significant implications in determining the intention to disclose HIV positive status. The study limitations and recommendations were further discussed.
Attitudes Toward Caring for People Living with HIV/AIDS: A Cross-Sectional Study of Nursing Faculty in Six Countries
Authors: Leyva-Moral Juan. M. , Dominguez-Cancino Karen A. , Edwards Joan E. , Moriña-Soler David , Cesario Sandra K. , Guevara-Vasquez Genesis M. , Feijoo-Cid Maria , Palmieri Patrick A. 
Published: October 2020

Background:Since the earliest study about nursing faculty and student attitudes about caring for people living with HIV/AIDS (PLHIV) in 1992, there have been less than 20 additional studies reported in the literature. Yet, PLHIV continues to report stigma and experience discrimination. Nursing faculty attitudes are part of the informal curriculum. Negativity about caring for PLHIV can adversely impact student perceptions as well as their care. Current research in this area is essentially non-existent.Objective:To describe the attitudes of the university nursing faculty toward caring for PLHIV; and to identify the relationship between faculty attitudes and explanatory factors such as age, education, religion, nationality, teaching in a clinical setting, years of experience, and university attributes.Methods:This was a multicenter cross-sectional study with nonrandomized electronic purposeful sampling. The Healthcare Provider HIV/AIDS Stigma Scale (HPASS) is a 30-item scale with three subscales: Prejudice, stereotype, and discrimination. The English and Spanish versions of the HPASS exhibit stable psychometric properties for cross-cultural research. The HPASS was delivered to university nursing faculty in six countries across three continents.Results:A sample of 368 nursing faculty completed the HPASS. The mean composite score was 2.41 (SD = 0.69), six-point scale with lower scores indicating more positive attitudes, with subscale scores: Stereotypes 2.55 (SD = 0.84), discrimination 2.28 (SD = 0.74), and prejudices 2.41 (SD = 0.63). Peruvian faculty had the highest scores while Canadian had the lowest. Significant correlations were observed between attitudes and the three subscales, and between the three subscales and the composite score.Conclusion:Attitudes of the nursing faculty toward caring for PLHIV were slightly positive to slightly negative depending on the region and country. Knowledge deficiencies about HIV persist, incorrect beliefs are common, and attitudes appear to be influenced by culture. The correlation between subscales justifies continued research to implement targeted interventions. Education about HIV/AIDS can address knowledge deficits while structured interactions with PLHIV can facilitate experiential learning.
QueerVIEW: Protocol for a Technology-Mediated Qualitative Photo Elicitation Study With Sexual and Gender Minority Youth in Ontario, Canada
Authors: Craig Shelley L , Eaton Andrew D , Pascoe Rachael , Egag Egag , McInroy Lauren B , Fang Lin , Austin Ashley , Dentato Michael P 
Published: October 2020

Background
The experiences of resilience and intersectionality in the lives of contemporary sexual and gender minority youth (SGMY) are important to explore. SGMY face unique experiences of discrimination in both online and offline environments, yet simultaneously build community and seek support in innovative ways. SGMY who identify as transgender, trans, or gender nonconforming and have experiences with child welfare, homelessness, or immigration have been particularly understudied. A qualitative exploration that leverages technology may derive new understanding of the negotiations of risk, resilience, and identity intersections that impact the well-being of vulnerable SGMY.

Objective
The objectives of the QueerVIEW study were to (1) enhance understanding of SGMY identities, both online and offline, (2) identify experiences of intersectionality among culturally, regionally, and racially diverse SGMY in Ontario, Canada, (3) explore online and offline sources of resilience for SGMY, and (4) develop and apply a virtual photo elicitation methodological approach.

Methods
This is the first study to pilot a completely virtual approach to a photo elicitation investigation with youth, including data collection, recruitment, interviewing, and analysis. Recruited through social media, SGMY completed a brief screening survey, submitted 10 to 15 digital photos, and then participated in an individual semistructured interview that focused on their photos and related life experiences. Online data collection methods were employed through encrypted online file transfer and secure online interviews. Data is being analyzed using a constructivist grounded theory approach, with six coders participating in structured online meetings that triangulated photo, video, and textual data.

Results
Data collection with 30 participants has been completed and analyses are underway. SGMY expressed appreciation for the photo elicitation and online design of the study and many reported experiencing an emotional catharsis from participating in this process. It is anticipated that results will form a model of how participants work toward integrating their online and offline experiences and identities into developing a sense of themselves as resilient.

Conclusions
This protocol presents an innovative, technology-enabled qualitative study that completely digitized a popular arts-based methodology—photo elicitation—that has potential utility for contemporary research with marginalized populations. The research design and triangulated analyses can generate more nuanced conceptualizations of SGMY identities and resilience than more traditional approaches. Considerations for conducting online research may be useful for other qualitative research.

International Registered Report Identifier (IRRID)
DERR1-10.2196/20547
Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing
Authors: Izquierdo Jose Luis , Ancochea Julio ,   Savana COVID-19 Research Group, Soriano Joan B 
Published: October 2020

Background
Many factors involved in the onset and clinical course of the ongoing COVID-19 pandemic are still unknown. Although big data analytics and artificial intelligence are widely used in the realms of health and medicine, researchers are only beginning to use these tools to explore the clinical characteristics and predictive factors of patients with COVID-19.

Objective
Our primary objectives are to describe the clinical characteristics and determine the factors that predict intensive care unit (ICU) admission of patients with COVID-19. Determining these factors using a well-defined population can increase our understanding of the real-world epidemiology of the disease.

Methods
We used a combination of classic epidemiological methods, natural language processing (NLP), and machine learning (for predictive modeling) to analyze the electronic health records (EHRs) of patients with COVID-19. We explored the unstructured free text in the EHRs within the Servicio de Salud de Castilla-La Mancha (SESCAM) Health Care Network (Castilla-La Mancha, Spain) from the entire population with available EHRs (1,364,924 patients) from January 1 to March 29, 2020. We extracted related clinical information regarding diagnosis, progression, and outcome for all COVID-19 cases.

Results
A total of 10,504 patients with a clinical or polymerase chain reaction–confirmed diagnosis of COVID-19 were identified; 5519 (52.5%) were male, with a mean age of 58.2 years (SD 19.7). Upon admission, the most common symptoms were cough, fever, and dyspnea; however, all three symptoms occurred in fewer than half of the cases. Overall, 6.1% (83/1353) of hospitalized patients required ICU admission. Using a machine-learning, data-driven algorithm, we identified that a combination of age, fever, and tachypnea was the most parsimonious predictor of ICU admission; patients younger than 56 years, without tachypnea, and temperature <39 degrees Celsius (or >39 ºC without respiratory crackles) were not admitted to the ICU. In contrast, patients with COVID-19 aged 40 to 79 years were likely to be admitted to the ICU if they had tachypnea and delayed their visit to the emergency department after being seen in primary care.

Conclusions
Our results show that a combination of easily obtainable clinical variables (age, fever, and tachypnea with or without respiratory crackles) predicts whether patients with COVID-19 will require ICU admission.
Digital Support for Healthier Eating Habits Among Patients With Type 2 Diabetes: Protocol for a Randomized Clinical Trial Within Primary Care (HAPPY Trial)
Authors: Trolle Lagerros Ylva , Dahlgren Anna , Sjöblom Linnea , Bonn Stephanie E 
Published: October 2020

Background
Despite the large impact that dietary habits have in the management of diabetes, few tools for supporting healthy eating habits are available for persons with diabetes.

Objective
The aim of this randomized clinical trial is to evaluate the effect of a 12-week, mobile health (mHealth), app-based intervention promoting healthy eating habits among patients with type 2 diabetes.

Methods
The HAPPY (Healthy eating using APP technologY) trial is a randomized clinical trial with two arms aiming to include 200 patients, 18 years of age or older, with type 2 diabetes. Both women and men are eligible for inclusion. Study participants are randomized 1:1 to an intervention group, where they are instructed to use a smartphone app promoting healthy eating, or to a control group, where they receive standard primary care only, for a period of 12 weeks. Each week a new topic (eg, vegetable intake) is introduced via the app. After an introduction text, the user is given a topic-related activity to perform (eg, eat one additional serving of vegetables per day during that week). The app records daily progress and sends automatic reminders or feedback to the user. Dietary intake, body composition, clinical variables, and biomarkers are measured at baseline and at 3- and 6-month follow-ups. An extensive web-based questionnaire comprising several validated questionnaires assessing a number of lifestyle factors is distributed via email at baseline and at 3-, 6-, and 12-month follow-ups; lifestyle factors include, for example, sleep, physical activity, eating behavior, and health-related quality of life. The effect of the intervention on dietary intake (primary outcome) and on glycated hemoglobin and blood lipid levels, body composition, blood pressure, other lifestyle factors, and overall health (secondary outcomes) will be assessed.

Results
Data collection is ongoing. Recruitment of participants started in January 2019. Findings from the study are expected to be published by the end of 2021.

Conclusions
Technology development provides new ways to promote and support long-term adherence to healthier eating habits. mHealth-based approaches allow for real-time interaction and the delivery of an intervention at any time. Further, focusing on overall diet allows the user to apply new knowledge to current eating patterns, creating an individualized approach. In this study, we evaluate the effect of using a new smartphone app promoting healthy eating habits on dietary intake, clinical markers, and lifestyle factors among patients with type 2 diabetes.

Trial Registration
ClinicalTrials.gov NCT03784612; https://clinicaltrials.gov/ct2/show/NCT03784612

International Registered Report Identifier (IRRID)
DERR1-10.2196/24422