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Aim: Although most patients with COVID-19 experience respiratory tract infections, severe reactions to the virus may cause coagulation abnormalities that mimic other systemic coagulopathies associated with severe infections, such as disseminated intravascular coagulation and thrombotic microangiopathy. Fluctuations in platelet markers, which are an indicator of the acute phase response for COVID-19, are of clinical importance. The aim of this study is to evaluate the relationship between disease severity and Platelet Mass Index (MPI) parameters in COVID-19 patients. Material(s) and Method(s): This retrospective observational study was conducted with patients who were diagnosed with COVID-19 in a tertiary hospital. The study was continued with the remaining 280 patients. All laboratory data were scanned retrospectively from patient files and hospital information system. Result(s): A very high positive correlation was found between PMI and PLT. The PMI value in women was significantly higher than in men. It was observed that PMI did not differ significantly in terms of mortality, intubation, CPAP and comorbidity. PMI vs. Pneumonia Ct Severity Score, biochemistry parameters (AST, CRP), hemogram parameters (WBC, HGB, HCT, MCV, LYM, MPV EO) and coagulation factors (aPTT and FIB) at various levels of positive/negative, weak and strong, and significant relationship was found. There was no significant relationship between hormone and D-dimer when compared with PMI. Discussion(s): Although platelet count alone does not provide information about the prognosis of the disease, PMI may guide the clinician as an indicator of lung damage in seriously ill patients.Copyright © 2022, Derman Medical Publishing. All rights reserved.
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Compared to other respiratory viruses, the proportion of hospitalizations due to SARS-CoV-2 among children is relatively low. While severe illness is not common among children and young individuals, a particular type of severe condition called multisystem inflammatory syndrome in children (MIS-C) has been reported. The aim of this prospective cohort study, which followed a group of individuals under the age of 19, was to examine the characteristics of patients who had contracted SARS-CoV-2, including their coexisting medical conditions, clinical symptoms, laboratory findings, and outcomes. The study also aimed to investigate the features of children who met the WHO case definition of MIS-C, as well as those who required intensive care. A total of 270 patients were included between March 2020 and December 2021. The eligible criteria were individuals between 0-18 with a confirmed SARS-CoV-2 infection at the Infectious Disease Hospital "Prof. Ivan Kirov"in Sofia, Bulgaria. Nearly 76% of the patients were <= 12 years old. In our study, at least one comorbidity was reported in 28.1% of the cases, with obesity being the most common one (8.9%). Less than 5% of children were transferred to an intensive care unit. We observed a statistically significant difference in the age groups, with children between 5 and 12 years old having a higher likelihood of requiring intensive care compared to other age groups. The median values of PaO2 and SatO2 were higher among patients admitted to the standard ward, while the values of granulocytes and C-reactive protein were higher among those transferred to the intensive care unit. Additionally, we identified 26 children who met the WHO case definition for MIS-C. Our study data supports the evidence of milder COVID-19 in children and young individuals as compared to adults. Older age groups were associated with higher incidence of both MIS-C and ICU admissions.Copyright © 2023 P. Velikov et al., published by Sciendo.
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This paper presents a control system for indoor safety measures using a Faster R-CNN (Region-based Convolutional Neural Network) architecture. The proposed system aims to ensure the safety of occupants in indoor environments by detecting and recognizing potential safety hazards in real time, such as capacity control, social distancing, or mask use. Using deep learning techniques, the system detects these situations to be controlled, notifying the person in charge of the company if any of these are violated. The proposed system was tested in a real teaching environment at Rey Juan Carlos University, using Raspberry Pi 4 as a hardware platform together with an Intel Neural Stick board and a pair of PiCamera RGB (Red Green Blue) cameras to capture images of the environment and a Faster R-CNN architecture to detect and classify objects within the images. To evaluate the performance of the system, a dataset of indoor images was collected and annotated for object detection and classification. The system was trained using this dataset, and its performance was evaluated based on precision, recall, and F1 score. The results show that the proposed system achieved a high level of accuracy in detecting and classifying potential safety hazards in indoor environments. The proposed system includes an efficiently implemented software infrastructure to be launched on a low-cost hardware platform, which is affordable for any company, regardless of size or revenue, and it has the potential to be integrated into existing safety systems in indoor environments such as hospitals, warehouses, and factories, to provide real-time monitoring and alerts for safety hazards. Future work will focus on enhancing the system's robustness and scalability to larger indoor environments with more complex safety hazards.
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Extensive spread of the coronavirus disease (COVID-19) prompted an investigation of its diagnostic features. Acute viral pneumonia associated with COVID-19 has been described in detail using CT, radiography, and MRI. There is no data in the literature on the descriptive picture observed with dynamic MRI. Considering a comprehensive diagnostic approach, radiologists should know how to correctly recognize and interpret COVID-19 on MRI. This case series demonstrated the ability of dynamic MRI to detect the cloudy sky sign and distinguish it from consolidation in COVID-19 patients, thus presumably distinguishing between early or mild changes and a progressive clinical course. These changes in dynamic lung images on MRI can be recorded depending on the phase of the respiratory cycle. Thus, MRI, as a radiation-free tool that can be used to examine a patient with acute viral pneumonia COVID-19, can be useful in cases where access to computed tomography is limited and dynamic morphofunctional imaging is required. © Eco-Vector, 2023.
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The present study investigates the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the vaginal swabs of female patients diagnosed with coronavirus disease 2019 (COVID-19) based on a positive real-time reverse transcription polymerase chain reaction (RT-PCR) test on a combined throat and nasopharyngeal swab.This study included 48 female patients hospitalized in two tertiary hospitals diagnosed with COVID-19 based on a positive RT-PCR test of the combined throat and nasopharyngeal swab samples, along with clinical and radiological findings. The IBM SPSS software package was used for the statistical analysis of the study data.SARS-CoV-2 positivity was detected in only one patient (2.08 %) in the present study from RT-PCR tests of vaginal swab samples. This patient was a 64-year-old, postmenopausal woman who tested positive for SARS-CoV-2 in a RT-PCR test of a vaginal swab sample six days after having tested positive in an RT-PCR test of a combined throat and nasopharyngeal swab. The patient's partner also tested positive for SARS-CoV-2 in an RT-PCR of a combined throat and nasopharyngeal swab.The present study is the first to report the presence of SARS-CoV-2 in vaginal secretions in Türkiye. The authors believe there is a need for studies investigating the presence of SARS-CoV-2 in the semen samples of the male partners of female patients to establish whether the presence of SARS-CoV-2 in vaginal secretions can play a role in the transmission of the virus. [ FROM AUTHOR] Copyright of Turkish Journal of Biochemistry / Turk Biyokimya Dergisi is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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In recent years, the COVID-19 has made it difficult for people to interact with each other face-to-face, but various kinds of social interactions are still needed. Therefore, we have developed an online interactive system based on the image processing method, that allows people in different places to merge the human region of two images onto the same image in real-time. The system can be used in a variety of situations to extend its interactive applications. The system is mainly based on the task of Human Segmentation in the CNN (convolution Neural Network) method. Then the images from different locations are transmitted to the computing server through the Internet. In our design, the system ensures that the CNN method can run in real-time, allowing both side users can see the integrated image to reach 30 FPS when the network is running smoothly. © 2023 IEEE.
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Summary Introduction: The SARS-CoV-2 coronavirus, that causes the COVID-19 disease, has become a global public health problem that requires the implementation of rapid and sensitive diagnostic tests. Aim(s): To evaluate and compare the sensitivity of LAMP assay to a standard method and use RT-LAMP for the diagnosis of SARS-CoV-2 in clinical samples from Colombian patients. Method(s): A descriptive and cross-sectional study was conducted. A total of 25 nasopharyngeal swab samples including negative and positive samples for SARS-CoV-2 were analyzed, through the RT-LAMP method compared to the RT-qPCR assay. Result(s): LAMP method detected ~18 copies of the N gene, in 30 min, evidenced a detection limit similar to the standard method, in a shorter time and a concordance in RT-LAMP of 100% with the results. Conclusion(s): RT-LAMP is a sensitive, specific, and rapid method that can be used as a diagnostic aid of COVID-19 disease.Copyright © 2021. All Rights Reserved.
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Coronavirus disease 2019 (COVID-19) is a fatal pandemic viral disease caused by the severe acute respiratory syndrome corona virus type-2 (SARS-CoV-2). The aim of this study is to observe the associations of IL-6, SARS-COV-2 viral load (RNAemia), IL- 6 gene polymorphism and lymphocytes and monocytes in peripheral blood with disease severity in COVID-19 patients. This study was carried out from March 2021 to January 2022. RT-PCR positive 84 COVID-19 patients and 28 healthy subjects were enrolled. Blood was collected to detect SARS-COV-2 viral RNA (RNAemia) by rRT-PCR, serum IL-6 level by chemiluminescence method, SNPs of IL-6 by SSP-PCR, immunophenotyping of lymphocytes and monocyte by flow cytometry. Serum IL-6 level (pg/ml) was considerably high among critical patients (102.02 +/- 149.7) compared to severe (67.20 +/- 129.5) and moderate patients (47.04 +/- 106.5) and healthy controls (3.5 +/- 1.8). Serum SARS-CoV-2 nucleic acid positive cases detected mostly in critical patients (39.28%) and was correlated with extremely high IL-6 level and high mortality (R =.912, P < 0.001). Correlation between IL-6 and monocyte was statistically significant with disease severity (severe group, p < 0.001, and 0.867*** and critical group p < 0.001 and 0.887***). In healthy controls, moderate, severe and critically ill COVID-19 patients, IL-6 174G/C (rs 1800795) GG genotype was 82.14%, 89.20%, 67.85% and 53.57% respectively. CC and GC genotype had strong association with severity of COVID-19 when compared with GG genotype. Significant statistical difference found in genotypes between critical and moderate groups (p < 0.001, OR-10.316, CI-3.22-23.86), where CC genotype was associated with COVID-19 severity and mortality. The absolute count of T cell, B cell, NK cell, CD4+ T cells and CD8+ T cells were significantly decreased in critical group compared to healthy, moderate and severe group (P < 0.001). Exhaustion marker CD94/NKG2A was increased on NK cells and CD8+ cytotoxic T cell among critical and severe group. Absolute count of monocyte was significantly increased in critical group (P < 0.001). Serum IL-6, IL-6 174 G/C gene and SARS-CoV-2 RNAaemia can be used in clinical practice for risk assessment;T cell subsets and monocyte as biomarkers for monitoring COVID-19 severity. Monoclonal antibody targeting IL-6 receptor and NKG2A for therapeutics may prevent disease progression and decrease morbidity and mortality.Copyright © 2023 Elsevier Inc.
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In this paper, we present a Distributionally Robust Markov Decision Process (DRMDP) approach for addressing the dynamic epidemic control problem. The Susceptible-Exposed-Infectious-Recovered (SEIR) model is widely used to represent the stochastic spread of infectious diseases, such as COVID-19. While Markov Decision Processes (MDP) offers a mathematical framework for identifying optimal actions, such as vaccination and transmission-reducing intervention, to combat disease spreading according to the SEIR model. However, uncertainties in these scenarios demand a more robust approach that is less reliant on error-prone assumptions. The primary objective of our study is to introduce a new DRMDP framework that allows for an ambiguous distribution of transition dynamics. Specifically, we consider the worst-case distribution of these transition probabilities within a decision-dependent ambiguity set. To overcome the computational complexities associated with policy determination, we propose an efficient Real-Time Dynamic Programming (RTDP) algorithm that is capable of computing optimal policies based on the reformulated DRMDP model in an accurate, timely, and scalable manner. Comparative analysis against the classic MDP model demonstrates that the DRMDP achieves a lower proportion of infections and susceptibilities at a reduced cost. [ FROM AUTHOR] Copyright of IISE Transactions is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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The aim of the study was to study the clinical and epidemiological features of the new COVID-19 coronavirus infection in children hospitalized in the infectious department. Material and methods. 249 case histories of patients from 0 to 18 years of age who are on inpatient treatment at <<Clinical Hospital N1>> in Smolensk for the period from April 2020 to July 2022 were studied by the continuous sampling method. Verification of a new coronavirus infection was carried out by examining smears from the nasopharynx and oropharynx for the presence of SARS-CoV-2 by real-time PCR. Results. The prevalence of patients from 1 to 3 (19.3%, 49.1%) and from 6-15 (15.8%, 50.5%) years was revealed both in 2020 and in 2021 and the first half of 2022. No significant differences in gender were found. The largest number of cases in 2020 was registered in April (16%) and November (14%), in 2021 - in December (18%) and November (16%). The prevailing severity in both 2020 and 2021, 2022 was the average severity (63%, 72%, 93%, respectively). The main syndromes of COVID-19 have been identified: intoxication syndrome, respiratory catarrhal syndrome, bronchopulmonary, intestinal. Bilateral pneumonia was most often detected (47% in 2020, 44% in 2021, 62% in 2022), right-sided pneumonia (33% in 2020, 30% in 2021, 31% in 2022), and left-sided pneumonia (20%, 26% and 7%, respectively). The main co-morbid pathologies are noted, and cases of somatic diseases first registered against the background of COVID-19 are described.Copyright © Children Infections.All rights reserved
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Objective: Intensive care units (ICUs) collapsed under the global wave of coronavirus disease 2019 (COVID-19). Thus, we designed a clinical decision-making model that can help predict at hospital admission what patients with COVID-19 are at higher risk of requiring critical care. Method(s): This was a cross-sectional study in 119 patients that met hospitalization criteria for COVID-19 including less than 30 breaths per minute, peripheral oxygen saturation < 93%, and/or >= 50% lung involvement on imaging. Depending on the need for critical care, patients were retrospectively assigned to ICU and non-ICU groups. Demographic, clinical, and laboratory parameters were collected at admission and analyzed by classification and regression tree (CRT). Result(s): Forty-five patients were admitted to ICU and 80% of them were men older than 57.13 +/- 12.80 years on average. The leading comorbidity in ICU patients was hypertension. The CRT revealed that direct bilirubin (DB) > 0.315 mg/dl together with the neutrophil-to-monocyte ratio (NMR) > 15.90 predicted up to correctly in 92% of the patients the requirement of intensive care management, with sensitivity of 93.2%. Preexisting comorbidities did not influence on the tree growing. Conclusion(s): At hospital admission, DB and NMR can help identify nine in 10 patients with COVID-19 at higher risk of ICU admission.Copyright © 2022 Sociedad Medica del Hospital General de Mexico.
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Burkholderia pseudomallei is soil saprophytic Gram-negative bacilli that cause a fatal disease called melioidosis. Melioidosis is capable of causing cutaneous infection and systemic infections in the respiratory tract, cardiovascular, gastrointestinal, urinary, skin and soft tissue, and musculoskeletal and central nervous systems. Here, we report rare forms of pulmonary, cerebral, and splenic abscess case series of melioidosis caused by B. pseudomallei. Imported cases have been reported among tourists, immigrants, and soldiers who returned from endemic areas. The acquisition of infection is through percutaneous, inhalation, and ingestion of contaminated water;person-to-person transmission is very rare. Melioidosis cases are primarily found in the rainfall season and are usually associated with risk factors such as diabetes, alcoholism, and chronic renal diseases. However, 20-26% of cases were not associated with predisposing conditions. The identification is based on colony morphology, Gram stain, antibiotic susceptibility testing, and other supportive automated and molecular assays when we suspect B. pseudomallei. There are two phases, the intensive and eradication phases, in managing melioidosis. In the intensive phase, ceftazidime for 2 weeks showed efficacy in almost 50% of cases, and the eradication phase treatment with co-trimoxazole and doxycycline or amoxicillin/clavulanic acid for 3-6 months showed an excellent response. The improper clinical diagnosis and management of B. pseudomallei can lead to complications. Hence, early diagnosis with microbiological approaches such as culture, biochemical reactions, or automated systems available and antimicrobial sensitivity testing will cure the patient quickly without mortality.Copyright © 2023 The Authors.
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Background: The quantification of SARS-CoV-2 in wastewater is a tool that allows determining the trend of viral circulation in a particular geographical area. Aim(s): To quantify the SARS-CoV-2 virus in 15 wastewater treatment plants in different Chilean cities to establish a comparison with the variables of: I) Active cases per 100,000 inhabitants;ii) daily positivity (novel cases);and iii) phases of the lockdown strategy. Method(s): SARS-CoV-2 was concentrated from wastewater samples. To obtain the number of virus genomes per liter, absolute quantification was performed using qRT-PCR. Result(s): Between January and June 2021, 253 samples were processed, all of which were positive for the presence of the virus. Likewise, it will be determined that the rate of active cases per 100,000 inhabitants is the variable that best fits the trends obtained with the quantification of the viral load in wastewater. Conclusion(s): The quantification of SARS- CoV-2 in wastewater as a continuous strategy is an efficient tool to determine the trend of the viral circulation in a delimited geographical area and, combined with genomic surveillance, it can constitute an ideal sentinel surveillance alert on future outbreaks.Copyright © 2022, Sociedad Chilena de Infectologia. All rights reserved.
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Background: Coronavirus Disease 2019 (COVID-19) is a highly contagious disease that resulted in 4533645 deaths until September first, 2021. Multiple Sclerosis (MS) patients receive immunosuppressive drugs. Thus, there is a concern that these drugs will reduce the patient's immune system resistance against COVID19. Objective(s): This study aimed to evaluate the epidemiology of COVID19 and its impact on MS patients in our university hospital in Tehran City, Iran. Material(s) and Method(s): A cross-sectional study was conducted based on hospital-based registry data from May 2020 to March 2021. Among more than 500 registered MS patients in Imam Khomeini Hospital in Tehran City, Iran, referring within our study period, 84 patients reported SARS-COV2 infection. The diagnosis of MS was confirmed by the McDonald criteria. Moreover, the diagnosis of COVID-19 in MS patients was established by the real-time-PCR technique and chest computed tomography. Result(s): Out of 84 MS patients with SARS-COV2 infection, 55(65.5%) were women, and their mean age was 37.48 years. The most commonly used medications by MS patients were Rituximab 20 (26.3%) and Dimethyl Fumarate 14(18.4%). Totally, 9(10.8%) of the patients needed to be hospitalized due to COVID-19, with a mean hospitalization duration of 5.88 days. A total of 1 (1.2%) death was reported. Conclusion(s): Compared to the healthy population, COVID-19 is not more serious in MS patients. Most MS patients with COVID-19 infection were not hospitalized and continued their medication during the infection.Copyright © 2022 The Authors. This is an open access article under the CC-By-NC license. All Rights Reserved.
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Given the rapid spread of coronavirus disease 2019 (COVID-19) globally, test systems are needed for its diagnosis, timely treatment, and introduction of quarantine measures. In the shortest possible time, a diagnostic system based on real-time reverse-transcription polymerase chain reaction to detect the ribonucleic acid of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in nasopharyngeal and oropharyngeal smears was developed and registered. The method determines the nucleocapsid and small-membrane protein genes and the human PGK1 gene, acting as internal control reactions. The nucleotide sequences of SARS-CoV-2 were analyzed, and primers were selected. The conditions for carrying out real-time reverse-transcription polymerase chain reaction and the composition of a set of reagents were set. The diagnostic sensitivity and specificity of the kit were tested on biological samples, with the addition of inactivated SARSCoV-2. The high analytical characteristics of the developed set of reagents were demonstrated, with a sensitivity of at least 103 GE/mL and a specificity of 100%, and no false-positive or false-negative results were recorded. The high specificity of the test system was shown on a representative sample of genetic materials of respiratory viral pathogens. Clinical and laboratory tests of the diagnostic "SARS-CoV-2 test” were conducted in the N.F. Gamalei National Research Center for Epidemiology and Microbiology. A set of reagents for the detection of ribonucleic acid of SARS-CoV-2 through on real-time reverse-transcription polymerase chain reaction for in vitro diagnostics "SARS-CoV-2 test” was registered in the Russian Federation as a medical device (Registration certificate no. RZN 2020/10632, dated 06/03/2020). The article can be used under the CC BY-NC-ND 4.0 license © Authors, 2022.
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In this article, we present a [Formula Omitted]-learning-enabled safe navigation system—S-Nav—that recommends routes in a road network by minimizing traveling through categorically demarcated COVID-19 hotspots. S-Nav takes the source and destination as inputs from the commuters and recommends a safe path for traveling. The S-Nav system dodges hotspots and ensures minimal passage through them in unavoidable situations. This feature of S-Nav reduces the commuter's risk of getting exposed to these contaminated zones and contracting the virus. To achieve this, we formulate the reward function for the reinforcement learning model by imposing zone-based penalties and demonstrate that S-Nav achieves convergence under all conditions. To ensure real-time results, we propose an Internet of Things (IoT)-based architecture by incorporating the cloud and fog computing paradigms. While the cloud is responsible for training on large road networks, the geographically aware fog nodes take the results from the cloud and retrain them based on smaller road networks. Through extensive implementation and experiments, we observe that S-Nav recommends reliable paths in near real time. In contrast to state-of-the-art techniques, S-Nav limits passage through red/orange zones to almost 2% and close to 100% through green zones. However, we observe 18% additional travel distances compared to precarious shortest paths.
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This paper provides a remote access control experiment for students who can't go to the campus because of the COVID-19 pandemic. This paper utilizes the SCADA (supervisory control and data acquisition) using LabView with the Internet of things technology to control the laboratory remotely in real-time. Remote access experiments of a Linear actuator, PID algorithm, Dynamics and Control of Second-order system response, and survey questionnaires were applied and used as an example to show how effective the research study is. The safety of the SCADA system was also considered by using the Virtual Private Network as the primary connection between the student and the server. The remote access laboratory will give a solution to the current problem of the academe for not providing a real-time laboratory equipment experiment. © 2022 IEEE.