ABSTRACT
The novel coronavirus, or COVID-19, emerged from Wuhan, Hubei Province, China, and has recently spread all over the world. During the COVID-19 pandemic, healthcare workers struggle against this microscopic enemy due to their job responsibilities, thus leading to be infected in some of them, even some of them are died in line of duty. As of 2 February 2021, 37 million cases of COVID-19 among health workers from 183 countries and regions were reported to the World Health Organization (WHO), a figure that represents 36% of the total cases globally. The median age of these cases was 42 years and 68% were women. On May 24, 2021, the World Health Organization (WHO) stated that at least 115,000 healthcare workers have died due to COVID-19 worldwide since the pandemic began last year. It is important to pay attention to the situation related to COVID-19 infection for medical staff and their preventive measures. This paper reviews the literature on all available information about the situation and preventive measures (The primary prevention of COVID-19 is to break the chain of transmission from infected to healthy people, secondary preventive measures comprise the use of health screening and recognition activities to ascertain those infected with COVID-19 and tertiary prevention consists of treatment and proper rehabilitation) related to COVID-19 infection for medical staff.
ABSTRACT
This study aims to provide a feasibility bask for image processing for automatic throat swab robot sampling. For target segmentation and identification in the oral environment, we use a robust instance segmentation algorithm Mask R-CNN. In order to solve the insufficiency of the data used, we use data augmentation methods based on the original data to increase the available effective data. Experiments have proved that good results have been achieved for the segmentation of the throat swab and the posterior pharyngeal wall.
ABSTRACT
Objective: To investigate the clinical features and outcome of treatment for novel coronavirus pneumonia. Methods: Literature on novel coronavirus pneumonia was retrieved from PubMed and EMBASE databases. The relevant data was extracted and a meta-analysis was performed using StatsDirect statistical software V.2.8.0 to calculate the combined odds ratio. Results: Seven studies were included, consisting of 1594 cases. The meta-analysis result showed that the most common clinical symptoms of the novel coronavirus pneumonia were fever (91.6%) and cough (64.5%), followed by dyspnea (32.8%) and sputum (28.1%). Headache (10.5%), sore throat (11.2%), hemoptysis (3.2%), diarrhea (6.6%) and the other symptoms were relatively rare. Aspartate aminotransferase (29%), alanine transaminase (22.7%), and total bilirubin (11.7%) levels were elevated, except for serum albumin levels (80.4%). The common therapeutic agents used were antibiotics (87.7%), antiviral drugs (75.5%), and glucocorticoids (26.6%), while antifungal agents (7.7%) were used in few. Mechanical ventilation (13.4%), extracorporeal membrane oxygenation (1.9%), and continuous renal replacement therapy (3.8%) were used in severe cases. The rate of mortality in hospital was 7.7%, respectively. Heterogeneity between studies was significant; however, subgroup and sensitivity analysis had failed to identify clear sources of heterogeneity. Conclusion: Fever, cough and liver dysfunction are the main clinical manifestations of this disease and the mortality rate is low.