bluuebunny/crossref_metadata_2025_split huggingface dataset:
INDUCTION AND ORIENTATION PRACTICES AND PERCEIVED EFFECT ON HEALTH WORK FORCE PERFORMANCE AND SATISFACTION IN PUBLIC HOSPITALS OF ILUBABOUR ZONE, OROMIA REGIONAL STATE, SOUTH WEST ETHIOPIA, 2018: FACILITY BASED CROSS SECTIONAL STUDY DESIGN WAS EMPLOYED
Authors: Ayana Sisay Siraj , Alaro Tesfamichael , Gebissa Feyera 
Published: January 2021

AbstractBackgroundSuccessful orientation speeds up the adaptation process by helping new employees feel comfortable in the organization and by making them more productive on the job. In today’s world most organization are recognizing that this type of simple generic orientation is not enough, a more complex employee orientation or on boarding process is required.ObjectiveTo assess induction and orientation practices and perceived effect on health work force performance and satisfaction in public hospitals of Ilubabour zone, Oromia regional state, south west Ethiopia, 2018.MethodsA Facility based cross sectional study was conducted by using both quantitative and qualitative methods. Quantitative data was collected by self-administered questionnaire and qualitative data was collected by in-depth interview with purposefully selected key informants using interviewer guide. The sample sizes for quantitative data were calculated by using single population proportion formula. Accordingly, a total of 403 samples were drawn from the source population by stratified sampling technique. Qualitative data of in-depth interview was transcribed, and thematically analyzed and triangulated with quantitative findings.ResultsOut of 388 only 135(34 %) respondents have attended induction and orientation training while assignment to different new responsibilities. The finding from key informants revealed that they take even for less than one day or an hour. Regarding the practices held during the training; only proper welcoming them to the organization and department was practiced, the rest practices like sharing the organization vision, involving senior leaders and post training evaluation was responded that they were exercised poorly within the organizations. Only 53.1% responded that induction and orientation training have perceived effect on employee Performance while 46.7% of respondents do not. About 55.7% respondents said that induction and orientation training have perceived effect on employees’ job satisfaction and the remaining responded to have no effect on employee’s satisfaction.ConclusionGenerally, the induction and orientation practice was poor so as the supportive supervision and post training evaluation. More than half of the respondents perceived that it has effect on performance and satisfaction and the rest did not understand its specific effects.
Issues of Random Sampling with Rapid Antigen Tests for COVID-19 Diagnosis: A Special Reference to Kalmunai RDHS Division
Authors: Razmy AM , Junaideen SM 
Published: January 2021

AbstractRandom sampling from the community and performing the rapid antigen test has become a debatable issue during this COVID-19 pandemic. This writing analyzes the concerns using the data from Kalmunai RDHS Division, Sri Lanka, related to COVID-19 and shows the issues of random sampling in a community wherein the incident rate is small. Therefore, suitable sampling protocol is to be developed for performing rapid antigen test for COVID-19 diagnosis.
BAYESIAN GROUP TESTING WITH DILUTION EFFECTS
Authors: Tatsuoka Curtis , Chen Weicong , Lu Xiaoyi 
Published: January 2021

SummaryA Bayesian framework for group testing under dilution effects has been developed, using latticebased models. This work has particular relevance given the pressing public health need to enhance testing capacity for COVID-19 and future pandemics, and the need for wide-scale and repeated testing for surveillance under constantly varying conditions. The proposed Bayesian approach allows for dilution effects in group testing and for general test response distributions beyond just binary outcomes. It is shown that even under strong dilution effects, an intuitive group testing selection rule that relies on the model order structure, referred to as the Bayesian halving algorithm, has attractive optimal convergence properties. Analogous look-ahead rules that can reduce the number of stages in classification by selecting several pooled tests at a time are proposed and evaluated as well. Group testing is demonstrated to provide great savings over individual testing in the number of tests needed, even for moderately high prevalence levels. However, there is a trade-off with higher number of testing stages, and increased variability. A web-based calculator is introduced to assist in weighing these factors and to guide decisions on when and how to pool under various conditions. High performance distributed computing methods have also been implemented for considering larger pool sizes, when savings from group testing can be even more dramatic.
Genomics of Aminoglycoside Resistance in Pseudomonas aeruginosa Bloodstream Infections at a United States Academic Hospital
Authors: Atassi Giancarlo , Scheetz Marc , Nozick Sophia , Rhodes Nathaniel J. , Murphy-Belcaster Megan , Murphy Katherine R , Ozer Egon A. , Hauser Alan R. 
Published: January 2021

AbstractPseudomonas aeruginosa is a frequent cause of antibiotic-resistant infections. Although P. aeruginosa is intrinsically resistant to many antimicrobial agents, aminoglycosides are active against this organism in the absence of acquired resistance determinants and mutations. However, genes encoding aminoglycoside modifying enzymes (AMEs) are found in many strains that are resistant to these agents. We examined the prevalence of phenotypic resistance to the commonly used aminoglycosides gentamicin, tobramycin, and amikacin in a collection of 227 P. aeruginosa bloodstream isolates collected over two decades from a single U.S. academic medical institution. Resistance to these antibiotics was relatively stable over this time period. High-risk clones ST111 and ST298 were initially common but decreased in frequency over time. Whole genome sequencing identified relatively few AME genes in this collection compared to the published literature; only 14% of isolates contained an AME gene other than the ubiquitous aph(3’)-IIb. Of those present, only ant(2”)-Ia was associated with phenotypic resistance to gentamicin or to tobramycin. One extensively drug-resistant strain, PS1871, contained 5 AME genes, most of which were part of clusters of antibiotic resistance genes embedded within transposable elements. These findings suggest that AME genes play a relatively minor role in aminoglycoside resistance at our institution but that multidrug-resistant strains remain a problem.
The management of Moderate Acute Malnutrition (MAM) in children aged 6-59 months: A systematic review and meta-analysis
Authors: Gluning I , Kerac M , Bailey J , Bander A , Opondo C 
Published: January 2021

AbstractBackgroundMalnutrition is a leading cause of morbidity and mortality in children aged under five years, especially in low- and middle-income countries (LMICs). Although severe acute malnutrition (SAM) is considered the most serious form of malnutrition, moderate acute malnutrition (MAM) affects greater numbers globally and, unlike SAM, guidelines lack a robust evidence-base. This systematic review and meta-analysis assessed the evidence for lipid-based nutrient supplements (LNS), fortified-blended-flours (FBF) and nutrition counselling, in the treatment of MAM.MethodsFive databases were systematically searched for studies conducted in LMICs that compared the effectiveness of food-based products versus any comparator group in promoting recovery from MAM in children aged 6-59 months. Where appropriate, pooled estimates of effect were estimated using random-effects meta-analyses.ResultsA total of thirteen trials were identified for inclusion. All used active controls rather than ‘standard care’, which is often minimal in most settings. There was evidence of increased probability of recovery (as assessed by gaining normal weight-for-height and/or MUAC) among children treated with LNS compared to children treated with FBF (RR 1·05, 95%CI 1·01-1·09, p=0·009). Treatment with an LNS was also associated with a lower risk of persistent MAM at the end of treatment compared with a FBF (RR 0·82, 95%CI 0·71-0·95, p=0·007).ConclusionBased on a relatively small number of studies mainly from Africa, LNS are superior to FBF in improving anthropometric recovery from MAM. The true benefit of MAM treatment may be underestimated due to all studies using active controls rather than usual care which is minimal.More high-quality evidence is needed to evaluate nutrition education/counselling alone as a MAM intervention. Studies should also assess a wider range of outcomes including body composition, morbidity and development – not weight-gain alone.
Sword of Damocles or choosing well. Population genetics sheds light into the future of the COVID-19 pandemic and SARS-CoV-2 new mutant strains
Authors: García de Alcañíz J. G. , López-Rodas V. , Costas E. 
Published: January 2021

AbstractAn immense scientific effort has been made worldwide due to Covid-19’s pandemic magnitude. It has made possible to identify almost 300,000 SARS-CoV-2 different genetic variants, connecting them with clinical and epidemiological findings. Among this immense data collection, that constitutes the biggest evolutionary experiment in history, is buried the answer to what will happen in the future. Will new strains, more contagious than the current ones or resistant to the vaccines, arise by mutation? Although theoretic population genetics is, by far, the most powerful tool we have to do an accurate prediction, it has been barely used for the study of SARS-CoV-2 due to its conceptual difficulty. Having in mind that the size of the SARS-CoV-2 population is astronomical we can apply a discrete treatment, based on the branching process method, Fokker-Plank equations and Kolmogoroff’s forward equations, to calculate the survival likelihood through time, to elucidate the likelihood to become dominant genotypes and how long will this take, for new SARS-CoV-2 mutants depending on their selective advantage. Results show that most of the new mutants that will arise in the SARS-CoV-2 meta-population will stay at very low frequencies. However, some few new mutants, significantly more infectious than current ones, will still emerge and become dominant in the population favoured by a great selective advantage. Far from showing a “mutational meltdown”, SARS-CoV-2 meta-population will increase its fitness becoming more infective. There is a probability, small but finite, that new mutants arise resistant to some vaccines. High infected numbers and slow vaccination programs will significantly increase this likelihood.
Development of Predictive Risk Models for All-cause Mortality in Pulmonary Hypertension using Machine Learning
Authors: Zhou Jiandong , Wong Ka Hei Gabriel , Lee Sharen , Liu Tong , Kit Leung Keith Sai , Jeevaratnam Kamalan , Yung Cheung Bernard Man , Kei Wong Ian Chi , Zhang Qingpeng , Tse Gary 
Published: January 2021

AbstractBackgroundPulmonary hypertension, a progressive lung disorder with symptoms such as breathlessness and loss of exercise capacity, is highly debilitating and has a negative impact on the quality of life. In this study, we examined whether a multi-parametric approach using machine learning can improve mortality prediction.MethodsA population-based territory-wide cohort of pulmonary hypertension patients from January 1, 2000 to December 31, 2017 were retrospectively analyzed. Significant predictors of all-cause mortality were identified. Easy-to-use frailty indexes predicting primary and secondary pulmonary hypertension were derived and stratification performances of the derived scores were compared. A factorization machine model was used for the development of an accurate predictive risk model and the results were compared to multivariate logistic regression, support vector machine, random forests, and multilayer perceptron.ResultsThe cohorts consist of 2562 patients with either primary (n=1009) or secondary (n=1553) pulmonary hypertension. Multivariate Cox regression showed that age, prior cardiovascular, respiratory and kidney diseases, hypertension, number of emergency readmissions within 28 days of discharge were all predictors of all-cause mortality. Easy-to-use frailty scores were developed from Cox regression. A factorization machine model demonstrates superior risk prediction improvements for both primary (precision: 0.90, recall: 0.89, F1-score: 0.91, AUC: 0.91) and secondary pulmonary hypertension (precision: 0.87, recall: 0.86, F1-score: 0.89, AUC: 0.88) patients.ConclusionWe derived easy-to-use frailty scores predicting mortality in primary and secondary pulmonary hypertension. A machine learning model incorporating multi-modality clinical data significantly improves risk stratification performance.
The Socioeconomic Impact of COVID-19 in Urban Informal Settlements
Authors: Gil Diego , Domínguez Patricio , Undurraga Eduardo A. , Valenzuela Eduardo 
Published: January 2021

AbstractThe COVID-19 pandemic has reached almost every corner of the world. Without a pharmaceutical solution, governments have been forced to implement regulations and public policies to control social behavior and prevent the spread of the virus. There is dramatic evidence of the social and economic effects of these measures and their disparate impact on vulnerable communities. Individuals living in urban informal settlements are in a structurally disadvantaged position to cope with a health crisis such as the COVID-19 pandemic. This paper examines the socioeconomic impact of the crisis brought by the pandemic in informal settlements in Chile. We use a three-wave panel study to compare the situation in informal settlements before and during the health crisis. We show that households living in informal settlements are paying a high toll. Their employment loss is dramatic, substantially larger than the loss reported in the general population, and has particularly affected the inmigrant population. We also find that the pandemic has triggered neighborhood cooperation within the settlements. Targeted government assistance programs have reached these communities; however, this group’s coverage is not enough to counteract the magnitude of the crisis. Our results suggest that governments, the non-profit sector, and the community need to urgently provide economic support and protections to individuals living in informal settlements and consider this opportunity for long-term improvements in these marginalized communities.HighlightsGovernments have implemented large-scale non-pharmaceutical interventions to control the spread of the COVID-19 pandemicThese measures have had dramatic social and economic effects on the population, particularly affecting vulnerable communitiesIndividuals living in urban informal settlements are in a structurally disadvantaged position to cope with this crisisUsing panel data, we document a dramatic employment loss among informal settlements dwellers, substantially larger than the general populationThe pandemic has also triggered neighborhood cooperation within the settlements as well as targeted government assistance, but not enough to counteract the magnitude of the economic loss
Meta-Analysis of Robustness of COVID-19 Diagnostic Kits During Early Pandemic
Authors: Shanmugam Chandrakumar , Behring Michael , Luthra Vishwas , Leal Sixto M , Diffalha Sameer Al , Varambally Sooryanarayana , Netto George J , Manne Upender 
Published: January 2021

ABSTRACTBackgroundAccurate detection of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) is necessary to mitigate the coronavirus disease-19 (COVID-19) pandemic. However, the test reagents and assay platforms are varied and may not be sufficiently robust to diagnose COVID-19.MethodsWe reviewed 85 studies (21,530 patients), published from five regions of the world, to highlight issues involved in the diagnosis of COVID-19 in the early phase of the pandemic, following the standards outlined in the PRISMA statement. All relevant articles, published up to May 31, 2020, in PubMed, BioRiXv, MedRiXv, and Google Scholar, were included. We evaluated the qualitative (9749 patients) and quantitative (10,355 patients) performance of RT-PCR and serologic diagnostic tests for real-world samples, and assessed the concordance (5,538 patients) between methods in meta-analyses.ResultsThe RT-PCR tests exhibited heterogeneity in the primers and reagents used. Of 1,957 positive RT-PCR COVID-19 participants, 1,585 had positive serum antibody (IgM +/- IgG) tests (sensitivity 0.81, 95%CI 0.66-.90). While 3,509 of 3581 participants RT-PCR negative for COVID-19 were found negative by serology testing (specificity 0.98, 95%CI 0.94-0.99). The chemiluminescent immunoassay exhibited the highest sensitivity, followed by ELISA and lateral flow immunoassays. Serology tests had higher sensitivity and specificity for laboratory-approval than for real-world reporting data.ConclusionsThe robustness of the assays/platforms is influenced by variability in sampling and reagents. Serological testing complements and may minimize false negative RT-PCR results. Lack of standardized assay protocols in the early phase of pandemic might have contributed to the spread of COVID-19.
Exposure to glucagon-like peptide 1 receptor (GLP-1R) agonists reduces glaucoma risk
Authors: Sterling Jacob K. , Hua Peiying , Dunaief Joshua L. , Cui Qi N. , VanderBeek Brian L. 
Published: January 2021

AbstractImportanceGlucagon-like peptide-1 receptor (GLP-1R) agonists regulate blood glucose and are commonly used to treat Type II Diabetes Mellitus. Recent work has shown that treatment with the novel GLP-1R agonist, NLY01, decreased retinal neuroinflammation and glial activation to rescue retinal ganglion cells in an animal model of glaucoma.ObjectiveIn this study, we used an insurance claims database to examine whether GLP-1R agonist exposure impacts glaucoma risk.Design, Setting, and ParticipantsA retrospective cohort of adult patients who initiated a new GLP-1R agonist (i.e., exenatide, liraglutide, albiglutide, dulaglutide, semaglutide, or lixisenatide) was 1:3 age, gender, race, active diabetes medication classes, and year of index date matched to a cohort of patients who initiated a different class of oral diabetic medication during their time in the database. Exclusion occurred for <2 years in the database, age <18 years old, no visit to an eyecare provider prior to the index date, a prior diagnosis of glaucoma, glaucoma suspect, or ocular hypertension, or prior glaucoma medication, procedure, or surgery. Diabetes severity was assessed using hemoglobin A1c and the Diabetes Complications Severity Index (DCSI), a validated metric based on six categories of diabetic complications. Inverse probability of treatment weighting (IPTW) was used within a multivariable Cox proportional hazard regression model to test the association between GLP-1R agonist exposure and the primary outcome. IPTW was derived from a propensity score model based on the DCSI, HbA1c, demographic factors and other systemic health conditions.ExposureGlucagon-like peptide 1 receptor agonist.Main Outcomes and MeasuresNew diagnosis of primary open angle glaucoma, glaucoma suspect, or low tension glaucoma.ResultsCohorts were comprised of 1,961 new users of GLP-1R agonists matched to 4,371 unexposed controls. After IPTW, age was the only covariate imbalanced (SMD >0.1) between cohorts. Ten new diagnoses of glaucoma (0.51%) were present in the GLP-1R agonist cohort compared to 58 (1.33%) in the unexposed controls. After adjustment, GLP-1R exposure conferred a reduced hazard of 0.54 (95%CI: 0.35-0.85, P =0.007), suggesting that GLP-1R agonists reduce the risk for glaucoma.Conclusions and RelevanceGLP-1R agonist use was associated with a statistically significant hazard reduction for a new glaucoma diagnosis. Our findings support further investigations into the use of GLP-1R agonists in glaucoma prevention.
TRACT revisited: an algebraic solution for determining overall rotational correlation times from cross-correlated relaxation rates
Authors: Robson Scott A. , Dağ Çağdaş , Wu Hongwei , Ziarek Joshua J. 
Published: January 2021

AbstractAccurate rotational correlation times (τc) are critical for quantitative analysis of fast timescale NMR dynamics. As molecular weights increase, the classic derivation ofτcusing transverse and longitudinal relaxation rates becomes increasingly unsuitable due to the non-trivial contribution of remote dipole-dipole interactions to longitudinal relaxation. Derivations using cross-correlated relaxation experiments, such as TRACT, overcome these limitations but are erroneously calculated in 65% of the citing literature. Herein, we developed an algebraic solutions to the Goldman relationship that facilitate rapid, point-by-point calculations for straightforward identification of appropriate spectral regions where global tumbling is likely to be dominant. The rigid-body approximation of the Goldman relationship has been previously shown to underestimate TRACT-based rotational correlation time estimates. This motivated us to develop a second algebraic solution that employs a simplified model-free spectral density function including an order parameter term that could, in principle, be set to an average backbone S2≈ 0.9 to further improve the accuracy ofτcestimation. These solutions enabled us to explore the boundaries of the Goldman relationship as a function of the H-N internuclear distance (r), difference of the two principal components of the axially-symmetric15N CSA tensor (ΔδN), and angle of the CSA tensor relative to the N-H bond vector (θ). We hope our algebraic solutions and analytical strategies will increase the accuracy and application of the TRACT experiment.
Modeling and Simulation: A study on predicting the outbreak of COVID-19 in Saudi Arabia
Authors: Msmali Ahmed , Mutum Zico , Mechai Idir , Ahmadini Abdullah 
Published: January 2021

AbstractThe novel coronavirus (Covid-19) infection has resulted in an ongoing pandemic affecting health system and economy of more than 200 countries around the world. Mathematical models are used to predict the biological and epidemiological trends of an epidemic and develop methods for controlling it. In this work, we use mathematical model perspective to study the role of behavior change in slowing the spread of the COVID-19 disease in Saudi Arabia. The real-time updated data from 1st May 2020 to 8th January 2021 is collected from Saudi Ministry of Health, aiming to provide dynamic behaviors of the pandemic in Saudi Arabia. During this period, it has infected 297,205 people, resulting in 6124 deaths with the mortality rate 2.06 %. There is weak positive relationship between the spread of the infection and mortality (R2 =0.412). We use Susceptible-Exposed-Infection-Recovered (SEIR) mode, the logistic growth model and with special focus on the exposed, infection and recovery individuals to simulate the final phase of the outbreak. The results indicate that social distancing, good hygienic conditions, and travel limitation are the crucial measures to prevent further spreading of the epidemic.