ABSTRACT
Background: Coronavirus disease 2019 (COVID-19) is a devastating viral pandemic infecting millions of people with a wide range of symptoms from fever to death. It has been suggested that immunocompromised patients are at a higher risk of severe disease, poor clinical outcomes, and mortality. However, these patients' risk factors and COVID-19-related outcomes are not well characterized. Objective(s): We evaluated the COVID-19-related outcomes among immunocompromised patients ranging from solid tumors, hema-tological malignancies, and HIV to autoimmune disease and transplant recipients who received immunosuppressive agents. We also aimed at finding risk factors related to mortality among immunocompromised patients with COVID-19. Method(s): This cross-sectional study was conducted in Khansari Hospital, Iran between March and November 2021. We included immunocompromised patients with nasal swab positive SARS-CoV-2 polymerase chain reaction (PCR) results in the study. Patient outcomes, including hospitalization ward and the mortality rate, were assessed till three months after COVID-19 infection were evaluated in all patients. Moreover, the relation between risk factors and the rate of the mortality rate was analyzed in immuno-compromised patients with COVID-19. Result(s): A total number of 74 immunocompromised patients with solid tumors, hematologic malignancies, autoimmune diseases, acquired immunodeficiencies, and solid-organ transplant recipients were included in the study. Results indicated that the male gender and ICU hospitalization significantly increase the mortality risk. Surprisingly, chemotherapy is associated with a lower risk of mortality. Conclusion(s): Identifying the risk factors can improve the decision-making on cancer patients' management during the COVID-19 infection. A further large cohort of patients would be required to identify risk factors relating to poor clinical outcomes and mortality rates in immunocompromised patients with COVID-19.Copyright © 2023, Author(s).
ABSTRACT
The rapid outbreak of COVID-19 has heightened interest in news about the pandemic. In addition to obtaining real-time developments about COVID-19, people have learned about prevention methods through the news media. Ironically, false COVID-19 news has spread faster than the virus, posing an additional health threat with advice being as dangerous as infection. In this study, we developed a Chinese news article dataset on COVID-19 misinformation, which contained 1266 verified articles from 118 Chinese digital newspaper platforms from January 2020 to January 2021. This dataset uses machine learning methods to detect false news in the Chinese language. Because automated classification methods, combined with human computation-based approaches, are effective for combating digital misinformation, we applied and evaluated a collaborative intelligence approach that leverages human fact-checking skills with feedback on news stories using four criteria: source, author, message, and spelling. The results show that reliable human feedback can help detect false news with high accuracy. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Purpose: Coronavirus disease-2019 (COVID-19) is becoming a crucial health problem worldwide. Continued and high-speed mutations of this virus result in the appearance of new manifestations, making the control of this disease difficult. It has been shown that well-nourished patients have strong immune systems who mostly have short-term hospitalization compared to others. The purpose of this study is to review the major nutrients involved in the immune system reinforcement and to explain nutritional aspects during the recovery of COVID-19. Design/methodology/approach: In this review paper, the mechanistic role of nutrients in boosting the immune system and the nutritional aspects during the recovery of COVID-19 patients were discussed. Papers indexed in scientific databases were searched using antioxidants, COVID-19, inflammation, immune system, macronutrient, micronutrient and probiotic as keywords from 2000 to 2022. Findings: Because of the adverse effects of drugs like thrombosis, pulmonary embolism and hypercholesterolemia, a balanced diet with enough concentrations of energy and macronutrients could increase the patient's durability. The inflammatory cytokines in a vicious cycle delay patients’ rehabilitation. The main mechanistic roles of micronutrients are attributed to the downregulation of virus replication and are involved in energy homeostasis. Dysbiosis is defined as another disturbance among COVID-19 patients, and supplementation with beneficial strains of probiotics helps to exert anti-inflammatory effects in this regard. Being on a well-planned diet with anti-inflammatory properties could reverse cytokine storms as the major feature of COVID-19. Future studies are needed to determine the safe and effective dose of dietary factors to control the COVID-19 patients. Originality/value: Being on a well-planned diet with anti-inflammatory properties could reverse cytokine storms as the major feature of COVID-19. Future studies are needed to determine the safe and effective dose of dietary factors to control the COVID-19 patients. © 2022, Emerald Publishing Limited.
ABSTRACT
Spread of online misinformation is an ubiquitous problem especially in the context of social media. In addition to the impact on global health caused by the current COVID-19 pandemic, the spread of related misinformation poses an additional health threat. Detecting and controlling the spread of misinformation using algorithmic methods is a challenging task. Relying on human fact-checking experts is the most reliable approach, however, it does not scale with the volume and speed with which digital misinformation is being produced and disseminated. In this paper, we present the SAMS Human-in-the-loop (SAMS-HITL) approach to combat the detection and the spread of digital misinformation. SAMS-HITL leverages the fact-checking skills of humans by providing feedback on news stories about the source, author, message, and spelling. The SAMS features are jointly integrated into a machine learning pipeline for detecting misinformation. First results indicate that SAMS features have a marked impact on the classification as it improves accuracy by up to 7.1%. The SAMS-HITL approach goes one step further than the traditional human-in-the-loop models in that it helps raising awareness about digital misinformation by allowing users to become self fact-checkers. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org)