bluuebunny/crossref_metadata_2025 huggingface dataset:
Determinants of HIV-1 late presentation in a cohort of Portuguese HIV-1 patients
Authors: Cláudia Miranda Ana , Miranda Mafalda , Pingarilho Marta , Pimentel Victor , Torres João , Peres Susana , Alberto Teresa Baptista , Gomes Perpetua , Abecasis Ana , Mansinho Kamal
Published: June 2020

Background

Undiagnosed HIV-1 patients still account for 25% of worldwide HIV patients. Studying late presenters for HIV care may help to identify characteristics of such patients.

Objective

The present study aims to identify factors associated with late presentation (LP) and late presentation with advanced disease (LPAD) based on a population of patients followed in a Portuguese hospital between 1984 and 2017.

Methods

Sociodemographic and clinical data from infected patients with HIV-1 aged 18 years and older, followed in Egas Moniz Hospital, in Portugal were collected.

Results

Of the 907 patients included in this study, 68.7% were males and the median age was 37 years (IQR 30-47). 459 patients (50.6%) were LP and, of these, 284 patients (61.9%) were LPAD. The LP population mostly originated from Portugal and Sub-Saharan Africa (64.4% and 28.8%; p=0.004) and the HIV exposure category mainly heterosexuals and MSM (57.0% and 24.9%; p<0.001). The stage of disease and viral load at diagnosis were significantly associated with both LP and LPAD (p<0.001). Factors associated with LP in the logistic regression included age at diagnosis lower than 30y (aOR 0.34; 0.17-0.68; p=0.002) and origin from Sub-Saharan Africa (aOR 2.24; 1.44-3.50; p<0.001).

Conclusion

Late presentation is a major obstacle to halt the HIV epidemic. In this population, the majority of newly diagnosed HIV-infected individuals were late presenters. Our results characterize vulnerable populations that should be frequently tested for HIV.
Hospital based autonomous pre-clinical screening of COVID-19: An emergency triage using a vital signs recording system, Paris-Ile de France region
Authors: Brizio Albert , Faure Valérie , Baudino Franck , Wilmet Arnaud , Gonzalez Jean-Paul
Published: June 2020

The COVID-19 pandemic, has had a dramatic toll worldwide on the populations but also has been essentially supported by the existing public health system, particularly hospital-based emergency wards and intensive care units.

In France, the first cases were identified on the 24th of January 2020. The first epidemic sprout emerged in the Eastern part of the country and spread in two weeks towards the center to the Paris-region where it peaked on the 14th of April 2020. In Paris and the region around it, the intensity of the epidemic has increased significantly to have a strong impact on all public and private hospital systems in a few weeks.

During France’s 2020 COVID-19 epidemic, a private hospital went into a major organizational change of its Emergency Department which mainly included the use of a Telemedicine Booth for vitals automatic recording during triage procedures.

The present study describes the organizational scheme adopted by the hospital and discusses the data of 1,844 patients that attended the facility over a month. While among them, 766 patients were engaged in a automated triage process supported by a Telemedicine Booth. Patients’ clinical characteristics are comparable to those found in international literature during the COVID-19 pandemic.

The use of the Telemedicine Booth as a screening process facilitated patients’ flow. It usefully participated in the patient rapid orientation, relieving the hospital emergency department, actively contributes in a safe and secure environment highly trusted by the hospital staff and health workers. To our nowledge, the Telemedicine Booth use as a screening process during an epidemic constitutes the first contribution to such an innovative approach.
Asynchronicity of endemic and emerging mosquito-borne disease outbreaks in the Dominican Republic
Authors: Petrone Mary E. , Earnest Rebecca , Lourenço José , Kraemer Moritz U.G. , Paulino-Ramirez Robert , Grubaugh Nathan D. , Tapia Leandro
Published: June 2020

Mosquito-borne viruses pose a perpetual public health threat to countries and territories in the Carribean due to the region’s tropical climate and seasonal reception of international tourists. Outbreaks of the emerging viruses chikungunya and Zika in 2014 and 2016, respectively, demonstrated the rapidity with which these viruses can spread between islands. At the same time, the number of reported dengue fever cases, caused by the endemic dengue virus, has steadily climbed over the past decade, and a large dengue outbreak that began sweeping through this region in 2019 continues in 2020. Sustainable disease and mosquito control measures are urgently needed to quell virus transmission in the long term and prevent future outbreaks from occurring. To improve upon current surveillance methods, we analyzed temporal and spatial patterns of chikungunya, Zika, and dengue outbreaks reported in the Dominican Republic between 2012 and 2018. The viruses that caused these outbreaks are transmitted by Aedes mosquitoes, which are sensitive to seasonal climatological variability. In this study, we evaluated whether climate and the spatio-temporal dynamics of past dengue outbreaks could inform when and where future emerging disease outbreaks might occur. We found that the temporal and spatial distribution of emerging disease outbreaks did not conform to those of seasonal dengue outbreaks. Rather, the former occurred when climatological conditions were suboptimal for Aedes activity. Provincial dengue attack rates did not correspond to those of emerging diseases. Our study also provides evidence for under-reporting of dengue cases, especially following the 2016 Zika outbreak. We advocate for the implementation of a sustainable and long-term surveillance system to monitor the spread of known mosquito-borne viruses and to identify emerging threats before they cause outbreaks. Specifically, we recommend the use of febrile illness incidence, ca se fatality rates, and serosurveys during inter-outbreak periods to better understand rates of transmission and asymptomatic infection.
Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: results of a Bayesian evidence synthesis model
Authors: Chitwood Melanie H. , Russi Marcus , Gunasekera Kenneth , Havumaki Joshua , Klaassen Fayette , Pitzer Virginia E. , Salomon Joshua A. , Swartwood Nicole A. , Warren Joshua L. , Weinberger Daniel M. , Cohen Ted , Menzies Nicolas A.
Published: June 2020

Reported COVID-19 cases and deaths provide a delayed and incomplete picture of SARS-CoV-2 infections in the United States (US). Accurate estimates of both the timing and magnitude of infections are needed to characterize viral transmission dynamics and better understand COVID- 19 disease burden. We estimated time trends in SARS-CoV-2 transmission and other COVID-19 outcomes for every county in the US, from the first reported COVID-19 case in January 13, 2020 through January 1, 2021. To do so we employed a Bayesian modeling approach that explicitly accounts for reporting delays and variation in case ascertainment, and generates daily estimates of incident SARS-CoV-2 infections on the basis of reported COVID-19 cases and deaths. The model is freely available as thecovidestimR package. Nationally, we estimated there had been 49 million symptomatic COVID-19 cases and 400,718 COVID-19 deaths by the end of 2020, and that 27% of the US population had been infected. The results also demonstrate wide county-level variability in the timing and magnitude of incidence, with local epidemiological trends differing substantially from state or regional averages, leading to large differences in the estimated proportion of the population infected by the end of 2020. Our estimates of true COVID-19 related deaths are consistent with independent estimates of excess mortality, and our estimated trends in cumulative incidence of SARS-CoV-2 infection are consistent with trends in seroprevalence estimates from available antibody testing studies. Reconstructing the underlying incidence of SARS-CoV-2 infections across US counties allows for a more granular understanding of disease trends and the potential impact of epidemiological drivers.
Prolonged low-dose methylprednisolone in patients with severe COVID-19 pneumonia
Authors: Salton Francesco , Confalonieri Paola , Santus Pierachille , Harari Sergio , Scala Raffaele , Lanini Simone , Vertui Valentina , Oggionni Tiberio , Caminati Antonella , Patruno Vincenzo , Tamburrini Mario , Scartabellati Alessandro , Parati Mara , Villani Massimiliano , Radovanovic Dejan , Tomassetti Sara , Ravaglia Claudia , Poletti Venerino , Vianello Andrea , Gaccione Anna Talia , Guidelli Luca , Raccanelli Rita , Lucernoni Paolo , Lacedonia Donato , Foschino Barbaro Maria Pia , Centanni Stefano , Mondoni Michele , Davì Matteo , Fantin Alberto , Cao Xueyuan , Torelli Lucio , Zucchetto Antonella , Montico Marcella , Casarin Annalisa , Romagnoli Micaela , Gasparini Stefano , Bonifazi Martina , D’Agaro Pierlanfranco , Marcello Alessandro , Licastro Danilo , Ruaro Barbara , Volpe Maria Concetta , Umberger Reba , Meduri Umberto , Confalonieri Marco
Published: June 2020

Background

In hospitalized patients with COVID-19 pneumonia, progression to acute respiratory failure requiring invasive mechanical ventilation (MV) is associated with significant morbidity and mortality. Severe dysregulated systemic inflammation is the putative mechanism. We hypothesize that early prolonged methylprednisolone (MP) treatment could accelerate disease resolution, decreasing the need for ICU and mortality.

Methods

We conducted a multicenter, observational study to explore the association between exposure to prolonged, low-dose, MP treatment and need for ICU referral, intubation or death within 28 days (composite primary endpoint) in patients with severe COVID-19 pneumonia admitted to Italian respiratory high-dependency units. Secondary outcomes were invasive MV-free days and changes in C-reactive protein (CRP) levels.

Results

Findings are reported as MP (n=83) vs. control (n=90). The composite primary endpoint was met by 19 vs. 40 [adjusted hazard ratio (HR) 0.41; 95% confidence interval (CI): 0.24-0.72]. Transfer to ICU and need for invasive MV was necessary in 15 vs. 27 (p=0.07) and 14 vs. 26 (p=0.10), respectively. By day 28, the MP group had fewer deaths (6 vs. 21, adjusted HR=0.29; 95% CI: 0.12-0.73) and more days off invasive MV (24.0 ± 9.0 vs. 17.5 ± 12.8; p=0.001). Study treatment was associated with rapid improvement in PaO2:FiO2 and CRP levels. The complication rate was similar for the two groups (p=0.84).

Conclusion

In patients with severe COVID-19 pneumonia, early administration of prolonged MP treatment was associated with a significantly lower hazard of death (71%) and decreased ventilator dependence. Randomized controlled studies are needed to confirm these findings.

Registration

ClinicalTrials.gov. Identifier: NCT04323592
Molecular epidemiology of Blastocystis in urban and periurban human populations in Arequipa, Peru
Authors: Ascuña-Durand Kasandra , Salazar-Sánchez Renzo S. , Cartillo-Neyra Ricardo , Ballón-Echegaray Jorge
Published: June 2020

Blastocystis is one of the most common parasites found in the gut of humans and other hosts. It has a wide genetic diversity distributed around the world, predominating subtypes 1, 2 and 3 in South America countries. Nonspecific and inconsistent symptoms associated with this parasite made it controversial. The aim of this study was to estimate the prevalence of subtypes and determinate the epidemiological conditions associated with them. A total of 116 Blastocystis positive stool samples were processed by conventional PCR with Blastocystis-specific primers for subtypes 1 to 3. We identified subtype 1 (10.3%), subtype 2 (7.6%), subtype 3 (25.0%) and mixed infections (8.6%). We did not identify these Blastocystis subtypes in 48.7% of stool samples, assuming the presence of other subtypes in the zone. Any association was found between gastrointestinal symptoms and single subtype infections neither with mixed subtypes coinfections. However, our results suggest an association of Blastocystis subtype 2 and Irritable Bowel Syndrome (IBS, p=0.039). Besides, there was not an association between Blastocystis subtypes 1, 2 and 3 nor-mixed infections with epidemiological variables such as gender, age, presence of animals or vectors, places of food consumption, type of water consumption and water supply.
Combining clinical and polygenic risk improves stroke prediction among individuals with atrial fibrillation
Authors: O’Sullivan Jack W. , Shcherbina Anna , Justesen Johanne M , Turakhia Mintu , Perez Marco , Wand Hannah , Tcheandjieu Catherine , Clarke Shoa L. , Harrington Robert A. , Rivas Manuel A. , Ashley Euan A
Published: June 2020

Background

Atrial fibrillation (AF) is associated with a five-fold increased risk of ischemic stroke. A portion of this risk is heritable, however current risk stratification tools (CHA2DS2-VASc) don’t include family history or genetic risk. We hypothesized that we could improve ischemic stroke prediction in patients with AF by incorporating polygenic risk scores (PRS).

Objectives

To construct and test a PRS to predict ischemic stroke in patients with AF, both independently and integrated with clinical risk factors.

Methods

Using data from the largest available GWAS in Europeans, we combined over half a million genetic variants to construct a PRS to predict ischemic stroke in patients with AF. We externally validated this PRS in independent data from the UK Biobank (UK Biobank), both independently and integrated with clinical risk factors.

Results

The integrated PRS and clinical risk factors risk tool had the greatest predictive ability. Compared with the currently recommended risk tool (CHA2DS2-VASc), the integrated tool significantly improved net reclassification (NRI: 2.3% (95%CI: 1.3% to 3.0%)), and fit (χ2 P =0.002). Using this improved tool, >115,000 people with AF would have improved risk classification in the US. Independently, PRS was a significant predictor of ischemic stroke in patients with AF prospectively (Hazard Ratio: 1.13 per 1 SD (95%CI: 1.06 to 1.23))). Lastly, polygenic risk scores were uncorrelated with clinical risk factors (Pearson’s correlation coefficient: −0.018).

Conclusions

In patients with AF, there appears to be a significant association between PRS and risk of ischemic stroke. The greatest predictive ability was found with the integration of PRS and clinical risk factors, however the prediction of stroke remains challenging.
Drainage of inflammatory macromolecules from brain to periphery targets the liver for macrophage infiltration
Authors: Yang Linlin , Jiménez Jessica A. , Earley Alison M. , Hamlin Victoria , Kwon Victoria , Dixon Cameron T. , Shiau Celia E.
Published: June 2020

Many brain pathologies are associated with liver damage, but a direct link has long remained elusive. Here, we establish a new paradigm for interrogating brain-periphery interactions by leveraging zebrafish for its unparalleled access to the intact whole animal forin vivoanalysis in real time after triggering focal brain inflammation. We reveal that drainage of inflammatory macromolecules from the brain led to a strikingly robust peripheral infiltration of macrophages into the liver independent of Kupffer cells. We further demonstrate that this macrophage recruitment requires signaling from the cytokine IL-34, Toll-like receptor adaptor protein MyD88, and neutrophils. These results highlight the ability for circulation of brain-derived substances to serve as a rapid mode of communication from brain to the liver. Understanding how the brain engages the periphery at times of danger may offer new perspectives for detecting and treating brain pathologies.
SARS-CoV-2-specific antibody detection for sero-epidemiology: a multiplex analysis approach accounting for accurate seroprevalence
Authors: Hartog Gerco den , Schepp Rutger M. , Kuijer Marjan , GeurtsvanKessel Corine , van Beek Josine , Rots Nynke , Koopmans Marion P.G. , van der Klis Fiona R.M. , van Binnendijk Robert S.
Published: June 2020

Background

The COVID-19 pandemic demands detailed understanding of the kinetics of antibody production induced by infection with SARS-CoV-2. We aimed to develop a high throughput multiplex assay to detect antibodies to SARS-CoV-2 to assess immunity to the virus in the general population.

Methods

Spike protein subunits S1 and RBD, and Nucleoprotein were coupled to distinct microspheres. Sera collected before the emergence of SARS-CoV-2 (N=224), and of non-SARS-CoV-2 influenza-like illness (N=184), and laboratory-confirmed cases of SARS-CoV-2 infection (N=115) with various severity of COVID-19 were tested for SARS-CoV-2-specific concentrations of IgG.

Results

Our assay discriminated SARS-CoV-2-induced antibodies and those induced by other viruses. The assay obtained a specificity between 95.1 and 99.0% with a sensitivity ranging from 83.6-95.7%. By merging the test results for all 3 antigens a specificity of 100% was achieved with a sensitivity of at least 90%. Hospitalized COVID-19 patients developed higher IgG concentrations and the rate of IgG production increased faster compared to non-hospitalized cases.

Conclusions

The bead-based serological assay for quantitation of SARS-CoV-2-specific antibodies proved to be robust and can be conducted in many laboratories. Finally, we demonstrated that testing of antibodies against different antigens increases sensitivity and specificity compared to single antigen-specific IgG determination.
Modeling COVID19 mortality in the US: Community context and mobility matter
Authors: McGough Sarah F. , Gan Ryan W. , Tibshirani Robert , Meyer Anne-Marie
Published: June 2020

The United States has become an epicenter for the coronavirus disease 2019 (COVID-19) pandemic. However, communities have been unequally affected and evidence is growing that social determinants of health may be exacerbating the pandemic. Furthermore, the impact and timing of social distancing at the community level have yet to be fully explored. We investigated the relative associations between COVID-19 mortality and social distancing, sociodemographic makeup, economic vulnerabilities, and comorbidities in 24 counties surrounding 7 major metropolitan areas in the US using a flexible and robust time series modeling approach. We found that counties with poorer health and less wealth were associated with higher daily mortality rates compared to counties with fewer economic vulnerabilities and fewer pre-existing health conditions. Declines in mobility were associated with up to 15% lower mortality rates relative to pre-social distancing levels of mobility, but effects were lagged between 25-30 days. While we cannot estimate causal impact, this study provides insight into the association of social distancing on community mortality while accounting for key community factors. For full transparency and reproducibility, we provide all data and code used in this study.

One-sentence summary

County-level disparities in COVID19 mortality highlight inequalities in socioeconomic and community factors and delayed effects of social distancing.
THE USE OF DENATURING SOLUTION AS COLLECTION AND TRANSPORT MEDIA TO IMPROVE SARS-COV-2 RNA DETECTION AND REDUCE INFECTION OF LABORATORY PERSONNEL
Authors: de Carvalho Alex Fiorini , Gonçalves Andreza Parreiras , de Souza Silva Thaís Bárbara , Sato Hugo Itaru , Vuitika Larissa , Bagno Flavia Fonseca , Sérgio Sarah Aparecida Rodrigues , Figueiredo Maria Marta , Rocha Raissa Prado , Fernandes Ana Paula Salles Moura , Alves Pedro Augusto , Teixeira Santuza Maria Ribeiro , da Fonseca Flavio Guimarães
Published: June 2020

Background

Since the emergence of the COVID-19, health officials have struggled to devise strategies to counteract the speed of the pandemic’s spread across the globe. It became imperative to implement accurate diagnostic tests for the detection of SARS-CoV-2 RNA on respiratory samples. In many places, however, besides the limited availability of test reagents, laboratory personnel face the challenge of adapting their working routines to manipulate highly infective clinical samples. Here, we proposed the use of a virus-inactivating solution as part of a sample collection kit to decrease the infectious potential of the collected material without affecting the integrity of RNA samples used in diagnostic tests based on RT-qPCR.

Methods

Nasopharyngeal and oropharyngeal swab samples were collected from SARS-CoV-2-infected patients and from laboratory personnel using a commercially available viral transport solution (VTM) and the denaturing solution (DS) described here. RNA extracted from all samples was tested by RT-qPCR using probes for viral and human genes. Exposure of laboratory personnel to infective viruses was also accessed using ELISA tests.

Findings

The use of the DS did not interfere with the detection of viral genome or the endogenous human mRNA, since similar results were obtained from samples collected with VTM or DS. In addition, all tests of laboratory personnel for the presence of viral RNA and IgG antibodies against SARS-CoV-2 were negative.

Interpretation

The methodology described here provides a strategy that allow high diagnostic accuracy as well as safe manipulation of clinical samples by those involved with diagnostic procedures.

Funding

CAPES, FAPEMIG, CNPq, MCTIC, FIOCRUZ and the UK Global Challenges Research Fund (GCRF).
Descriptive Epidemiological Assessment of the Relationship between the Global Burden of Influenza from 2017-2019 and COVID-19
Authors: Baral Stefan David , Rucinski Katherine B. , Twahirwa Rwema Jean Olivier , Rao Amrita , Menezes Neia Prata , Diouf Daouda , Kamarulzaman Adeeba , Phaswana-Mafuya Nancy , Mishra Sharmistha
Published: June 2020

Background

SARS-CoV-2 and influenza are lipid-enveloped viruses with differential morbidity and mortality but shared modes of transmission. With a descriptive epidemiological framing, we assessed whether historical patterns of regional influenza burden are reflected in the observed heterogeneity in COVID-19 cases across regions of the world.

Methods

Weekly surveillance data reported in FluNet from January 2017–December 2019 for influenza and World Health Organization for COVID-19 (to May 31, 2020) across the seven World Bank regions were used to assess the total and annual number of influenza and COVID-19 cases per country, within and across all regions, to generate comparative descending ranks from highest to lowest burden of disease.

Results

Across regions, rankings of influenza and COVID-19 were relatively consistent. Europe and Central Asia and North America ranked first and second for COVID-19 and second and first for influenza, respectively. East Asia and the Pacific traditionally ranked higher for influenza with recent increases in COVID-19 consistent with influenza season. Across regions, Sub-Saharan Africa ranked amongst the least affected by both influenza and COVID-19.

Conclusion

Consistency in the regional distribution of the burden of COVID-19 and influenza suggest shared individual, structural, and environmental determinants of transmission. Using a descriptive epidemiological framework to assess shared regional trends for rapidly emerging respiratory pathogens with better studied respiratory infections may provide further insights into the differential impacts of non-pharmacologic interventions and intersections with environmental conditions. Ultimately, forecasting trends and informing interventions for novel respiratory pathogens like COVID-19 should leverage epidemiologic patterns in the relative burden of past respiratory pathogens as prior information.
IL-13 is a driver of COVID-19 severity
Authors: Donlan Alexandra N. , Sutherland Tara E. , Marie Chelsea , Preissner Saskia , Bradley Ben T. , Carpenter Rebecca M. , Sturek Jeffrey M. , Ma Jennie Z. , Moreau G. Brett , Donowitz Jeffrey R. , Buck Gregory A. , Serrano Myrna G. , Burgess Stacey L. , Abhyankar Mayuresh M. , Mura Cameron , Bourne Philip E. , Preissner Robert , Young Mary K. , Lyons Genevieve R. , Loomba Johanna J. , Ratcliffe Sarah J , Poulter Melinda D. , Mathers Amy J. , Day Anthony , Mann Barbara J. , Allen Judith E. , Petri William A.
Published: June 2020

Immune dysregulation is characteristic of the more severe stages of SARS-CoV-2 infection. Understanding the mechanisms by which the immune system contributes to COVID-19 severity may open new avenues to treatment. Here we report that elevated interleukin-13 (IL-13) was associated with the need for mechanical ventilation in two independent patient cohorts. In addition, patients who acquired COVID-19 while prescribed Dupilumab had less severe disease. In SARS-CoV-2 infected mice, IL-13 neutralization reduced death and disease severity without affecting viral load, demonstrating an immunopathogenic role for this cytokine. Following anti-IL-13 treatment in infected mice, in the lung, hyaluronan synthase 1 (Has1) was the most downregulated gene and hyaluronan accumulation was decreased. Blockade of the hyaluronan receptor, CD44, reduced mortality in infected mice, supporting the importance of hyaluronan as a pathogenic mediator, and indicating a new role for IL-13 in lung disease. Understanding the role of IL-13 and hyaluronan has important implications for therapy of COVID-19 and potentially other pulmonary diseases.

L-13 levels are elevated in patients with severe COVID-19. In a mouse model of disease, IL-13 neutralization results in reduced disease and lung hyaluronan deposition. Similarly, blockade of hyaluronan’s receptor, CD44, reduces disease, highlighting a novel mechanism for IL-13-mediated pathology.
SARS-CoV-2 in human milk is inactivated by Holder pasteurization but not cold storage
Authors: Walker Gregory J. , Clifford Vanessa , Bansal Nidhi , Stella Alberto Ospina , Turville Stuart , Stelzer-Braid Sacha , Klein Laura D , Rawlinson William
Published: June 2020

As the COVID-19 pandemic evolves, human milk banks worldwide continue to provide donor human milk to vulnerable infants who lack access to mother’s own milk. Under these circumstances, ensuring the safety of donor human milk is paramount, as the risk of vertical transmission of SARS-CoV-2 is not well understood. Here, we investigate the inactivation of SARS-CoV-2 in human milk by pasteurisation, and the stability of SARS-CoV-2 in human milk under cold storage (freezing or refrigeration). Following heating to 63°C or 56°C for 30 minutes, SARS-CoV-2 replication competent (i.e. live) virus was undetected in both human milk and the control medium. Cold storage of SARS-CoV-2 in human milk (either at 4°C or - 30°C) did not significantly impact infectious viral load over a 48 hour period. Our findings demonstrate that SARS-CoV-2 can be effectively inactivated by Holder pasteurisation, and confirm that existing milk bank processes will effectively mitigate the risk of transmission of SARS-COV-2 to vulnerable infants through pasteurised donor human milk.
Simulation of COVID-19 Incubation Period and the Effect of Probability Distribution Function on Model Training Using MIMANSA
Authors: Patel Abhilasha P. , Welling Arpita A. , Vaidya Vinay G. , Kulkarni Padmaj S.
Published: June 2020

Coronavirus disease 2019 (COVID-19) has infected people all over the world. While scientists are busy finding a vaccine and medicine, it becomes difficult to control the spread and manage patients. Mathematical models help one get a better feel for the challenges in patient management. With this in mind, our team developed a model called Multilevel Integrated Model with a Novel Systems Approach (MIMANSA) Welling et. al (2020). MIMANSA is a multi-parametric model. One of the challenges in the design of MIMANSA was to simulate the incubation period of coronavirus. The incubation period decides when virus-infected patients would show symptoms. The probability distribution function (PDF), when applied to the number of virus-infected cases, gives a good representation of the process of the incubation period. The probability distribution functions can take various forms. In this paper, we explore a variety of PDFs and their impact on parameter estimation in the MIMANSA model. For our experiments, we used Weibull, Gaussian, uniform, and Gamma distribution. To ensure a fair comparison of Weibull, Gaussian, and Gamma distribution, we matched the peak value of the distribution. Our results show that the Weibull distribution with shape 7.7 and scale 7 for 14 days gives a better training model and predictions.
Prognostic factors in spanish COVID-19 patients: A case series from barcelona
Authors: Sisó-Almirall Antoni , Kostov Belchin , Mas-Heredia Minerva , Vilanova-Rotllan Sergi , Sequeira-Aymar Ethel , Sans-Corrales Mireia , Sant-Arderiu Elisenda , Cayuelas-Redondo Laia , Martínez-Pérez Angela , Plana Noemí García , Anguita-Guimet August , Benavent-Àreu Jaume
Published: June 2020

Background

In addition to the lack of COVID-19 diagnostic tests for the whole Spanish population, the current strategy is to identify the disease early to limit contagion in the community.

Aim

To determine clinical factors of a poor prognosis in patients with COVID-19 infection.

Design and Setting

Descriptive, observational, retrospective study in three primary healthcare centres with an assigned population of 100,000.

Method

Examination of the medical records of patients with COVID-19 infections confirmed by polymerase chain reaction.

Results

We included 322 patients (mean age 56.7 years, 50% female, 115 (35.7%) aged ≥ 65 years). The best predictors of ICU admission or death were greater age, male sex (OR=2.99; 95%CI=1.55 to 6.01), fever (OR=2.18; 95%CI=1.06 to 4.80), dyspnoea

(OR=2.22; 95%CI=1.14 to 4.24), low oxygen saturation (OR=2.94; 95%CI=1.34 to 6.42), auscultatory alterations (OR=2.21; 95%CI=1.00 to 5.29), heart disease (OR=4.37; 95%CI=1.68 to 11.13), autoimmune disease (OR=4.03; 95%CI=1.41 to 11.10), diabetes (OR=4.00; 95%CI=1.89 to 8.36), hypertension (OR=3.92; 95%CI=2.07 to 7.53), bilateral pulmonary infiltrates (OR=3.56; 95%CI=1.70 to 7.96), elevated lactate-dehydrogenase (OR=3.02; 95%CI=1.30 to 7.68), elevated C-reactive protein (OR=2.94; 95%CI=1.47 to 5.97), elevated D-dimer (OR=2.66; 95%CI=1.15 to 6.51) and low platelet count (OR=2.41; 95%CI=1.12 to 5.14). Myalgia or artralgia (OR=0.28; 95%CI=0.10 to 0.66), dysgeusia (OR=0.28; 95%CI=0.05 to 0.92) and anosmia (OR=0.23; 95%CI=0.04 to 0.75) were protective factors.

Conclusion

Determining the clinical, biological and radiological characteristics of patients with suspected COVID-19 infection will be key to early treatment and isolation and the tracing of contacts.
Kidney function on admission predicts in-hospital mortality in COVID-19
Authors: Trabulus Sinan , Karaca Cebrail , İnanç Balkan İlker , Dincer Mevlüt Tamer , Murt Ahmet , Gül Özcan Şeyda , Karaali Rıdvan , Mete Bilgül , Bakır Alev , Kuşkucu Mert Ahmet , Altıparmak Mehmet Rıza , Tabak Fehmi , Seyahi Nurhan
Published: June 2020

Background

Recent data have reinforced the concept of a reciprocal relationship between COVID-19 and kidney function. However, most studies have focused on the effect of COVID-19 on kidney function, whereas data regarding kidney function on the COVID-19 prognosis is scarce. Therefore, in this study, we aimed to investigate the association between eGFR on admission and the mortality rate of COVID-19.

Methods

We recruited 336 adult consecutive patients (male 57.1%, mean age 55.0±15.9) that were hospitalized with the diagnosis of COVID-19 in the tertiary care university hospital. Data were collected from the electronic health records of the hospital. On admission, eGFR was calculated using the CKD-EPI formula. Acute kidney injury was defined according to the KDIGO criteria. Binary logistic regression and Cox regression analyses were used to assess the relationship between eGFR on admission and in-hospital mortality of COVID-19.

Results

Baseline eGFR was under 60 mL/min/1.73m2in 61 patients (18.2%). Acute kidney injury occurred in 29.1% of the patients. In-hospital mortality was calculated as 12.8%. Age-adjusted and multivariate logistic regression analysis (p:0.005, odds ratio:0.974, CI:0.956-0.992) showed that baseline eGFR was independently associated with mortality. Additionally, age-adjusted Cox regression analysis revealed a higher mortality rate in patients with an eGFR under 60 mL/min/1.73m2.

Conclusions

On admission eGFR seems to be a prognostic marker for mortality in patients with COVID-19; We recommend to determine eGFR in all patients on admission and use it as an additional tool for risk stratification. Close follow-up should be warranted in patients with reduced eGFR.
Dimensions and modulators of behavioural and mental-health change during the Covid-19 pandemic
Authors: Hampshire Adam , Hellyer Peter , Soreq Eyal , Mehta Mitul A. , Ioannidis Konstantinos , Trender William , Grant Jon E. , Chamberlain Samuel R.
Published: June 2020

How has the Covid-19 pandemic affected mental health? What are the most common positives and negatives? How do population variables mediate the impact on mood and behaviour? Who is most at risk of adverse consequences? Which pragmatic measures can help? We address these questions in a data-driven manner by applying multivariate, machine-learning and natural-language processing methods to a survey database collected from 376,987 members of the general public. We report that small average changes in mood from pre-to mid-pandemic obfuscate substantial consequences, both positive and negative, for people from particular sub-populations, vocations, circumstances and personality profiles. The coping strategies that people find helpful during the pandemic are correspondingly diverse yet predictable. We propose that by combining psychological, and demographic variables, it is possible to identify individuals who are at most risk of adverse consequences and to extract individually tailored advice from the collective lived experiences of the general population.
Twitter activity about treatments during the COVID-19 pandemic: case studies of remdesivir, hydroxychloroquine, and convalescent plasma
Authors: Hamamsy Tymor , Bonneau Richard
Published: June 2020

Since the COVID-19 pandemic started, the public has been eager for news about promising treatments, and social media has played a large role in information dissemination. In this paper, our objectives are to characterize the public discussion of treatments on Twitter, and demonstrate the utility of these discussions for public health surveillance. We pulled tweets related to three promising COVID-19 treatments (hydroxychloroquine, remdesivir and convalescent plasma), between the dates of February 28th and May 22nd using the Twitter public API. We characterize treatment tweet trends over this time period. Most major tweet/retweet/sentiment trends correlated to public announcement made by the white house and/or to new clinical trial evidence about treatments. Most of the websites people shared in treatment-related tweets were non-scientific media sources that leaned conservative. Hydroxychloroquine was the most discussed treatment on Twitter, and over 10% of hydroxychloroquine tweets mentioned an adverse drug reaction. There is a gap between the public attention/discussion around COVID-19 treatments and their evidence. Twitter data can and should be used for public health surveillance during this pandemic, as it is informative for monitoring adverse drug reactions, especially as many people avoid going to hospitals/doctors.
Estimating and explaining the spread of COVID-19 at the county level in the USA
Authors: Ives Anthony R. , Bozzuto Claudio
Published: June 2020

The basic reproduction number, R0, determines the rate of spread of a communicable disease and therefore gives fundamental information needed to plan public health interventions. Estimated R0 values are only useful, however, if they accurately predict the future potential rate of spread. Using mortality records, we estimated the rate of spread of COVID-19 among 160 counties and county-aggregates in the USA. Most of the high among-county variance in the rate of spread was explained by four factors: the timing of the county-level outbreak (partial R2 = 0.093), population size (partial R2 = 0.34), population density (partial R2 = 0.13), and spatial location (partial R2 = 0.42). Of these, the effect of timing is explained by early steps that people and governments took to reduce transmission, and population size is explained by the sample size of deaths that affects the statistical ability to estimate R0. For predictions of future spread, population density is important, likely because it scales the average contact rate among people. To generate support for a possible explanation for the importance of spatial location, we show that SARS-CoV-2 strains containing the G614 mutation to the spike gene are associated with higher rates of spread (P = 0.016). The high predictability of R0 based on population density and spatial location allowed us to extend estimates to all 3109 counties in the lower 48 States. The high variation of R0 among counties argues for public health policies that are enacted at the county level for controlling COVID-19.
A Combined Deep CNN-LSTM Network for the Detection of Novel Coronavirus (COVID-19) Using X-ray Images
Authors: Islam Md. Zabirul , Islam Md. Milon , Asraf Amanullah
Published: June 2020

Nowadays automatic disease detection has become a crucial issue in medical science with the rapid growth of population. Coronavirus (COVID-19) has become one of the most severe and acute diseases in very recent times that has been spread globally. Automatic disease detection framework assists the doctors in the diagnosis of disease and provides exact, consistent, and fast reply as well as reduces the death rate. Therefore, an automated detection system should be implemented as the fastest way of diagnostic option to impede COVID-19 from spreading. This paper aims to introduce a deep learning technique based on the combination of a convolutional neural network (CNN) and long short-term memory (LSTM) to diagnose COVID-19 automatically from X-ray images. In this system, CNN is used for deep feature extraction and LSTM is used for detection using the extracted feature. A collection of 421 X-ray images including 141 images of COVID-19 is used as a dataset in this system. The experimental results show that our proposed system has achieved 97% accuracy, 91% specificity, and 100% sensitivity. The system achieved desired results on a small dataset which can be further improved when more COVID-19 images become available. The proposed system can assist doctors to diagnose and treatment the COVID-19 patients easily.
Epidemiological characterization of asymptomatic carriers of COVID-19 in Colombia
Authors: Teherán Aníbal A. , Camero Gabriel , de la Guardia Ronald Prado , Hernández Carolina , Herrera Giovanny , Pombo Luis M. , Ávila Albert A. , Flórez Carolina , Barros Esther C. , Perez-Garcia Luis A. , Paniz-Mondolfi Alberto , Ramírez Juan David
Published: June 2020

Objective

Asymptomatic carriers (AC) of the new Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) represent an important source of spread for Coronavirus Disease 2019 (COVID-19). Early diagnosis of these cases is a powerful tool to control the pandemic. Our objective was to characterize patients with AC status and identify associated sociodemographic factors.

Methods

Using a cross-sectional design and the national database of daily occurrence of COVID-19, we characterized both socially and demographically all ACs. Additional Correspondence Analysis and Logistic Regression Model were performed to identify characteristics associated with AC state (OR, 95% CI).

Results

2338 ACs (11.8%; 95% CI, 11.3-12.2%) were identified, mainly in epidemiological week 18 [EW] (3.98; 3.24-4.90). Age ≤ 39 years (1.56; 1.42-1.72). Male sex (1.39; 1.26-1.53), cases imported from Argentina, Spain, Peru, Brazil, Costa Rica or Mexico (3.37; 1.47-7.71) and autochthonous cases (4.35; 2.12-8.93) increased the risk of identifying AC. We also identified groups of departments with moderate (3.68; 3.13-4.33) and strong (8.31; 6.10-7.46) association with AC.

Discussion

Sociodemographic characteristics strongly associated with AC were identified, which may explain its epidemiological relevance and usefulness to optimize mass screening strategies and prevent person-to-person transmission.
Modelling for prediction of the spread and severity of COVID-19 and its association with socioeconomic factors and virus types
Authors: Tuli Shreshth , Tuli Shikhar , Verma Ruchi , Tuli Rakesh
Published: June 2020

We report the development of a Weibull based Long-Short-Term-Memory approach (W-LSTM) for the prediction of COVID-19 disease. The W-LSTM model developed in this study, performs better in terms of MSE, R2 and MAPE, as compared to the previously published models, including ARIMA, LSTM and their variations. Using W-LSTM model, we have predicted the beginning and end of the current cycle of COVID-19 in several countries. Performance of the model was validated as satisfactory in 82% of the 50 test countries, while asking for prediction for 10 days beyond the period of training. Accuracy of the above prediction with days beyond training was assessed in comparison with the MAPE that the model gave with cumulative global data. The model was applied to study correlation between the growth of infection and deaths, and a number of effectors that may influence the epidemic. The model identified age groups, trade with China, air traffic, country temperature and CoV-2 virus types as the likely effectors of infection and virulence leading to deaths. The predictors likely to promote or suppress the epidemic were identified. Some of the predictors had significant effect on the shape parameters of Weibull distribution. The model can function on cloud, take inputs in real time and handle large data country wise, at low costs to make predictions dynamically. Such predictions are highly valuable in guiding policy makers, administration and health. Interactive curves generated from the W-LSTM model can be seen at http://collaboration.coraltele.com/covid2/.
Association of Assisted Reproductive Technologies with offspring cord blood DNA methylation across cohorts
Authors: Caramaschi Doretta , Jungius James , Page Christian M. , Novakovic Boris , Saffery Richard , Halliday Jane , Lewis Sharon , Magnus Maria C. , London Stephanie J. , Håberg Siri E. , Relton Caroline L. , Lawlor Deborah A. , Elliott Hannah R.
Published: June 2020

Study question

Is DNA methylation at birth associated with having been conceived by assisted reproductive technologies (ART)?

Summary answer

This study shows does not provide strong evidence of an association of conception by ART with variation in infant blood cell DNA methylation.

What is known already

Assisted reproductive technologies (ART) are procedures used to help infertile/subfertile couples conceive. Due to its importance in gene regulation during early development programming, DNA methylation and its perturbations associated with ART could reveal new insights into the biological effects of ART and potential adverse offspring outcomes.

Study design

We investigated the association of DNA methylation and ART using a case-control study design (N=205 ART cases and N=2439 non-ART controls in discovery cohorts; N=149 ART cases and N=58 non-ART controls in replication cohort).

Participants/materials, settings, method

We assessed the association between ART and DNA methylation at birth in cord blood (205 ART conceptions and 2439 naturally conceived controls) at >450000 CpG sites across the genome in two sub-samples of the UK Avon Longitudinal Study of Parents and Children (ALSPAC) and two sub-samples of the Norwegian Mother, Father and Child Cohort Study (MoBa) by meta-analysis. We explored replication of findings in the Australian Clinical review of the Health of adults conceived following Assisted Reproductive Technologies (CHART) study (N=149 ART conceptions and N=58 controls).

Main results and the role of chance

The ALSPAC and MoBa meta-analysis revealed evidence of association between conception by ART and DNA methylation (false-discovery-rate-corrected p-value < 0.05) at 5 CpG sites which are annotated to 2 genes. Methylation at 3 of these sites has been previously linked to cancer, aging, HIV infection and neurological diseases. None of these associations replicated in the CHART cohort. There was evidence of a functional role of ART-induced hypermethylation at CpG sites located within regulatory regions as shown by putative transcription factor binding and chromatin remodelling.

Limitations, reasons for cautions

While insufficient power is likely, heterogeneity in types of ART and between populations may also contribute. Larger studies might identify replicable variation in DNA methylation at birth due to ART.

Wider implications of the findings

ART-conceived newborns present with divergent DNA methylation in cord blood white cells. If these associations are true and causal, they might have long-term consequences for offspring health.
P-wave Centric Ambulatory ECG Monitoring in Infants and Young Children
Authors: Romme Angela , Nguyen Hoang
Published: June 2020

Background

P-wave centric ambulatory ECG monitoring has emerged as an important tool aiding the diagnosis of arrhythmias. However, with no specific pediatric approved ambulatory monitors, efficacy and user experience with these devices in young infants have not been established.

Objective

To evaluate tracings quality in children less than 10 kilograms who have been prescribed the P-wave centric Carnation Ambulatory Monitor (CAM) patch by Bardy Diagnostics Inc.

Methods

We performed an observational, retrospective study on patients prescribed 48-hour ambulatory Holter monitoring. We aimed to detail our experience with using the CAM patch with a patient population smaller than the recommended weight set forth by Bardy Diagnostics Inc. All patients less than 10 kg who were prescribed a 48-hour CAM patch were included in this review. Additionally, 2 different monitor locations (over the sternum and horizontal over the left axilla) were assessed to address the optimal placement in small children less than 10 kg.

Results

A total of 33 CAM reports from 25 patients, aged 0-15 months were included in the study. Mean patient age was 4.2 months ± 5.0 and mean weight was 5.3 kg ± 2.4. Twenty-Four percent of patients (8/33) had known congenital heart disease. Indications for monitoring included: tachyarrhythmia (15/33, 45%), bradycardia (6/33, 18%), ectopic rhythm (9/33, 27%), cardiac tumor (1/33, 1%), and prolonged QT interval (1/33, 1%). All CAM reports showed clear, identifiable P waves which were diagnostic and lead to changes in medical management for 30% of patients (i.e. medication adjustments or discharge from cardiology care). When comparing the P wave between a 12-lead ECG and the CAM patch, 77% of patients had the same or similar P wave morphology to lead aVF.

We found the recommended, upright placement over the sternum performed better than the horizontal placement over the left axilla for small infants and children less than 10 kg.

Conclusion

A P-wave centric Holter monitor is helpful in providing accurate diagnostics tracings even in infants and small children aiding in their clinical management.