bluuebunny/crossref_metadata_2025 huggingface dataset:
Studying Institutional Situational Awareness Through Anonymous Incident Reporting
Authors: Kurapati Srikanth , Boyd Carter J. , King Timothy W. , Awad Samir S.
Published: June 2020

Background and Objectives:

The efficacy of anonymous incident reporting (AIR) is critical to creating a culture of safety. Prior studies have sought to establish AIR in a similar manner as aviation, nuclear power, and other industries. However, health care presents unique challenges that differ greatly from these industries. We present a straightforward method using statistical process control to study the progression and efficacy of AIR.

Methods:

This study represents a retrospective review of all anonymous incident reports and surgical critical events from 2012 to 2017 at a single-institution, 500-bed, university-based, metropolitan Veterans Affairs Administration Medical Center located in Texas. This work was approved by the Veterans Administration Quality Board and deemed to be an appropriate quality improvement project. This project did not require institutional review board approval.

Results:

There was an exponential increase in AIRs in the first 15 months from 1 report per month to 168 reports in the ninth month (1425% increase). The results then plateaued over time (first year: 1017, second year: 1634, and third year: 1938—common-cause variation). A logarithmic regression was performed for progression of AIRs per month yielding the equation y = −7E-13ln(x) + 142.92, Pearson Correlation Coefficient = 0.55, where y represents number of reports and x time by month. The highest number of Critical Incident Tracking Notification System (CITNS) reports was observed early in the self-reporting process and decreased over time (first year: 5, second year: 2, third year: 1, fourth year: 1, and fifth year: 0). The numbers of AIR and CITNS reports were found to be inversely related with a Pearson correlation coefficient of −0.4.

Conclusions:

Statistical process control can be applied to an institution's AIR program to study progression and situational awareness.
Impact of collision models on the physical properties and the stability of lattice Boltzmann methods
Authors: Coreixas C. , Wissocq G. , Chopard B. , Latt J.
Published: June 2020

The lattice Boltzmann method (LBM) is known to suffer from stability issues when the collision model relies on the BGK approximation, especially in the zero viscosity limit and for non-vanishing Mach numbers. To tackle this problem, two kinds of solutions were proposed in the literature. They consist in changing either the numerical discretization (finite-volume, finite-difference, spectral-element, etc.) of the discrete velocity Boltzmann equation (DVBE), or the collision model. In this work, the latter solution is investigated in detail. More precisely, we propose a comprehensive comparison of (static relaxation time based) collision models, in terms of stability, and with preliminary results on their accuracy, for the simulation of isothermal high-Reynolds number flows in the (weakly) compressible regime. It starts by investigating the possible impact of collision models on the macroscopic behaviour of stream-and-collide based D2Q9-LBMs, which clarifies the exact physical properties of collision models on LBMs. It is followed by extensive linear and numerical stability analyses, supplemented with an accuracy study based on the transport of vortical structures over long distances. In order to draw conclusions as generally as possible, the most common moment spaces (raw, central, Hermite, central Hermite and cumulant), as well as regularized approaches, are considered for the comparative studies. LBMs based on dynamic collision mechanisms (entropic collision, subgrid-scale models, explicit filtering, etc.) are also briefly discussed.

This article is part of the theme issue ‘Fluid dynamics, soft matter and complex systems: recent results and new methods’.
Compressibility in lattice Boltzmann on standard stencils: effects of deviation from reference temperature
Authors: Hosseini S. A. , Darabiha N. , Thévenin D.
Published: June 2020

With growing interest in the simulation of compressible flows using the lattice Boltzmann (LB) method, a number of different approaches have been developed. These methods can be classified as pertaining to one of two major categories: (i) solvers relying on high-order stencils recovering the Navier–Stokes–Fourier equations, and (ii) approaches relying on classical first-neighbour stencils for the compressible Navier–Stokes equations coupled to an additional (LB-based or classical) solver for the energy balance equation. In most cases, the latter relies on a thermal Hermite expansion of the continuous equilibrium distribution function (EDF) to allow for compressibility. Even though recovering the correct equation of state at the Euler level, it has been observed that deviations of local flow temperature from the reference can result in instabilities and/or over-dissipation. The aim of the present study is to evaluate the stability domain of different EDFs, different collision models, with and without the correction terms for the third-order moments. The study is first based on a linear von Neumann analysis. The correction term for the space- and time-discretized equations is derived via a Chapman–Enskog analysis and further corroborated through spectral dispersion–dissipation curves. Finally, a number of numerical simulations are performed to illustrate the proposed theoretical study.

This article is part of the theme issue ‘Fluid dynamics, soft matter and complex systems: recent results and new methods’.
On relaxation systems and their relation to discrete velocity Boltzmann models for scalar advection–diffusion equations
Authors: Simonis Stephan , Frank Martin , Krause Mathias J.
Published: June 2020

The connection of relaxation systems and discrete velocity models is essential to the progress of stability as well as convergence results for lattice Boltzmann methods. In the present study we propose a formal perturbation ansatz starting from a scalar one-dimensional target equation, which yields a relaxation system specifically constructed for its equivalence to a discrete velocity Boltzmann model as commonly found in lattice Boltzmann methods. Further, the investigation of stability structures for the discrete velocity Boltzmann equation allows for algebraic characterizations of the equilibrium and collision operator. The methods introduced and summarized here are tailored for scalar, linear advection–diffusion equations, which can be used as a foundation for the constructive design of discrete velocity Boltzmann models and lattice Boltzmann methods to approximate different types of partial differential equations.

This article is part of the theme issue ‘Fluid dynamics, soft matter and complex systems: recent results and new methods’.
The lattice Fokker–Planck equation for models of wealth distribution
Authors: Kaushal Shaurya , Ansumali Santosh , Boghosian Bruce , Johnson Merek
Published: June 2020

Recent work on agent-based models of wealth distribution has yielded nonlinear, non-local Fokker–Planck equations whose steady-state solutions describe empirical wealth distributions with remarkable accuracy using only a few free parameters. Because these equations are often used to solve the ‘inverse problem’ of determining the free parameters given empirical wealth data, there is much impetus to find fast and accurate methods of solving the ‘forward problem’ of finding the steady state corresponding to given parameters. In this work, we derive and calibrate a lattice Boltzmann equation for this purpose.

This article is part of the theme issue ‘Fluid dynamics, soft matter and complex systems: recent results and new methods’.
A lattice-Boltzmann free surface model for injection moulding of a non-Newtonian fluid
Authors: Chiappini Daniele
Published: June 2020

The aim of this work is to present a lattice Boltzmann (LB) model devoted to dealing with non-Newtonian free surface flow. The combination of LB solver with a free-surface model allows dealing with multiphase flows where the density ratio in between the two considered phases is so high that the lighter phase can be neglected. For this particular set of multiphase models, the interface between the two phases is numerically reconstructed and transported via a diffusion equation. Moreover, the application of a Carreau approach for viscosity modelling allows the introduction of effects related to shear stress on fluid flow evolution. Two different non-Newtonian silicon-like materials have been considered here, namely the polystyrene and acrylonitrile butadiene styrene. Here, the author, after the mandatory model validation with a reference configuration, presents some applications of injection moulding for two different test-cases: the former is the injection in a labyrinth-like gasket, whereas the latter is the injection in a porous media.

This article is part of the theme issue ‘Fluid dynamics, soft matter and complex systems: recent results and new methods’.
Boltzmann equation and hydrodynamic equations: their equilibrium and non-equilibrium behaviour
Authors: Verma Mahendra K.
Published: June 2020

This short article summarizes the key features of equilibrium and non-equilibrium aspects of Boltzmann and hydrodynamic equations. Under equilibrium, the Boltzmann equation generates uncorrelated random velocity that corresponds tok2energy spectrum for the Euler equation. The latter spectrum is produced using initial configuration with many Fourier modes of equal amplitudes but with random phases. However, for a large-scale vortex as an initial condition, earlier simulations exhibit a combination ofk−5/3(in the inertial range) andk2(for large wavenumbers) spectra, with the range ofk2spectrum increasing with time. These simulations demonstrate an approach to equilibrium or thermalization of Euler turbulence. In addition, they also show how initial velocity field plays an important role in determining the behaviour of the Euler equation. In non-equilibrium scenario, both Boltzmann and Navier–Stokes equations produce similar flow behaviour, for example, Kolmogorov’sk−5/3spectrum in the inertial range.

This article is part of the theme issue ‘Fluid dynamics, soft matter and complex systems: recent results and new methods’.
The Citation Cloud of a Biomedical Article: Enabling Citation Analysis
Authors: Smalheiser Neil R. , Schneider Jodi , Torvik Vetle I. , Fragnito Dean P. , Tirk Eric E.
Published: June 2020

Using open citations provided by iCite and other sources, we have built an extension to PubMed that allows any user to visualize and analyze the “citation cloud” around any target article A: the set of articles cited by A; those which cite A; those which are co-cited with A; and those which are bibliographically coupled to A. This greatly enables the study of citations by the scientific community. The Citation Cloud can be accessed by running any query on the Anne O’Tate value-added PubMed search interface http://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith_uic/AnneOTate.cgi and clicking on the Citations button next to any retrieved article.
A downscaling approach to compare COVID-19 count data from databases aggregated at different spatial scales
Authors: Python Andre , Bender Andreas , Blangiardo Marta , Illian Janine B. , Lin Ying , Liu Baoli , Lucas Tim , Tan Siwei , Wen Yingying , Svanidze Davit , Yin Jianwei
Published: June 2020

As the COVID-19 pandemic continues to threaten various regions around the world, obtaining accurate and reliable COVID-19 data is crucial for governments and local communities aiming at rigorously assessing the extent and magnitude of the virus spread and deploying efficient interventions. Using data reported between January and February 2020 in China, we compared counts of COVID-19 from near-real time spatially disaggregated data (city-level) with fine-spatial scale predictions from a Bayesian downscaling regression model applied to a reference province-level dataset. The results highlight discrepancies in the counts of coronavirus-infected cases at district level and identify districts that may require further investigation.
Assessment of clinical characteristics and mortality-associated factors in COVID-19 Critical cases in Kuwait
Authors: Ayed Mariam , Borahmah Abdulwahab A , Yazdani Anwar , Sultan Ahmad , Mossad Ahmad , Rawdhan Hanouf
Published: June 2020

Purpose

To assess the clinical characteristics and identify mortality predicting factors in intensive care unit (ICU)-admitted COVID-19 confirmed patients.

Methods

We recruited and analyzed COVID-19 infected adult patients (age≥ 18 years) who were admitted to the ICU at Jaber AlAhmad Al Sabah Hospital,Kuwait, between 1stMarch, 2020and 30thApril 2020. The patients were followed up to 20th May, 2020. The risk factors associated with in-hospital mortality were assessed using multiple regression analysis.

Results

We recruited a total of 103 ICU patients in this retrospective cohort. The median age of the patients was 53 years (Interquartile Range (IQR): 44-63 years). The fatality rate was 43.7%. Among the patients, majority were males (85.5%) and 38% patients had more than two comorbidities. Pre-existing hypertension (OR:3.2,95%CI: 1.2-8.9), moderate/severe ARDS (OR: 3.4, 95%CI: 1.1-10.8),lymphocyte counts <0.5 (OR: 6.1, 95%CI: 1.2-29.8)albumin < 22 (OR: 7.5, 95%CI: 2.1-26.2), procalcitonin >0.2 (OR: 3.8, 95%CI: 1.3-7.8), D-Dimer >1200 (OR: 5.1, 95%CI: 1.2-21.6), and the need forcontinuous renal replacement therapy (OR: 9.3, 95%CI: 2.4-36.2) weresignificantly associated with mortality.

Conclusion

This study describes the clinical characteristics and predictors ofmortality among ICU patients. Early identification of risk factors to mortality might help in their better outcome.
Predicting Antibody Developability from Sequence using Machine Learning
Authors: Chen Xingyao , Dougherty Thomas , Hong Chan , Schibler Rachel , Zhao Yi Cong , Sadeghi Reza , Matasci Naim , Wu Yi-Chieh , Kerman Ian
Published: June 2020

Antibodies are prominent therapeutic agents but costly to develop. Existing approaches to predict developability depend on structure, which requires expensive laboratory or computational work to obtain. To address this issue, we present a machine learning pipeline to predict developability from sequence alone using physicochemical and learned embedding features. Our approach achieves high sensitivity and specificity on a dataset of 2400 antibodies. These results suggest that sequence is predictive of developability, enabling more efficient development of antibodies.
Questionnaire based Prediction of Hypertension using Machine Learning
Authors: Chaturvedi Abhijat , Srivastava Siddharth , Rai Astha , Cheema A S , Chelimela Desham , Aravindakshan Rajeev
Published: June 2020

Machine Learning has proven its ability in healthcare as an assisting technology for health care providers either by saving precious time or timely alerts or vitals monitoring. However, their application in real world is limited by availability of data. In this paper, we show that simple machine learning algorithms especially neural networks, if designed carefully, are extremely effective even with limited amount of data. Specifically with exhaustive experiments on standard Modified National Institute of Standards and Technology database (MNIST) dataset we analyse the impact of various parameters for effective performance. Further, on a custom dataset collected at a tertiary care hospital for hypertension analysis, we apply these design considerations to achieve better performance as compared to competitive baselines. On a real world dataset of only a few hundred patients, we show the effectiveness of these design choices and report an accuracy of 75% in determining whether a patient suffers from hypertension.
Clinical Outcomes of Patients with COVID-19 and Chronic Inflammatory and Autoimmune Rheumatic Diseases: A Multicentric Matched-Cohort Study
Authors: Pablos José L. , Galindo María , Carmona Loreto , Retuerto Miriam , Lledó Ana , Blanco Ricardo , González-Gay Miguel A. , Martinez-Lopez David , Castrejón Isabel , Álvaro-Gracia José M. , Fernández-Fernández David , Mera-Varela Antonio , Manrique-Arija Sara , Mena-Vázquez Natalia , Fernández-Nebro Antonio ,   RIER investigators group
Published: June 2020

Background

The impact of inflammatory rheumatic diseases on COVID-19 severity is poorly known. Here we compare the outcomes of a cohort of rheumatic patients with a matched control cohort to identify potential risk factors for severe illness.

Methods

In this comparative cohort study, we identified hospital PCR+ COVID-19 rheumatic patients with chronic inflammatory arthritis (IA) or autoimmune/immunomediated diseases (AI/IMID). Non-rheumatic controls were randomly sampled 1:1, and matched by age, sex, and PCR date. The main outcome was severe COVID-19, defined as death, invasive ventilation, ICU admission, or serious complications. We assessed the association between the outcome and potential prognostic variables, adjusted by COVID treatment, using logistic regression.

Results

The cohorts were composed of 456 rheumatic and non-rheumatic patients, in equal numbers. Mean age was 63 [IQR 53-78] and male sex 41% in both cohorts. Rheumatic diseases were IA (60%) and AI/IMID (40%). Most patients (74%) had been hospitalised, and the risk of severe COVID was 31.6% in the rheumatic and 28.1% in the non-rheumatic cohort. Ageing, male sex and previous comorbidity (obesity, diabetes, hypertension, cardiovascular, or lung disease) increased the risk in the rheumatic cohort by bivariate analysis. In logistic regression analysis, independent factors associated with severe COVID were increased age (OR 5.31; CI 3.14-8.95), male sex (2.13; CI 1.35-3.36) and having an AI/IMID (OR 1.98; CI 1.15-3.41).

Conclusion

In patients with chronic inflammatory rheumatic diseases aging, sex and having an AI/IMID but not IA nor previous immunosuppressive therapies were associated with severe COVID-19.
The influence of comorbidity on the severity of COVID-19 disease: A systematic review and analysis
Authors: Zaki Nazar , Mohamed Elfadil A. , Ibrahim Sahar , Khan Gulfaraz
Published: June 2020

Background

A novel form of coronavirus disease (SARS-CoV-2) has spread rapidly across the world. What risk factors influence the severity of the disease is of considerable importance.

Aim

This research offers a systematic review and meta-analysis of the correlation between common clinical conditions and comorbidities and the severity of COVID-19.

Methodology

Two independent researchers searched Europe PMC, Google Scholar, and PubMed databases for articles related to influence comorbidities have on the progress of the disease. A search engine was also created to screen a further 59,000 articles in COVID-19 Open Research Dataset (CORD-19). Random-effects modeling was used to pool 95% confidence intervals (CIs) and odds ratios (ORs). The significance of all comorbidities and clinical conditions to the severity of the disease was evaluated by employing machine-learning techniques. Publication bias was assessed by using funnel-plots and Egger's test. Heterogeneity was tested using I2.

Results

The meta-analysis incorporated 12 studies spanning 4,101 confirmed COVID-19 patients who were admitted to Chinese hospitals. The prevalence of the most commonly associated co-morbidities and their corresponding odds ratio for disease severity were as follows: coronary heart disease (OR 2.97 [CI: 1.99-4.45], p < 0.0001), cancer (OR 2.65 [CI: 1.12-6.29], p < 0.03), cardiovascular disease (OR 2.89 [CI: 1.90-4.40], p < 0.0001), COPD (OR 3.24 [CI: 1.66-6.32], p = 0.0), and kidney disease (OR 2.2.4 [CI: 1.01-4.99], p = 0.05) with low or moderate level of heterogeneity. The most frequently exhibited clinical symptoms were fever (OR 1.37 [CI: 1.01-1.86], p = 0.04), myalgia/fatigue (OR 1.31 [CI: 1.11-1.55], p = 0.0018), and dyspnea (OR 3.61, [CI: 2.57-5.06], p = <0.0001). No significant associations between disease severity and liver disease, smoking habits, and other clinical conditions, such as a cough, respiratory/ARDS, diarrhea or chest tightness/pain were found. The meta-analysis also revealed that the incubation period was positively associated with disease severity.

Conclusion

Existing comorbidities, including COPD, cardiovascular disease, and coronary heart disease, increase the severity of COVID-19. Some studies found a statistically significant association between comorbidities such as diabetes and hypertension and disease severity. However, these studies may be biased due to substantial heterogeneity.
Covid-19 Pandemic- Pits and falls of major states of India
Authors: Singh Abhinesh , Gupte Samriddhi S
Published: June 2020

Covid-19, just like SARS and MERS before it, is a disease caused by corona virus and can lead to severe respiratory diseases in humans. With the outbreak of novel corona virus, WHO on 30thJanuary 2020 declared it a Public Health Emergency and further on 11thMarch 2020, Covid-19 disease was declared a pandemic. India in the initial stages of the pandemic dealt with it in a very effective manner. With timely implementation of lockdown, India was able to contain the spread of Covid-19 to some extent. However with the recently announced Unlock 1.0, the SARS CoV-2 is expected to spread. This study aims to track and analyze the Covid-19 situation in major states that constitute of 70 percent of the total cases. Thus the states selected for the study are: Maharashtra, Delhi, Tamil Nadu, Gujarat, Uttar Pradesh and Rajasthan. These are the states which had more than ten thousand Covid-19 patients as/on June 10th2020. The analysis period is from March 25thto June 10thand the data source is India’s Covid-19 tracker. To assess the previous and current Covid-19 situations in these states indicators such as Active rates, Recovery rate, Case fatality rate, Test positivity rate, tests per million, cases per million, test per confirmed case has been used. The study finds that although the absolute number of active cases may be rising, however it is showing a decreasing trend with an increase in recovery rates. With increasing number of Covid-19 cases, testing also has increased however not in the similar proportion and thus by developed nation standard we are lagging. With increasing TPR and cases per million, Delhi is well on its way to surpass even Mumbai which till now has proven to be worst hit in this pandemic. An interesting finding is that of test per confirmed case which shows that every 6thperson in Maharashtra and every 8thin Delhi is showing positive result of Covid-19 test. Given such an increase and unlocked India, Delhi might soon enter into the third stage of community transmission where source of 50 percent or more cases would be unknown. There has been an increase in the Covid-19 related health infrastructure with the public-private partnership which involved both private hospitals and lab joining hands to battle Covid-19, however, affordability still remains an issue. If experts are to be believed, pandemic isn’t over because we’ve unlocked. The worst is yet to come as Covid-19 is predicted to peak in mid-July to August in India. Thus, it’d be advisable to not venture out unnecessarily just because restrictions have been lifted. Also, following the guidelines-hand-washing, avoiding public gathering, social distancing and covering nose and mouth has now become imperative.
Racial and ethnic determinants of Covid-19 risk
Authors: Lo Chun-Han , Nguyen Long H. , Drew David A. , Graham Mark S. , Warner Erica T. , Joshi Amit D. , Astley Christina M. , Guo Chuan-Guo , Ma Wenjie , Mehta Raaj S. , Kwon Sohee , Song Mingyang , Davies Richard , Capdevila Joan , Lee Karla A. , Lochlainn Mary Ni , Varsavsky Thomas , Sudre Carole H. , Wolf Jonathan , Cozier Yvette C. , Rosenberg Lynn , Wilkens Lynne R. , Haiman Christopher A. , Le Marchand Loïc , Palmer Julie R. , Spector Tim D. , Ourselin Sebastien , Steves Claire J. , Chan Andrew T.
Published: June 2020

Background

Racial and ethnic minorities have disproportionately high hospitalization rates and mortality related to the novel coronavirus disease 2019 (Covid-19). There are comparatively scant data on race and ethnicity as determinants of infection risk.

Methods

We used a smartphone application (beginning March 24, 2020 in the United Kingdom [U.K.] and March 29, 2020 in the United States [U.S.]) to recruit 2,414,601 participants who reported their race/ethnicity through May 25, 2020 and employed logistic regression to determine the adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for a positive Covid-19 test among racial and ethnic groups.

Results

We documented 8,858 self-reported cases of Covid-19 among 2,259,841 non-Hispanic white; 79 among 9,615 Hispanic; 186 among 18,176 Black; 598 among 63,316 Asian; and 347 among 63,653 other racial minority participants. Compared with non-Hispanic white participants, the risk for a positive Covid-19 test was increased across racial minorities (aORs ranging from 1.24 to 3.51). After adjustment for socioeconomic indices and Covid-19 exposure risk factors, the associations (aOR [95% CI]) were attenuated but remained significant for Hispanic (1.58 [1.24-2.02]) and Black participants (2.56 [1.93-3.39]) in the U.S. and South Asian (1.52 [1.38-1.67]) and Middle Eastern participants (1.56 [1.25-1.95]) in the U.K. A higher risk of Covid-19 and seeking or receiving treatment was also observed for several racial/ethnic minority subgroups.

Conclusions

Our results demonstrate an increase in Covid-19 risk among racial and ethnic minorities not completely explained by other risk factors for Covid-19, comorbidities, and sociodemographic characteristics. Further research investigating these disparities are needed to inform public health measures.
Design and clinical validation of a 3D-printed nasopharyngeal swab for COVID-19 testing
Authors: Tay Joshua K , Cross Gail B , Lee Chun Kiat , Yan Benedict , Loh Jerold , Lim Zhen Yu , Ngiam Nicholas , Chee Jeremy , Gan Soo Wah , Saraf Anmol , Eason Chow Wai Tung , Goh Han Lee , Siow Chor Hiang , Lian Derrick WQ , Loh Woei Shyang , Loh Kwok Seng , Chow Vincent TK , Wang De Yun , Fuh Jerry YH , Yen Ching-Chiuan , Wong John EL , Allen David M
Published: June 2020

We describe the development and validation of a novel 3D-printed nasopharyngeal swab for the identification of SARS-CoV-2. We subjected the novel swab to mechanical and fluid absorption testing ex-vivo, and confirmed its ability to retain and release murine coronavirus and SARS-CoV-2. Compared to the Copan FLOQSwab, the novel swab displayed excellent correlation of RT-PCR cycle threshold values on paired clinical testing in COVID-19 patients, at r = 0.918 and 0.943 for the SARS-CoV-2 ORF1/a and sarbecovirus E-gene respectively. Overall positive and negative percent agreement was 90.6% and 100% respectively on a dual-assay RT-PCR platform, with discordant samples observed only at high cycle thresholds. When carefully designed and tested, 3D-printed swabs are a viable alternative to traditional swabs and will help mitigate strained resources in the escalating COVID-19 pandemic.
Epidemiological description and analysis of RdRp, E and N genes dynamic by RT-PCR of SARS-CoV-2 in Moroccan population: Experience of the National Reference Laboratory (LNR)-UM6SS
Authors: Benrahma Houda , Idrissa Diawara , Imane Smyej , Jalila Rahoui , Nida Meskaouni , Rachid Benmessaoud , Khadija Arouro , Khadija Jaras , Zahra Moujid Fatima , Zahra Adam , Salma Nahir , Zineb Aouzal , Hajar Elguezzar , Leila Jeddane , Fadoua Ousti , Jalila EL Bakkouri , Chakib Nejjari
Published: June 2020

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a new infectious disease that first emerged in Hubei province, China, in December 2019. On 2 March 2020, the Moroccan Ministry of Health confirmed the first COVID-19 case in Morocco. The new virus SARS-CoV-2 was identified in the sample of a Moroccan expatriate residing in Italy. Without a therapeutic vaccine or specific antiviral drugs, early detection and isolation become essential against novel Coronavirus.

This study aims to analyze the epidemiological profile of the SARS-CoV-2 in Moroccan cases and to investigate the dynamic of RdRp, N, and E genes in patients from diagnosis until the recovery.

Among 859 COVID-19 RT-PCR tests realized for 376 patients, 187 cases had positive results COVID-19. 4% were positive with the 3 genes RdRp, N, and E, 40 % with N and E genes, 3% with RdRp and N genes, 31% with only the RdRp gene and 22% cases are positives with N gene. The analysis of the Covid-19 genes (RdRp, N, and E) dynamic reveal that more than 6% stay positive with detection of the N and E gene, and 14% with the N gene after 12 days of treatment.

The median period from positive to the first negative Covid-19 RT-PCR tests was 6.8±2.24 days for 44% cases, 14.31± 2.4 days for 30%, and 22.67 ± 1.21 days for 4%.

This a first description of the Moroccan COVID-19 cases and the analysis of the dynamic of the RdRp, N, and E genes. The analysis of our population can help to improve in the care of patients.
Cell lines of the same anatomic site and histologic type show large variability in radiosensitivity and relative biological effectiveness to protons and carbon ions
Authors: Flint David B. , Bright Scott J. , McFadden Conor H. , Konishi Teruaki , Ohsawa Daisuke , Turner Broderick , Lin Steven H. , Grosshans David R. , Shaitelman Simona F. , Chiu Hua-Sheng , Sumazin Pavel , Sawakuchi Gabriel O.
Published: June 2020

Purpose

To show that radiation response across cancer cell lines of the same anatomic site and histologic type varies remarkably for protons and carbon (C) ions.

Materials and Methods

We measured and obtained from the literature clonogenic survival of human cancer cell lines of the lung (n=18), brain (n=10) and pancreas (n=10) exposed to photons, protons, and C-ions to assess their variability in response. We also treated cancer cell lines with DNA repair inhibitors prior to irradiation to assess how DNA repair capacity affects their variability in response. We quantified the variability in response by calculating the relative range (range/mean) and the coefficient of variation (COV) of the dose at 10% survival fraction (D10%) and relative biological effectiveness (RBE10%).

Results

The relative range of D10%for lung cancer cell lines varied from 55-92% for photons, protons, and C-ions, with the relative range in RBE varying from 16-45% for protons and C-ions. For brain and pancreatic cancer cell lines, the relative range of D10%varied from 95-112%, and 39-75%, respectively, with the relative range in RBE varying from 27-33% and 25-50%, respectively. However, the COVs in D10%were approximately equal across radiation qualities, varying from 0.24±0.07–0.35±0.10, 0.35±0.09–0.69±0.62 and 0.13±0.03– 0.21±0.04 for lung, brain and pancreatic cancer cell lines, respectively. Greater relative ranges in D10%were observed in the cell lines with inhibited DNA repair, varying from 108%-157% for photons, protons, and C-ions, with relative ranges in RBE varying from 29-67%. The COVs in the D10%were also greater for the cell lines treated with inhibitors of DNA repair, varying from 0.34±0.09–0.41±0.06.

Conclusion

Cell lines of the same anatomic site and histologic type have a remarkable variability in response, not only to photons but also to protons and C-ions. We attributed this variability to differences in DNA repair capacity.

Category

Biological Physics and Response Prediction
Repeatability and reproducibility of thewziHigh Resolution Melting-based clustering analysis forKlebsiella pneumoniaetyping
Authors: Pasala Ajay Ratan , Perini Matteo , Piazza Aurora , Panelli Simona , Di Carlo Domenico , Loretelli Cristian , Cafiso Alessandra , Inglese Sonia , Zuccotti Gian Vincenzo , Comandatore Francesco
Published: June 2020

Aims

High Resolution Melting (HRM) is a fast closed-tube method for nucleotide variant scanning applicable for bacterial species identification or molecular typing. Recently a novel HRM-based method forKlebsiella pneumoniaetyping has been proposed: it consists of an HRM protocol designed on the capsularwzigene and an HRM-based algorithm of strains clustering. In this study, we evaluated the repeatability and reproducibility of this method.

Methods and Results

We performed HRM typing of a set ofK. pneumoniaestrains, on three different instruments and by two different operators. The results showed that operators do not affect measured melting temperatures while different instruments can. Despite this, we found that strains clustering analysis remains perfectly consistent performing the analysis using the MeltingPlot tool separately on the data from the three instruments.

Conclusions

The HRM protocol under study was highly repeatable and thus reliable for large studies, even when several operators are involved.

Significance and Impact of the Study

Our results show that thewzi-HRM protocol forK. pneumoniaetyping is suitable for multicenter studies, even if different instruments are used.
Computationally efficient whole genome regression for quantitative and binary traits
Authors: Mbatchou Joelle , Barnard Leland , Backman Joshua , Marcketta Anthony , Kosmicki Jack A. , Ziyatdinov Andrey , Benner Christian , O’Dushlaine Colm , Barber Mathew , Boutkov Boris , Habegger Lukas , Ferreira Manuel , Baras Aris , Reid Jeffrey , Abecasis Gonçalo , Maxwell Evan , Marchini Jonathan
Published: June 2020

Genome-wide association analysis of cohorts with thousands of phenotypes is computationally expensive, particularly when accounting for sample relatedness or population structure. Here we present a novel machine learning method called REGENIE for fitting a whole genome regression model that is orders of magnitude faster than alternatives, while maintaining statistical efficiency. The method naturally accommodates parallel analysis of multiple phenotypes, and only requires local segments of the genotype matrix to be loaded in memory, in contrast to existing alternatives which must load genomewide matrices into memory. This results in substantial savings in compute time and memory usage. The method is applicable to both quantitative and binary phenotypes, including rare variant analysis of binary traits with unbalanced case-control ratios where we introduce a fast, approximate Firth logistic regression test. The method is ideally suited to take advantage of distributed computing frameworks. We demonstrate the accuracy and computational benefits of this approach compared to several existing methods using quantitative and binary traits from the UK Biobank dataset with up to 407,746 individuals.
The enzymatic activity of the nsp14 exoribonuclease is critical for replication of Middle East respiratory syndrome-coronavirus
Authors: Ogando Natacha S. , Zevenhoven-Dobbe Jessika C. , Posthuma Clara C. , Snijder Eric J.
Published: June 2020

Abstract

Coronaviruses (CoVs) stand out for their large RNA genome and complex RNA-synthesizing machinery comprising 16 nonstructural proteins (nsps). The bifunctional nsp14 contains an N-terminal 3’-to-5’ exoribonuclease (ExoN) and a C-terminal N7-methyltransferase (N7-MTase) domain. While the latter presumably operates during viral mRNA capping, ExoN is thought to mediate proofreading during genome replication. In line with such a role, ExoN-knockout mutants of mouse hepatitis virus (MHV) and severe acute respiratory syndrome coronavirus (SARS-CoV) were previously found to have a crippled but viable hypermutation phenotype. Remarkably, using an identical reverse genetics approach, an extensive mutagenesis study revealed the corresponding ExoN-knockout mutants of another betacoronavirus, Middle East respiratory syndrome coronavirus (MERS-CoV), to be non-viable. This is in agreement with observations previously made for alpha- and gammacoronaviruses. Only a single MERS-CoV ExoN active site mutant could be recovered, likely because the introduced D191E substitution is highly conservative in nature. For 11 other MERS-CoV ExoN active site mutants, not a trace of RNA synthesis could be detected, unless – in some cases – reversion had first occurred. Subsequently, we expressed and purified recombinant MERS-CoV nsp14 and establishedin vitroassays for both its ExoN and N7-MTase activities. All ExoN knockout mutations that were lethal when tested via reverse genetics were found to severely decrease ExoN activity, while not affecting N7-MTase activity. Our study thus reveals an additional function for MERS-CoV nsp14 ExoN, which apparently is critical for primary viral RNA synthesis, thus differentiating it from the proofreading activity thought to boost long-term replication fidelity in MHV and SARS-CoV.

Importance

The bifunctional nsp14 subunit of the coronavirus replicase contains 3’-to-5’ exoribonuclease (ExoN) and N7-methyltransferase (N7-MTase) domains. For the betacoronaviruses MHV and SARS-CoV, the ExoN domain was reported to promote the fidelity of genome replication, presumably by mediating some form of proofreading. For these viruses, ExoN knockout mutants are alive while displaying an increased mutation frequency. Strikingly, we now established that the equivalent knockout mutants of MERS-CoV ExoN are non-viable and completely deficient in RNA synthesis, thus revealing an additional and more critical function of ExoN in coronavirus replication. Both enzymatic activities of (recombinant) MERS-CoV nsp14 were evaluated using newly developedin vitroassays that can be used to characterize these key replicative enzymes in more detail and explore their potential as target for antiviral drug development.
Clinical practice guidelines and recommendations in the context of the COVID-19 pandemic: systematic review and critical appraisal
Authors: Stamm Tanja A , Andrews Margaret R , Mosor Erika , Ritschl Valentin , Li Linda C , Ma Jasmin K , Arias Adalberto Campo , Baker Sarah , Burton Nicola W , Eghbali Mohammad , Fernandez Natalia , Ferreira Ricardo , Gäbler Gabriele , Makri Souzi , Mintz Sandra , Moe Rikke , Morasso Elizabeth , Murphy Susan L , Ntuli Simiso , Omara Maisa , Simancas Pallares Miguel Angel , Horonieff Jen , Gartlehner Gerald
Published: June 2020

Background

The number of published clinical practice guidelines and recommendations related to SARS-CoV-2 infections causing COVID-19 has rapidly increased. However, insufficient consideration of appropriate methodologies in the guideline development could lead to misleading information, uncertainty among professionals, and potentially harmful actions for patients.

Purpose

Rapid systematic review of clinical practice guidelines and recommendations in the context of COVID-19 to explore if basic methodological standards of guideline development have been met.

Data sources

MEDLINE [PubMed], CINAHL [Ebsco], Trip and manual search; from Feb 1st 2020 until April 27th 2020.

Study selection

All types of healthcare workers providing any kind of healthcare to any patient population in any setting.

Data extraction

At least two reviewers independently extracted guideline characteristics, conducted critical appraisal according to The Appraisal of Guidelines for Research and Evaluation Instrument (AGREE II) and classified the guidelines using the Association of the Scientific Medical Societies (AWMF) Guidance Manual and Rules for Guideline Development. We plan six-month updates (living review).

Data synthesis

There were 1342 titles screened and 188 guidelines included. The highest average AGREE II domain score was 89% for scope and purpose, the lowest for rigor of development (25%). Only eight guidelines (4%) were based on a systematic literature search and a structured consensus process by representative experts (classified as the highest methodological quality, S3 according to AWMF). Patients were only included in the development of one guideline. A process for regular updates was described in 27 guidelines (14%).

Limitations

Methodological focus only.

Conclusions

Despite clear scope, most publications fell short of basic methodological standards of guideline development. Future research should monitor the evolving methodological quality of the guidelines and their updates over time.

Registration/Publication

The protocol was published at www.researchgate.net, DOI: 10.13140/RG.2.2.21293.51689. Preliminary results are publicly available on medRxiv.
Observational Study of Metformin and Risk of Mortality in Patients Hospitalized with Covid-19
Authors: Bramante Carolyn T. , Ingraham Nicholas E. , Murray Thomas A. , Marmor Schelomo , Hovertsen Shane , Gronski Jessica , McNeil Chace , Feng Ruoying , Guzman Gabriel , Abdelwahab Nermine , King Samantha , Meehan Thomas , Pendleton Kathryn M. , Benson Bradley , Vojta Deneen , Tignanelli Christopher J.
Published: June 2020

Importance

Type 2 diabetes (T2DM) and obesity are significant risk factors for mortality in Covid19. Metformin has sex specific immunomodulatory effects which may elucidate treatment mechanisms in COVID-19.Objective:We sought to identify whether metformin reduced mortality from Covid19 and if sex specific interactions exist.

Design

Retrospective review of de-identified claims from UnitedHealth Group’s Clinical Discovery Database. Unadjusted and multivariate models were conducted to assess risk of mortality based on metformin and tumor necrosis factor alpha (TNFα) inhibitors as home medications in individuals with T2DM and obesity, controlling for comorbidities, medications, demographics, and state. Heterogeneity of effect was assessed by sex.

Setting

The database includes all 50 states in the United States.Participants:Persons with at least 6 months of continuous coverage from UnitedHealth Group in 2019 who were hospitalized with Covid-19. Persons in the metformin group had > 90 days of metformin claims in the 12 months before hospitalization.

Results

6,256 persons were included; 52.8% female; mean age 75 years. Metformin was associated with decreased mortality in women by logistic regression, OR 0.792 (0.640, 0.979); mixed effects OR 0.780 (0.631, 0.965); Cox proportional-hazards: HR 0.785 (0.650, 0.951); and propensity matching, OR of 0.759 (0.601, 0.960). There was no significant reduction in mortality among men. TNFα inhibitors were associated with decreased mortality, by propensity matching in a limited model, OR 0.19 (0.0378, 0.983).

Conclusions

Metformin was significantly associated with reduced mortality in women with obesity or T2DM in observational analyses of claims data from individuals hospitalized with Covid-19. This sex-specific finding is consistent with metformin’s reduction of TNFα in females over males, and suggests that metformin conveys protection in Covid-19 through TNFα effects. Prospective studies are needed to understand mechanism and causality.

Key Points

Question

Metformin has many anti-inflammatory effects, including sex-specific effects on TNFα. Is metformin protective from the Sars-CoV-2 virus, and does the effect differ by sex?

Findings

Metformin was associated with reduced mortality in women who were hospitalized with Covid-19, but not in men who were hospitalized with Covid-19.

Meaning

The sex-dependent survival by metformin use points towards TNFα reduction as a key mechanism for protection from Covid-19.
Inhaled corticosteroid use and risk COVID-19 related death among 966,461 patients with COPD or asthma: an OpenSAFELY analysis
Authors:   The OpenSAFELY Collaborative, Schultze Anna , Walker Alex J , MacKenna Brian , Morton Caroline E , Bhaskaran Krishnan , Brown Jeremy P , Rentsch Christopher T , Williamson Elizabeth , Drysdale Henry , Croker Richard , Bacon Seb , Hulme William , Bates Chris , Curtis Helen J , Mehrkar Amir , Evans David , Inglesby Peter , Cockburn Jonathan , McDonald Helen I , Tomlinson Laurie , Mathur Rohini , Wing Kevin , Wong Angel YS , Forbes Harriet , Parry John , Hester Frank , Harper Sam , Evans Stephen JW , Quint Jennifer , Smeeth Liam , Douglas Ian J , Goldacre Ben
Published: June 2020

Background

Early descriptions of the coronavirus outbreak showed a lower prevalence of asthma and COPD than was expected for people diagnosed with COVID-19, leading to speculation that inhaled corticosteroids (ICS) may protect against infection with SARS-CoV-2, and development of serious sequelae. We evaluated the association between ICS and COVID-19 related death using linked electronic health records in the UK.

Methods

We conducted cohort studies on two groups of people (COPD and asthma) using the OpenSAFELY platform to analyse data from primary care practices linked to national death registrations. People receiving an ICS were compared to those receiving alternative respiratory medications. Our primary outcome was COVID-19 related death.

Findings

We identified 148,588 people with COPD and 817,973 people with asthma receiving relevant respiratory medications in the four months prior to 01 March 2020. People with COPD receiving ICS were at a greater risk of COVID-19 related death compared to those receiving a long-acting beta agonist (LABA) and a long-acting muscarinic antagonist (LAMA) (adjusted HR = 1.38, 95% CI = 1.08 – 1.75). People with asthma receiving high dose ICS were at an increased risk of death compared to those receiving a short-acting beta agonist (SABA) only (adjusted HR = 1.52, 95%CI = 1.08 – 2.14); the adjusted HR for those receiving low-medium dose ICS was 1.10 (95% CI = 0.82 – 1.49). Quantitative bias analyses indicated that an unmeasured confounder of only moderate strength of association with exposure and outcome could explain the observed associations in both populations.

Interpretation

These results do not support a major role of ICS in protecting against COVID-19 related deaths. Observed increased risks of COVID-19 related death among people with COPD and asthma receiving ICS can be plausibly explained by unmeasured confounding due to disease severity.

Funding

This work was supported by the Medical Research Council MR/V015737/1.
COVID-19 pandemic and health worker stress: The mediating effect of emotional regulation
Authors: García-Batista Zoilo Emilio , Guerra-Peña Kiero , Kandany Vahid Nouri , Marte Maria Isabel , Garrido Luis Eduardo , Cantisano-Guzmán Luisa Marilia , Moretti Luciana , Medrano Leonardo A.
Published: June 2020

Background/Introduction

Psychological and physical well-being of health personnel has been significantly affected by COVID-19. Work overload and continuous exposure to positive COVID-19 cases have caused them fatigue, stress, anxiety, insomnia and other detriments. This research aims: 1) to analyze whether the use of cognitive reevaluation and emotional suppression strategies decreases and increases, respectively, stress levels of health personnel; 2) to quantify the impact of contact with patients with COVID-19 on stress’s level of medical staff.

Method

Emotion regulation strategies and stress level were evaluated in 155 Dominican physicians by means of psychological tests with adequate levels of reliability. In addition, a questionnaire created by the researchers quantified the impact that contact with those infected had on their stress levels.

Results

Contact with patients with COVID-19 predicts increased use of emotion suppression strategies, although is not associated with the use of cognitive reevaluation. These findings lead to an even greater increase in stress on health care providers.

Conclusions

Contextual contingencies demand immediate responses and may not allow health personnel to use cognitive re-evaluation strategies, leaning more towards emotion suppression. However, findings regarding high levels of stress require the implementation of intervention programs focused on the promotion of more functional emotion regulation strategies. Such programs may reduce current stress and prevent post-traumatic symptoms.