Novel coronavirus infection

Veselova, Elena; Russkikh, Anastasiia; Каминский, Г. Д.; Lovacheva, Olga; Samoilova, Anastasia; Васильева, И. А.

doi:10.21292/2075-1230-2020-98-4-6-14

Cited by 11 publications

(4 citation statements)

References 46 publications

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“…Выделяют следующие степени тяжести клинических проявлений COVID-19: 1) легкую: у пациентов клинические симптомы отсутствуют либо не выражены, на рентген-и КТ-изображениях нет признаков пневмонии; 2) среднетяжелую: у пациентов имеются клинико-рентгенологические признаки пневмонии без дыхательной недостаточности; 3) тяжелую: у пациентов имеются клинико- 1 рентгенологические признаки острого респираторного дистресс-синдрома (пневмонии с острой дыхательной недостаточностью) 4) критическую: наличие сепсиса, септического (инфекционно-токсического) шока; ДВСсиндрома, тромбозов и тромбоэмболии.…”

Section: клинические формы инфекции и факторы риска неблагоприятного теченияunclassified

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Topical issues of diagnostics, examination and treatment of patients with COVID-19-associated pneumonia in different countries and continents

et al. 2021

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The lack of effective etiotropic methods of treatment and prevention of the new coronavirus infection (COVID-19), which caused the pandemic in 2020, determines the relevance of the review of researches of medicines for etiotropic and pathogenetic therapy. Most patients are diagnosed with pneumonia, the disease is especially difficult in people with concomitant chronic diseases, since COVID-19 leads to their decompensation, which can lead to death. To assess risk factors for mortality, scientists are developing programs to transfer the patient to appropriate treatment in a timely manner. This article analyzes the clinical efficacy of various agents for etiotropic and pathogenetic treatment of a new coronavirus infection based on data from international researches. Etiotropic medicines used at the beginning of the pandemic did not show their effectiveness in reducing the duration of treatment, the development of death, and preventing the transition to the use of mechanical ventilation. There are described researches of vaccines against a new coronavirus infection, developed in the Russian Federation, the USA, Germany and the UK, which showed the greatest efficiency (more than 90%) in preventing COVID-19. The World Health Organization initiated the international clinical research SOLIDARITY, according to which all medicines participating in the trials have little or no effect on overall mortality, the onset of ventilation requirements and the length of hospital stay in hospitalized patients. Now, only systemic glucocorticosteroids have proven effective against severe and critical forms of COVID-19. Thus, effective etiotropic drugs for the treatment of COVID-19 have not been developing, however, an active search for these funds and the development of vaccines to prevent the incidence of coronavirus infection are underway.

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Section: клинические формы инфекции и факторы риска неблагоприятного теченияunclassified

“…-по настоящее время) и SARS-CoV-2 (2019 г.) 1 [1]. Коронавирусная инфекция (COVID- 19), вызвавшая пандемию в 2020 г., обусловлена РНК-вирусом SARS-CoV-2 семейства Coronaviridae, который имеет на 79% идентичный геном с SARS-CoV.…”

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Topical issues of diagnostics, examination and treatment of patients with COVID-19-associated pneumonia in different countries and continents

et al. 2021

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“…The lungs are most severely affected by COVID-19 [3]. To recognize pneumonia caused by various viruses, computed tomography with analysis of the got images using deep learning methods is widely used [4].…”

Section: Introductionmentioning

confidence: 99%

The Use of Convolution Neural Networks to Classify Viral Pneumonia and COVID-19 by Using Chest X-ray Images

Alwan Hasson

2024

Acad. Sci. J.

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The novel coronavirus outbreak reached pandemic status in March-2020. Since then, many countries have collaborated in the fight against COVID-19. The main objective of these governments is the rapid and effective identification of COVID-19-positive patients. While many molecular tests currently exist, not all hospitals have immediate access to these. However, X-rays, which are easily accessible in the majority of hospitals, provide different ways to detect COVID-19. This article discusses the use of neural networks for the classification of radiographic images of patients with pneumonia and COVID-19. Precision, Recall, and F1score were used to select the best resizing parameters and adaptive equalization of the brightness histogram of images, as well as the optimal architecture of the neural network and its hyperparameters. The high values of these classification quality metrics obtained accuracy (97%) for patients with COVID-19, and accuracy (99%) for patients with pneumonia. These results strongly indicate a reliable differentiation of radiographic images. This opens up the possibility of creating a model with good predictive ability without involving ready-made complex models and preliminary training on third-party data.

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“…В конце 2019 г. в Китайской Народной Республике произошла вспышка новой тяжелой респираторно-вирусной инфекции с высокой леталь-ностью, в короткие сроки приобретшей статус мировой пандемии. Болезни присвоено название «COronaVIrus Disease 2019» (COVID-19), а воз-будителю -официальное название SARS-CoV-2 [1,9]. У детей течение COVID-19 отличается от взрослых: реже наблюдаются тяжелые и осложненные проявления, летальные исходы, в большинстве случаев заболевание протекает бессимптомно или с малой клинической симптоматикой, характерной для сезонных респираторно-вирусных инфекций [3,6,8].…”

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The outbreak of the new coronavirus infection in pediatric TB department

Губкина

Петракова

Yukhimenko

et al. 2020

Tuberk. bolezni lëgk.

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The objective: to analyze the course of the new coronavirus infection (COVID-19) in children with active respiratory tuberculosis. Subjects and methods. The article describes results of retrospective analysis of the course of the new coronavirus infection in 25 children (3-12 years old) with active respiratory tuberculosis during the outbreak of COVID-19 in an in-patient TB unit.Results. 24 (96%) persons got infected after the close exposure to the coronavirus infection, and 1 (4%) child didn't get infected. The diagnosis was verified by polymerase chain reaction (detection of RNK of SARS-CoV-2) in 33.3%, by enzyme immunoassay (detection of IgG antibodies to SARS-CoV-2 in 1 month after quarantine removal) in 100%. 58.3% of children with respiratory tuberculosis (14 people) infected with coronavirus infection had minimal respiratory symptoms, that did not differ from signs of other respiratory viral infections; clinical manifestations of the disease were completely absent in 41.7% (10) patients. Coronavirus pneumonia was diagnosed in 4 (16.7%) children who suffered from COVID-19, they had no clinical signs of lower respiratory tract disorders and no body temperature increase; 3 patients had no signs of respiratory viral infection; in all cases, the lung damage detected by computed tomography didn't exceed 10%. In 2 months after the removal of quarantine, no IgG antibodies to SARS-CoV-2 were detected in 2 out of 10 examined children (20.0%), thus there was a chance for re-infection. No mutual aggravating effect of coronavirus infection and tuberculosis was revealed in their combination over the entire observation period (4 months).

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Novel coronavirus infection

Abstract: The article presents the review of 59 publications describing the aspects of etiology, pathogenesis, diagnostics, and treatment of COVID-19 caused by SARS-CoV-2 coronavirus.The authors state that they have no conflict of interests.

Cited by 11 publications

References 46 publications

Topical issues of diagnostics, examination and treatment of patients with COVID-19-associated pneumonia in different countries and continents

Topical issues of diagnostics, examination and treatment of patients with COVID-19-associated pneumonia in different countries and continents

The Use of Convolution Neural Networks to Classify Viral Pneumonia and COVID-19 by Using Chest X-ray Images

The outbreak of the new coronavirus infection in pediatric TB department

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