Bermanrichards5629

A significant relationship was found between the observance of patients' rights and their marital status, health insurance, and education level (P less then 0.05). This study showed that the observance of the COVID-19 patients' rights has not been affected by the social agitation caused by this disease.In this paper, we reflect on the COVID-19 pandemic based on medical philosophy. A critical examination of the Corona crisis uncovers that in order to understand and explain the unpreparedness of the health systems, we need a new conceptual framework. This helps us to look at this phenomenon in a new way, address new problems, and come up with creative solutions. Our proposal is that "health lag" is a concept that could help frame and explain this unpreparedness and unreadiness. The term "health lag" refers to the failure of health systems to keep up with clinical medicine. In other words, health issues in most situations fall behind clinical medicine, leading to social, cultural, and economic problems. Mitoquinone In the first step to define health lag, we have to explain the distinction between clinical medicine and health and address the role of individual health, public health, and epidemic in this dichotomy. Thereafter, the reasons behind health lag will be analyzed in three levels theoretical, practical, and institutional. In the third step, we will point out the most important consequences of health lag the medicalization of health, the inconsistency of biopolitics, inadequate ethical frameworks, and public sphere vulnerabilities. Finally, we try to come up with a set of recommendations based on this philosophical-conceptual analysis.Maintaining confidentiality, both in national and international codes of ethics, is considered an important principle in healthcare and the medical profession for both patients and physicians. This case-report article focused on a real case. Based on the request of the Iranian Blood Transfusion Organization (IBTO) for plasma donation from recovered COVID-19 patients, we asked the names and personal information of those patients from hospitals affiliated with Iran University of Medical Sciences (IUMS) and arranged for the subjects to be referred to the Medical Ethics Department of IUMS for consultation during the COVID-19 pandemic. Various ethical and legal aspects of this case were discussed in a special meeting, and practical solutions were then provided considering the limits of confidentiality and conditions for ethical access to patients' information during a pandemic. Since plasma therapy is not a definitive cure for COVID-19 and considering the ethical and legal points presented in this article, it is not recommended to announce the names of patients in the early stages. Given the potential impacts of the procedure and the possibility of patients being cured, however, their consent should be obtained in different situations and, if necessary, providing information to patients or educating them should be considered.Exposing medical students to real-world situations and clinical practice experiences during their education years can help them build their professional value frameworks. The COVID-19 pandemic is one of the most challenging conditions that medical students have experienced; however, this pandemic have provided value-rich opportunities assisting in development and enhancement of their professional identity. This commentary aimed to emphasize the importance of medical students' exposure to clinical practice during the pandemic and the potential that such encounters provide for internalizing values.Nurses face several challenges in providing care for patients with coronavirus disease in 2019 (COVID-19). The study aimed to explain the nurses' perception of ethical challenges in this regard. The qualitative study was carried out using a content analysis method. Individual and semi-structured interviews were conducted with 24 nurses. Inductive content analysis was used to categorize the data. Nurses' narratives indicated that ethical challenges in caring for patients with COVID-19 included threats to professional values and the absence of a holistic COVID-19 care approach. The first category was subcategorized into the risk of declining quality of patient care and a stigmatized public image about COVID-19 care. The second category was divided into poor spiritual care, poor compassionate care, and lack of family-centered care. Health care managers must develop protocols for nurses that address these issues to alleviate the ethical challenges of COVID-19 care.The world is facing the COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Likewise, other viruses of the Coronaviridae family were responsible for causing epidemics earlier. To tackle these viruses, there is a lack of approved antiviral drugs. Therefore, we have developed robust computational methods to predict the repurposed drugs using machine learning techniques namely Support Vector Machine, Random Forest, k-Nearest Neighbour, Artificial Neural Network, and Deep Learning. We used the experimentally validated drugs/chemicals with anticorona activity (IC50/EC50) from 'DrugRepV' repository. The unique entries of SARS-CoV-2 (142), SARS (221), MERS (123), and overall Coronaviruses (414) were subdivided into the training/testing and independent validation datasets, followed by the extraction of chemical/structural descriptors and fingerprints (17968). The highly relevant features were filtered using the recursive feature selection algorithm. The selected chemical descriptors were used to develop prediction models with Pearson's correlation coefficients ranging from 0.60 to 0.90 on training/testing. The robustness of the predictive models was further ensured using external independent validation datasets, decoy datasets, applicability domain, and chemical analyses. The developed models were used to predict promising repurposed drug candidates against coronaviruses after scanning the DrugBank. Top predicted molecules for SARS-CoV-2 were further validated by molecular docking against the spike protein complex with ACE receptor. We found potential repurposed drugs namely Verteporfin, Alatrofloxacin, Metergoline, Rescinnamine, Leuprolide, and Telotristat ethyl with high binding affinity. These 'anticorona' computational models would assist in antiviral drug discovery against SARS-CoV-2 and other Coronaviruses.