ABSTRACT
Aims: COVID-19 has affected a worldwide population, causing more than a million deaths from the end of 2019 until now;so the aim of this study was to determine the symptoms of COVID-19 in the Iranian population through a teleconsultation-based service to better deal with it. Instrument & Methods: This study was a cross-sectional study that included 12125 individuals calling for COVID-19 screening and consultation from 2 March 2020 to 19 April 2020 with the census method. A telephone number was assigned for consultation with more than 70 nurses responding to first-level questions and more than 30 medical doctors responding to second-level questions. For statistical analysis, a chi-squared test and univariate logistic regression with SPSS 25 were used. Finding: Cough was the most common complaint (41.3%), followed by shortness of breath (32.8%), and fever (31.5%). Confusion was the least common complaint (1.6%). Binary logistic regression revealed that men were at a higher risk of COVID-19 compared to women (OR:1.31, 95% CI 1.10-1.55, p=0.002). In addition, older age was a risk factor for COVID-19 (OR:1.02, 95% CI 1.02-1.03, p<0.001). Also, significant positive correlations were found between fever, chills, sore throat, shortness of breath, cough, body ache, and gastrointestinal symptoms with COVID-19 even after adjustment for gender and age. Conclusion: Fever, cough, and shortness of breath were the most common complaints in individuals calling for COVID-19 teleconsultation. It’s suggested that in times of crisis, such as the Covid-19 pandemic, remote sensing can be done to raise public awareness and break the transmission chain. © 2022, Tarbiat Modares University. All rights reserved.
ABSTRACT
Density functional theory (DFT) quantum calculations were performed to investigate attachment of favipiravir (FAV) to a conical nanocarbon (FCN) for assessments of the drug delivery approach. The continuous negative impacts of COVID-19 made an urgent of performing further investigations on developing its medication processes, in which FAV has been one of proposed drugs of medication of COVID-19. To this aim, the attachment of FAV to FCN was investigated in this work for showing benefits of such FAV@FCN complex formations. The apex of conical nanocarbon was doped by an iron atom to make an active site of interactions, in which three configurations of FAV versus FCN were obtained with different levels of strength and electronic features. In this regard, details of interactions were examined by the quantum theory of atoms in molecules (QTAIM). As a consequence, the investigated models of FAV@FCN could be proposed for drug delivery purposes.
ABSTRACT
OBJECTIVE: This study sought to determine how various stressors related to COVID-19 impacted the patient experience during fertility treatment. MATERIALS AND METHODS: An anonymous survey was distributed to patients at a private fertility clinic via the patient portal. Survey questions investigated patient demographics and feelings of anxiety regarding COVID-19 related stressors. Baseline levels of anxiety were measured by GAD-7, a 7-question generalized anxiety disorder scale. Patient confidence in their fertility treatment and potential changes to their treatment plan due to COVID-19 were assessed. Responses ranged from “not at all” to “all of the time”. Survey responses were analyzed at two different points, on Feb 5th with 290 participants and April 11th with 647 to determine average response and response frequencies. RESULTS: Of the initial 290 participants, 89% were women with an average age of 33.8. 58.9% reported pursuing fertility treatment for at least a year. The average GAD-7 Anxiety Severity Score for this cohort was 5.79, indicating an overall feeling of mild anxiety among respondents. 59% of respondents reported COVID-19 health concerns as one of their causes of stress, but only 29% reported considering or ultimately delaying treatment due to the pandemic. The data was again analyzed with 647 participants, of whom 80% were women with an average age of 34.5. 47.8% reported pursuing fertility treatment for at least a year. The average GAD-7 Anxiety Severity Score was 5.01 for this cohort, indicating a reduced overall feeling of mild anxiety. 52% of respondents reported COVID-19 health concerns as one of their causes of stress, but only 17% reported considering or deciding to delay treatment due to the pandemic. CONCLUSIONS: Individuals struggling to conceive often report feelings of depression and anxiety. Over the past year, the ongoing COVID-19 pandemic has been shown to cause increased stress, anxiety, and feelings of depression across almost all populations. For those already experiencing heightened levels of stress and anxiety prior to the pandemic, the effect of increased stress and worry may have detrimental effects on health outcomes. While the cause-and-effect relationship between stress and infertility is still unclear, it is important to consider how the COVID-19 pandemic leads to increased distress among infertility patients and how this may impact perceived treatment outcomes. In comparing results between data collection on Feb. 5th and April 11th, it appears that patients may be experiencing a reduction in stress regarding COVID-19. As the pandemic continues to evolve in terms of vaccine, treatment, and spread mitigation plans, patients continue to be resilient in adapting to COVID-19. Being aware of the increased levels of stress and anxiety experienced by patients during the ongoing COVID-19 crisis can help healthcare providers alleviate some of these worries. IMPACT STATEMENT: Various stressors, particularly during COVID-19 may impact a patient's experience in their fertility treatment, allowing healthcare providers an opportunity to help mitigate these during care.
ABSTRACT
The discovery paradigm of drugs is rapidly growing due to advances in machine learning (ML) and artificial intelligence (AI). This review covers myriad faces of AI and ML in drug design. There is a plethora of AI algorithms, the most common of which are summarized in this review. In addition, AI is fraught with challenges that are highlighted along with plausible solutions to them. Examples are provided to illustrate the use of AI and ML in drug discovery and in predicting drug properties such as binding affinities and interactions, solubility, toxicology, blood-brain barrier permeability and chemical properties. The review also includes examples depicting the implementation of AI and ML in tackling intractable diseases such as COVID-19, cancer and Alzheimer's disease. Ethical considerations and future perspectives of AI are also covered in this review.
ABSTRACT
Background: The global pandemic of coronavirus has resulted in it causing several respiratory diseases. The mild common cold like illness is one of the major symptoms that represents the clinical presentation of the respiratory infection. Some patients can be asymptomatic while some might have characteristic symptoms in the form of coughs, dyspnoea, and fever. Mostly it affects people aged between 30 to 79 years. Major risk factors are people residing or travelling in the areas where risk of transmission is quite high, old age, and presence of comorbidities. The origin of the virus was linked to the Southern China's Huanan wet market in Huanan. The pathophysiology has not yet been understood properly but the exudative diffuse alveolar is considered as the major reason behind the deaths due to respiratory failure. In order to control the spread there are four different ways currently: quarantine the contact for at least 14 days, screening of travellers, drive-through screening centres, and temperature screening. Isolation, infection management, and symptom management can be the most useful therapeutic approaches. Methodology: During this research, the systematic review has been done by referring to several studies that showed the data related to the diagnostic and therapeutic approach against Covid-19. During the research it has been-ensured that only the data from thighly qualified authors was used to determine the effective diagnostic and therapeutic options of Covid-19. The inclusion criteria were articles available in English language, the most recent and highly rated studies, and articles having statistics. The exclusion criteria were data which is available without clear statistics, articles other than those in the English language, data of high risk and low quality, and the data not able to provide the basic diagnostic and therapeutic options of Covid-19. It has been ensured that the quality of data should be maintained in order to establish quality research. Discussion: Covid-19 diagnostic options are oral and nasal PCR, rapid diagnostic test, serologic test, plain X-rays, Magnetic resonance imaging (MRI), CT scanning, ultrasonography, and nuclear scanning. The therapeutic options are pharmacological drugs (like chloroquine, hydroxychloroquine, corticosteroids, sirolimus, tocilizumab), airway assistance ventilation, and vaccination. Conclusion: Covid-19 is on the verge of constant increase and is impacting many people around the globe. Currently, there is no proper treatment for covid-19 as a result of which everyday preventive actions and vaccination are the best things that an individual can do in order to prevent the spread of covid-19.