Gender differences in patients with COVID-19: Focus on severity and mortality

AbstractImportanceThe recent outbreak of Novel Coronavirus (SARS-CoV-2) Disease (COVID-19) has put the world on alert, that is reminiscent of the SARS outbreak seventeen years ago.ObjectiveWe aim to compare the severity and mortality between male and female patients with both COVID-19 and SARS, to explore the most useful prognostic factors for individualized assessment.Design, Setting, and ParticipantsWe extracted the data from a case series of 43 hospitalized patients we treated, a public data set of the first 37 cases died of COVID-19 in Wuhan city and 1019 survived patients from six cities in China. We also analyzed the data of 524 patients with SARS, including 139 deaths, from Beijing city in early 2003.Main Outcomes and MeasuresSeverity and mortality.ResultsOlder age and high number of comorbidities were associated with higher severity and mortality in patients with both COVID-19 and SARS. The percentages of older age (≥65 years) were much higher in the deceased group than in the survived group in patients with both COVID-19 (83.8 vs. 13.2, P<0.001) and SARS (37.4 vs. 4.9, P<0.001). In the case series, men tend to be more serious than women (P=0.035), although age was comparable between men and women. In the public data set, age was also comparable between men and women in the deceased group or the survived group in patients with COVID-19. Meanwhile, gender distribution was exactly symmetrical in the 1019 survivors of COVID-19. However, the percentage of male were higher in the deceased group than in the survived group (70.3 vs. 50.0, P=0.015). The gender role in mortality was also observed in SARS patients. Survival analysis showed that men (hazard ratio [95% CI] 1.47 [1.05-2.06, P= 0.025) had a significantly higher mortality rate than women in patients with SARS.Conclusions and RelevanceOlder age and male gender are risk factors for worse outcome in patients with COVID. While men and women have the same susceptibility to both SARS-CoV-2 and SARS-CoV, men may be more prone to have higher severity and mortality independent of age and susceptibility.Key PointsQuestionAre men more susceptible to getting and dying from COVID-19?FindingsIn the case series, men tend to be more serious than women. In the public data set, the percentage of men were higher in the deceased group than in the survived group, although age was comparable between men and women.MeaningMale gender is a risk factor for worse outcome in patients with COVID independent of age and susceptibility.

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Dynamics based on analysis of public data for spreading of disease

10.21203/rs.3.rs-86552/v2 ◽

2021 ◽

Author(s):

Leonardo S. Lima

Keyword(s):

Planck Equation ◽

The Novel ◽

Epidemic Spreading ◽

Data Set ◽

Public Health Agencies ◽

The Public ◽

Public Data ◽

Health Agencies ◽

Novel Coronavirus ◽

Official Data

Abstract The stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supported by the public health agencies in countries as Brazil, EUA and India is investigated. We perform the numerical analysis using the stochastic differential equation in Itô’s calculus (SDE) for the estimating of novel cases daily as well as analytical calculations solving the correspondent Fokker-Planck equation for the density probability distribution of novel cases, P(N(t); t). Our results display that the model based in the Itô diffusion fits well to the results due to uncertain in the official data and to the number of tests realized in the populations of each country.

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Dynamics based on analysis of public data for spreading of disease

10.21203/rs.3.rs-86552/v3 ◽

2021 ◽

Author(s):

Leonardo S. Lima

Keyword(s):

Planck Equation ◽

Probability Density Distribution ◽

The Novel ◽

Epidemic Spreading ◽

Data Set ◽

Public Health Agencies ◽

The Public ◽

Public Data ◽

Health Agencies ◽

Novel Coronavirus

Abstract The stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supply by the public health agencies in countries as Brazil, United States and India is investigated. We perform a numerical analysis using the stochastic differential equation in Itô’s calculus for the estimating of novel cases daily, as well as analytical calculations solving the correspondent Fokker-Planck equation for the probability density distribution of novel cases, P(N(t); t). Our results display that the model based in the Itô’s diffusion fits well to the results due to uncertainty in the official data and to the number of testsrealized in populations of each country.

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Dynamics based on analysis of public data for spreading of disease

10.21203/rs.3.rs-86552/v1 ◽

2020 ◽

Author(s):

Leonardo S. Lima

Keyword(s):

Public Health ◽

The Novel ◽

Epidemic Spreading ◽

Data Set ◽

Public Health Agencies ◽

The Public ◽

Public Data ◽

Health Agencies ◽

Novel Coronavirus ◽

Official Data

Abstract The stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supported by the public health agencies in countries as Brazil, EUA and India is investigated. We performed the numerical analysis using the stochastic differential equation for estimating of the novel cases diary as well as analytical calculations solving the correspondent partial equation for the distribution of novel cases P. Our results display that the model based in the Itô diffusion fits well to the results diary due to uncertain in the official data and to the number of tests realized in the populations of each country.

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Dynamics based on analysis of public data for spreading of disease

Scientific Reports ◽

10.1038/s41598-021-91024-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Leonardo S. Lima

Keyword(s):

Planck Equation ◽

Probability Density Distribution ◽

The Novel ◽

Epidemic Spreading ◽

Data Set ◽

Public Health Agencies ◽

The Public ◽

Public Data ◽

Health Agencies ◽

Novel Coronavirus

AbstractThe stochastic model for epidemic spreading of the novel coronavirus disease based on the data set supply by the public health agencies in countries as Brazil, United States and India is investigated. We perform a numerical analysis using the stochastic differential equation in Itô’s calculus for the estimating of novel cases daily, as well as analytical calculations solving the correspondent Fokker–Planck equation for the probability density distribution of novel cases, P(N(t), t). Our results display that the model based in the Itô’s diffusion fits well to the results due to uncertainty in the official data and to the number of tests realized in populations of each country.

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CNVScope: Visually Exploring Copy Number Aberrations in Cancer Genomes

Cancer Informatics ◽

10.1177/1176935119890290 ◽

2019 ◽

Vol 18 ◽

pp. 117693511989029

Author(s):

James LT Dalgleish ◽

Yonghong Wang ◽

Jack Zhu ◽

Paul S Meltzer

Keyword(s):

Copy Number ◽

High Performance ◽

Data Sets ◽

Data Set ◽

The Public ◽

Public Data ◽

Analysis Package ◽

Cis And Trans ◽

High Performance Computing Cluster ◽

Shiny Application

Motivation: DNA copy number (CN) data are a fast-growing source of information used in basic and translational cancer research. Most CN segmentation data are presented without regard to the relationship between chromosomal regions. We offer both a toolkit to help scientists without programming experience visually explore the CN interactome and a package that constructs CN interactomes from publicly available data sets. Results: The CNVScope visualization, based on a publicly available neuroblastoma CN data set, clearly displays a distinct CN interaction in the region of the MYCN, a canonical frequent amplicon target in this cancer. Exploration of the data rapidly identified cis and trans events, including a strong anticorrelation between 11q loss and17q gain with the region of 11q loss bounded by the cell cycle regulator CCND1. Availability: The shiny application is readily available for use at http://cnvscope.nci.nih.gov/ , and the package can be downloaded from CRAN ( https://cran.r-project.org/package=CNVScope ), where help pages and vignettes are located. A newer version is available on the GitHub site ( https://github.com/jamesdalg/CNVScope/ ), which features an animated tutorial. The CNVScope package can be locally installed using instructions on the GitHub site for Windows and Macintosh systems. This CN analysis package also runs on a linux high-performance computing cluster, with options for multinode and multiprocessor analysis of CN variant data. The shiny application can be started using a single command (which will automatically install the public data package).

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An end-to-End deep context gate convolutional visual odometry system based on lightweight attention mechanism

Industrial Robot the international journal of robotics research and application ◽

10.1108/ir-01-2021-0019 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Yan Xu ◽

Hong Qin ◽

Jiani Huang ◽

Yanyun Wang

Keyword(s):

Visual Odometry ◽

Attention Mechanism ◽

Learning Ability ◽

Global Features ◽

Data Set ◽

Content Type ◽

Generalization Ability ◽

The Public ◽

Public Data ◽

End To End

Purpose Conventional learning-based visual odometry (VO) systems usually use convolutional neural networks (CNN) to extract features, where some important context-related and attention-holding global features might be ignored. Without essential global features, VO system will be sensitive to various environmental perturbations. The purpose of this paper is to design a novel learning-based framework that aims to improve accuracy of learning-based VO without decreasing the generalization ability. Design/methodology/approach Instead of CNN, a context-gated convolution is adopted to build an end-to-end learning framework, which enables convolutional layers that dynamically capture representative local patterns and composes local features of interest under the guidance of global context. In addition, an attention mechanism module is introduced to further improve learning ability and enhance robustness and generalization ability of the VO system. Findings The proposed system is evaluated on the public data set KITTI and the self-collected data sets of our college building, where it shows competitive performance compared with some classical and state-of-the-art learning-based methods. Quantitative experimental results on the public data set KITTI show that compared with CNN-based VO methods, the average translational error and rotational error of all the test sequences are reduced by 45.63% and 37.22%, respectively. Originality/value The main contribution of this paper is that an end-to-end deep context gate convolutional VO system based on lightweight attention mechanism is proposed, which effectively improves the accuracy compared with other learning-based methods.

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Management and Early Outcomes of Neonates Born to Women with SARS-CoV-2 in 16 U.S. Hospitals

American Journal of Perinatology ◽

10.1055/s-0041-1726036 ◽

2021 ◽

Author(s):

Jayme L. Congdon ◽

Laura R. Kair ◽

Valerie J. Flaherman ◽

Kelly E. Wood ◽

Mary Ann LoFrumento ◽

...

Keyword(s):

Clinical Management ◽

Neonatal Intensive Care ◽

Clinical Care ◽

Case Series ◽

Neonatal Outcomes ◽

Term Neonates ◽

Key Points ◽

Inpatient Management ◽

Novel Coronavirus

Objective There is a paucity of evidence to guide the clinical care of late preterm and term neonates born to women with perinatal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The objective of this case series is to describe early neonatal outcomes and inpatient management in U.S. hospitals. Study Design We solicited cases of mother–infant dyads affected by novel coronavirus disease 2019 (COVID-19) from the Better Outcomes through Research for Newborns (BORN) Network members. Using a structured case template, participating sites contributed deidentified, retrospective birth hospitalization data for neonates ≥35 weeks of gestation at birth with mothers who tested positive for SARS-CoV-2 before delivery. We describe demographic and clinical characteristics, clinical management, and neonatal outcomes. Results Sixteen U.S. hospitals contributed 70 cases. Birth hospitalizations were uncomplicated for 66 (94%) neonates in which 4 (6%) required admission to a neonatal intensive care unit. None required evaluation or treatment for infection, and all who were tested for SARS-CoV-2 were negative (n = 57). Half of the dyads were colocated (n = 34) and 40% directly breastfed (n = 28). Outpatient follow-up data were available for 13 neonates, all of whom remained asymptomatic. Conclusion In this multisite case series of 70 neonates born to women with SARS-CoV-2 infection, clinical outcomes were overall good, and there were no documented neonatal SARS-CoV-2 infections. Clinical management was largely inconsistent with contemporaneous U.S. COVID-19 guidelines for nursery care, suggesting concerns about the acceptability and feasibility of those recommendations. Longitudinal studies are urgently needed to assess the benefits and harms of current practices to inform evidence-based clinical care and aid shared decision-making. Key Points

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E-cigarette manufacturers’ compliance with clinical trial reporting expectations: a case series of registered trials by Juul Labs

Tobacco Control ◽

10.1136/tobaccocontrol-2020-056221 ◽

2021 ◽

pp. tobaccocontrol-2020-056221

Author(s):

Nicholas J DeVito ◽

Henry Drysdale ◽

Martin McKee ◽

Ben Goldacre

Keyword(s):

Public Health ◽

Clinical Trials ◽

Electronic Cigarettes ◽

Case Series ◽

Research Database ◽

The Public ◽

Public Data ◽

The Usa ◽

Specific Outcome ◽

Reporting Laws

BackgroundElectronic cigarettes (e-cigarettes) are a frequently debated topic in public health. It is essential that clinical trials examining e-cigarettes are fully and accurately reported, especially given long-standing concerns about tobacco industry research. We assess the reporting of clinical trials sponsored by Juul Labs, the largest e-cigarette company in the USA, against accepted reporting standards.MethodsWe searched ClinicalTrials.gov for all trials sponsored by Juul Labs and determined those with registry data consistent with coverage by the Food and Drug Administration (FDA) Amendments Act 2007 (FDAAA). For trials with a primary completion date more than 1 year earlier, we searched ClinicalTrials.gov, the academic literature and a Juul-funded research database (JLI Science) for results. For located results, we compared reported outcomes with registered outcomes in line with Consolidated Standards of Reporting Trials (CONSORT) reporting guidelines.ResultsWe located five registered trials sponsored by Juul Labs that appeared covered by the FDAAA 2007 in the public data. All five trials did not have results available on ClinicalTrials.gov. We found one publication and four poster presentations reporting results for four of the five covered trials outside of ClinicalTrials.gov. Of 61 specified outcomes, 28 were CONSORT compliant. Specific outcome reporting issues are detailed.DiscussionOur findings raise substantial concerns regarding these trials. Clinicians, public health professionals, and the public cannot make informed choices about the benefits or hazards of e-cigarettes if the results of clinical trials are not completely and transparently reported. Clarification and potential enforcement of reporting laws may be required.

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