ABSTRACT
Background: The 2019 novel coronavirus (COVID-19) global pandemic has greatly changed the mode of hospital admissions. This study summarized and analyzed the incidence of severe diarrhea and anastomotic leakage during different periods for colorectal cancer surgery. Methods: From January 2017 to September 2020, 2,619 colorectal operations were performed in Peking Union Medical College Hospital. In contrast with previous years, enhanced hand hygiene training, more frequent ventilation of the wards, and separate bed treatments for patients were implemented in 2020. Data on incidence of severe diarrhea and anastomotic leakage were retrieved and collected. Results: The number of cases of severe diarrhea after colorectal surgery was 32 (4.60%), 24 (3.33%), 32 (3.83%), and 11 (2.99%) in 2017, 2018, 2019, and 2020 respectively, while the incidence of anastomotic leakage was 3.30% (23/696), 3.75% (27/720), 2.87% (24/835), and 2.17% (8/368), respectively. There was no significant difference in the incidence of postoperative severe diarrhea or anastomotic leakage across the various years. Conclusions: The number of colorectal surgeries in 2020 was significantly decreased due to the COVID-19 pandemic. Among the different years, no difference was observed regarding the incidence of postoperative flora disorder or anastomosis leakage. Enhanced hygiene measures during the COVID-19 epidemic partially contributed to the decrease of severe diarrhea and anastomotic leakage.
ABSTRACT
Under the dispute between China and the United States, the international field of public opinion is dominated by increasing tensions, and the network rumors triggered by the COVID-19 epidemic are intensifying. In view of the above-mentioned context, this paper focuses on the development and the evolution process of public opinions. Since the evolution of public opinion is often accompanied by the spread and diffusion of information, this paper combines the process of information diffusion with the development process of polarization behavior, and brings in the dynamic network and the timeliness factor of public opinion dissemination, so as to better explore the polarization process of public opinion under the dynamic network. Then, this paper focuses on the analysis of the parameters of the model and through the dynamic adjustment of parameters, finding out the main factors that affect the trend and development of network public opinion. In addition, this paper introduces an actual case, and takes the actual case data as the support to demonstrate the reliability and practical application value of the model. Finally, based on the simulation results and analysis of actual cases, this paper puts forward the corresponding preventive measures to alleviate the polarization behavior of the group.