3,315 research outputs found

    Coronaviridae—Old friends, new enemy!

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    Coronaviridae is a family of single‐stranded positive enveloped RNA viruses. This article aimed to review the history of these viruses in the last 60 years since their discovery to understand what lessons can be learned from the past. A review of the PubMed database was carried out, describing taxonomy, classification, virology, genetic recombination, host adaptation, and main symptoms related to each type of virus. SARS‐CoV‐2 is responsible for the ongoing global pandemic, and SARS‐CoV and MERS‐CoV were responsible for causing severe respiratory illness and regional epidemics in the past while the four other strains of CoVs (229‐E OC43, NL63, and HKU1) circulate worldwide and normally only cause mild upper respiratory tract infections. Given the enormous diversity of coronavirus viruses in wildlife and their continuous evolution and adaptation to humans, future outbreaks would undoubtedly occur. Restricting or banning all trade in wild animals in wet markets would be a necessary measure to reduce future zoonotic infections

    A Real-Time intelligent system for tracking patient condition

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    Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance

    Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting

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    Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post—the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus. / Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics. / Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%. / Conclusion: Spatio-temporal analysis provided a broader assessment of those in the regions where the accumulated confirmed cases of Covid-19 were concentrated. It was possible to differentiate in the thematic maps the regions with the highest concentration of cases from the regions with low concentration and regions in the transition range. This approach is fundamental to support health managers and epidemiologists to elaborate policies and plans to control the Covid-19 pandemics

    COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19

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    Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To evaluate strategies for alleviating such problems, it is necessary to forecast the number of cases and deaths in order to aid the stakeholders in the process of making decisions against the disease. We propose a novel system for real-time forecast of the cumulative cases of Covid-19 in Brazil. / Methods: We developed the novel COVID-SGIS application for the real-time surveillance, forecast and spatial visualization of Covid-19 for Brazil. This system captures routinely reported Covid-19 information from 27 federative units from the Brazil.io database. It utilizes all Covid-19 confirmed case data that have been notified through the National Notification System, from March to May 2020. Time series ARIMA models were integrated for the forecast of cumulative number of Covid-19 cases and deaths. These include 6-days forecasts as graphical outputs for each federative unit in Brazil, separately, with its corresponding 95% CI for statistical significance. In addition, a worst and best scenarios are presented. / Results: The following federative units (out of 27) were flagged by our ARIMA models showing statistically significant increasing temporal patterns of Covid-19 cases during the specified day-to-day period: Bahia, MaranhĂŁo, PiauĂ­, Rio Grande do Norte, AmapĂĄ, RondĂŽnia, where their day-to-day forecasts were within the 95% CI limits. Equally, the same findings were observed for EspĂ­rito Santo, Minas Gerais, ParanĂĄ, and Santa Catarina. The overall percentage error between the forecasted values and the actual values varied between 2.56 and 6.50%. For the days when the forecasts fell outside the forecast interval, the percentage errors in relation to the worst case scenario were below 5%. / Conclusion: The proposed method for dynamic forecasting may be used to guide social policies and plan direct interventions in a cost-effective, concise, and robust manner. This novel tools can play an important role for guiding the course of action against the Covid-19 pandemic for Brazil and country neighbors in South America

    Impact of Routine Fractional Flow Reserve Evaluation During Coronary Angiography on Management Strategy and Clinical Outcome: One-Year Results of the POST-IT Multicenter Registry

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    Penetration of fractional flow reserve (FFR) in clinical practice varies extensively, and the applicability of results from randomized trials is understudied. We describe the extent to which the information gained from routine FFR affects patient management strategy and clinical outcome. METHODS AND RESULTS: Nonselected patients undergoing coronary angiography, in which at least 1 lesion was interrogated by FFR, were prospectively enrolled in a multicenter registry. FFR-driven change in management strategy (medical therapy, revascularization, or additional stress imaging) was assessed per-lesion and per-patient, and the agreement between final and initial strategies was recorded. Cardiovascular death, myocardial infarction, or unplanned revascularization (MACE) at 1 year was recorded. A total of 1293 lesions were evaluated in 918 patients (mean FFR, 0.81±0.1). Management plan changed in 406 patients (44.2%) and 584 lesions (45.2%). One-year MACE was 6.9%; patients in whom all lesions were deferred had a lower MACE rate (5.3%) than those with at least 1 lesion revascularized (7.3%) or left untreated despite FFR≀0.80 (13.6%; log-rank P=0.014). At the lesion level, deferral of those with an FFR≀0.80 was associated with a 3.1-fold increase in the hazard of cardiovascular death/myocardial infarction/target lesion revascularization (P=0.012). Independent predictors of target lesion revascularization in the deferred lesions were proximal location of the lesion, B2/C type and FFR. CONCLUSIONS: Routine FFR assessment of coronary lesions safely changes management strategy in almost half of the cases. Also, it accurately identifies patients and lesions with a low likelihood of events, in which revascularization can be safely deferred, as opposed to those at high risk when ischemic lesions are left untreated, thus confirming results from randomized trials

    Socioeconomic factors and health status disparities associated with difficulty in ADLs and IADLs among long-lived populations in Brazil: a cross-sectional study

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    © 2021 The Authors. Published by Sage. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://journals.sagepub.com/doi/full/10.1177/00469580211007264Objective: To evaluate the association between socioeconomic factors, health status, and Functional Capacity (FC) in the oldest senior citizens in a metropolis and a poor rural region of Brazil. Method: Cross-sectional study of 417 seniors aged ≄80 years, data collected through Brazil’s Health, Well-being and Aging survey. FC assessed by self-reporting of difficulties in Activities of Daily Living (ADLs) and Instrumental Activities of Daily Living (IADLs). Chi-square tests and multiple logistic regression analyses were performed using “R” statistical software. Results: Socioeconomic and demographic inequalities in Brazil can influence FC in seniors aged 80 years and older. Comparatively, urban long-lived people had a higher prevalence of difficulties for ADLs and rural ones showed more difficulties for IADLs. Among urban oldest seniors, female gender and lower-income were correlated with difficulties for IADLs. Among rural oldest seniors, female gender, stroke, joint disease, and inadequate weight independently were correlated with difficulties for ADLs, while the number of chronic diseases was associated with difficulties for IADLs. Conclusion: Financial constraints may favor the development of functional limitations among older seniors in large urban centers. In poor rural areas, inadequate nutritional status and chronic diseases may increase their susceptibility to functional decline

    Comparative cytogenetic analysis between Lonchorhina aurita and Trachops cirrhosus (Chiroptera, Phyllostomidae)

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    Phyllostomidae comprises the most diverse family of neotropical bats, its wide range of morphological features leading to uncertainty regarding phylogenetic relationships. Seeing that cytogenetics is one of the fields capable of providing support for currently adopted classifications through the use of several markers, a comparative analysis between two Phyllostomidae species was undertaken in the present study, with a view to supplying datasets for the further establishment of Phyllostomidae evolutionary relationships. Karyotypes of Lonchorhina aurita (2n = 32; FN = 60) and Trachops cirrhosus (2n = 30; FN = 56) were analyzed by G- and C-banding, silver nitrate staining (Ag-NOR) and base-specific fluorochromes. Chromosomal data obtained for both species are in agreement with those previously described, except for X chromosome morphology in T. cirrhosus, hence indicating chromosomal geographical variation in this species. A comparison of G-banding permitted the identification of homeologies in nearly all the chromosomes. Furthermore, C-banding and Ag-NOR patterns were comparable to what has already been observed in the family. In both species CMA3 /DA/DAPI staining revealed an R-banding-like pattern with CMA 3 , whereas DAPI showed uniform staining in all the chromosomes. Fluorochrome staining patterns for pericentromeric constitutive heterochromatin (CH) regions, as well as for nucleolar organizing regions (NORs), indicated heterogeneity regarding these sequences among Phyllostomidae species
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