Novel coronavirus SARS-CoV-2, designated as COVID-19 by the World Health Organization (WHO) on the February 11, 2020, is one of the highly pathogenic β‐coronaviruses which infects human. Early diagnosis of COVID-19 is the most critical step to treat infection. The diagnostic tools are generally molecular methods, serology and viral culture. Recently CRISPR-based method has been investigated to diagnose and treat coronavirus infection. The emergence of 2019-nCoV during the influenza season, has led to the extensive use of antibiotics and neuraminidase enzyme inhibitors, taken orally and intravenously. Currently, antiviral inhibitors of SARS and MERS spike proteins, neuraminidase inhibitors, anti-inflammatory drugs and EK1 peptide are the available therapeutic options for SARS-CoV-2 infected individuals. In addition, Chloroquine, which was previously used for malarial and autoimmune disease, has shown efficacy in the 2019-nCoV infection treatment. In severe hypoxaemia, a combination of antibiotics, α-interferon, lopinavir and mechanical ventilation can effectively mitigate the symptoms. Comprehensive knowledge on the innate and adaptive immune responses, will make it possible to propose potent antiviral drugs with their effective therapeutic measures for the prevention of viral infection. This therapeutic strategy will help patients worldwide to protect themselves against severe and fatal viral infections, that potentially can evolve and develop drug resistance, and to reduce mortality rates.
Background This study aims to review chest computed tomography (CT) scanning parameters which are utilized to evaluate patients for COVID-19-induced pneumonia. Also, some of radiation dose reduction techniques in CT would be mentioned, because using these techniques or low-dose protocol can decrease the radiation burden on the population. Main body Chest CT scan can play a key diagnostic role in COVID-19 patients. Additionally, it can be useful to monitor imaging changes during treatment. However, CT scan overuse during the COVID-19 pandemic raises concerns about radiation-induced adverse effects, both in patients and healthcare workers. Conclusion By evaluating the CT scanning parameters used in several studies, one can find the necessity for optimizing these parameters. It has been found that chest CT scan taken using low-dose CT protocol is a reliable diagnostic tool to detect COVID-19 pneumonia in daily practice. Moreover, the low-dose chest CT protocol results in a remarkable reduction (up to 89%) in the radiation dose compared to the standard-dose protocol, not lowering diagnostic accuracy of COVID-19-induced pneumonia in CT images. Therefore, its employment in the era of the COVID-19 pandemic is highly recommended.
All of humans and other mammalian species are colonized by some types of microorganisms such as bacteria, archaea, unicellular eukaryotes like fungi and protozoa, multicellular eukaryotes like helminths, and viruses, which in whole are called microbiota. These microorganisms have multiple different types of interaction with each other. A plethora of evidence suggests that they can regulate immune and digestive systems and also play roles in various diseases, such as mental, cardiovascular, metabolic and some skin diseases. In addition, they take-part in some current health problems like diabetes mellitus, obesity, cancers and infections. Viral infection is one of the most common and problematic health care issues, particularly in recent years that pandemics like SARS and COVID-19 caused a lot of financial and physical damage to the world. There are plenty of articles investigating the interaction between microbiota and infectious diseases. We focused on stimulatory to suppressive effects of microbiota on viral infections, hoping to find a solution to overcome this current pandemic. Then we reviewed mechanistically the effects of both microbiota and probiotics on most of the viruses. But unlike previous studies which concentrated on intestinal microbiota and infection, our focus is on respiratory system’s microbiota and respiratory viral infection, bearing in mind that respiratory system is a proper entry site and residence for viruses, and whereby infection, can lead to asymptomatic, mild, self-limiting, severe or even fatal infection. Finally, we overgeneralize the effects of microbiota on COVID-19 infection. In addition, we reviewed the articles about effects of the microbiota on coronaviruses and suggest some new therapeutic measures.
Background: Purpose of this study was to deliver a report of chest CT findings of COVID-19-infected pediatric and adult patients and to make an age-based comparison. A systematic search was conducted in accordance with PRIS MA guidelines to identify relevant studies in the electronic databases of PubMed, Scopus, ProQuest, ScienceDirect, and Web of Sciences from January 1, 2020 to March 27, 2020 using search terms in the titles and abstracts. Based on our inclusion and exclusion criteria, 762 articles were screened. Finally, 15 eligible articles which had adequate data on chest CT findings of COVID-19-infected patients were enrolled in this systematic review. Results: In pediatric patients (15 years old or younger), peripheral distribution was found in 100% of cases, ground glass opacities (GGO) in 55.2%, bilateral involvement in 50%, halo sign in 50%, unilateral involvement in 30%, consolidation in 22.2%, crazy paving pattern in 20%, nodular opacities in 15%, pleural effusion in 4.2%, lymphadenopathy in none, and normal imaging in 20.8% of cases. On the other hand, in adult patients, bilateral involvement was reported in 76.8%, GGO in 68.4%, peripheral distribution in 62.2%, mixed GGO and consolidation in 48.7%, consolidation in 33.7%, crazy paving pattern in 27.7%, mixed central and peripheral distribution in 25.0%, unilateral involvement in 15.2%, nodular opacities in 9.2%, pleural effusion in 5.5%, central distribution of lesions in 5.4%, lymphadenopathy in 2.4%, and normal imaging in 9.8% of cases. Conclusion: According to the findings of this systematic review, children infected with COVID-19 can present with normal or atypical findings (nodular opacities/unilateral involvement) in chest imaging more frequently than adult patients. Therefore, more caution should be taken to avoid misdiagnosis or missed diagnosis in infected children. Besides, clinical and laboratory findings need to be considered more decision-making for pediatric patients with normal or atypical chest CT scan but high suspicion of COVID-19.
Purpose. To investigate the factors contributing to mortality in coronavirus disease 2019 (COVID-19) patients admitted in the intensive care unit (ICU) and design a model to predict the mortality rate. Method. We retrospectively evaluated the medical records and CT images of the ICU-admitted COVID-19 patients who had an on-admission chest CT scan. We analyzed the patients’ demographic, clinical, laboratory, and radiologic findings and compared them between survivors and nonsurvivors. Results. Among the 121 enrolled patients (mean age, 62.2 ± 14.0 years; male, 82 (67.8%)), 41 (33.9%) survived, and the rest succumbed to death. The most frequent radiologic findings were ground-glass opacity (GGO) (71.9%) with peripheral (38.8%) and bilateral (98.3%) involvement, with lower lobes (94.2%) predominancy. The most common additional findings were cardiomegaly (63.6%), parenchymal band (47.9%), and crazy-paving pattern (44.4%). Univariable analysis of radiologic findings showed that cardiomegaly p : 0.04 , pleural effusion p : 0.02 , and pericardial effusion p : 0.03 were significantly more prevalent in nonsurvivors. However, the extension of pulmonary involvement was not significantly different between the two subgroups (11.4 ± 4.1 in survivors vs. 11.9 ± 5.1 in nonsurvivors, p : 0.59 ). Among nonradiologic factors, advanced age p : 0.002 , lower O2 saturation p : 0.01 , diastolic blood pressure p : 0.02 , and hypertension p : 0.03 were more commonly found in nonsurvivors. There was no significant difference between survivors and nonsurvivors in terms of laboratory findings. Three following factors remained significant in the backward logistic regression model: O2 saturation (OR: 0.91 (95% CI: 0.84–0.97), p : 0.006 ), pericardial effusion (6.56 (0.17–59.3), p : 0.09 ), and hypertension (4.11 (1.39–12.2), p : 0.01 ). This model had 78.7% sensitivity, 61.1% specificity, 90.0% positive predictive value, and 75.5% accuracy in predicting in-ICU mortality. Conclusion. A combination of underlying diseases, vital signs, and radiologic factors might have prognostic value for mortality rate prediction in ICU-admitted COVID-19 patients.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.