Analysis of social and psychological factors influencing the treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019.

Objective To explore the sociodemographic and psychological factors influencing the continuity of treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019 (COVID-19). Methods A total of 277 patients with chronic kidney disease who were admitted to Department of Nephrology, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. 2020 to Mar. 2021 were enrolled and divided into 3 groups: non-dialysis group (n=102), hemodialysis (HD) group (n=108), and peritoneal dialysis (PD) group (n=67). All patients were investigated by online and offline questionnaires, including self-designed basic situation questionnaire, self-rating anxiety scale (SAS), and self-rating depression scale (SDS). The general sociodemographic data, anxiety and depression of the 3 groups were compared, and the influence of sociodemographic and psychological factors on the interruption or delay of treatment was analyzed by binary logistic regression model. Results There were significant differences in age distribution, marital status, occupation, medical insurance type, caregiver type, whether there was an urgent need for hospitalization and whether treatment was delayed or interrupted among the 3 groups (all P0.05). The average SAS score of 65 PD patients was 38.15+/-15.83, including 53 (81.5%) patients without anxiety, 7 (10.8%) patients with mild anxiety, and 5 (7.7%) patients with moderate to severe anxiety. The average SAS score of 104 patients in the HD group was 36.86+/-14.03, including 81 (77.9%) patients without anxiety, 18 (17.3%) patients with mild anxiety, and 5 (4.8%) patients with moderate to severe anxiety. There were no significant differences in the mean score of SAS or anxiety severity grading between the 2 groups (both P0.05). The mean SDS scores of 65 PD patients were 53.42+/-13.30, including 22 (33.8%) patients without depression, 21 (32.3%) patients with mild depression, and 22 (33.8%) patients with moderate to severe depression. The mean SDS scores of 104 patients in the HD group were 50.79+/-10.76, including 36 (34.6%) patients without depression, 56 (53.8%) patients with mild depression, and 12 (11.6%) patients with moderate to severe depression. There were no significant differences in mean SDS scores or depression severity grading between the 2 groups (both P0.05). The results of intra-group comparison showed that the incidence and severity of depression were higher than those of anxiety in both groups. Multivariate binary logistic regression analysis showed that high school education level (odds ratio OR=5.618, 95% confidence interval CI) 2.136-14.776, P0.01), and unmarried (OR=6.916, 95% CI 1.441-33.185, P=0.016), divorced (OR= 5.588, 95% CI 1.442-21.664, P=0.013), urgent need for hospitalization (OR=8.655, 95% CI 3.847-19.476, P0.01) could positively promote the continuity of treatment in maintenance dialysis patients under the regular epidemic prevention and control of COVID-19. In the non-dialysis group, no sociodemographic and psychological factors were found to be associated with the interruption or delay of treatment (P0.05). Conclusion Education, marital status, and urgent need for hospitalization are correlated with the continuity of treatment in patients with chronic kidney disease on maintenance dialysis.Copyright © 2022, Second Military Medical University Press. All rights reserved.

Analysis of social and psychological factors influencing the treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019

Objective To explore the sociodemographic and psychological factors influencing the continuity of treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019 (COVID-19). Methods A total of 277 patients with chronic kidney disease who were admitted to Department of Nephrology, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. 2020 to Mar. 2021 were enrolled and divided into 3 groups: non-dialysis group (n=102), hemodialysis (HD) group (n=108), and peritoneal dialysis (PD) group (n=67). All patients were investigated by online and offline questionnaires, including self-designed basic situation questionnaire, self-rating anxiety scale (SAS), and self-rating depression scale (SDS). The general sociodemographic data, anxiety and depression of the 3 groups were compared, and the influence of sociodemographic and psychological factors on the interruption or delay of treatment was analyzed by binary logistic regression model. Results There were significant differences in age distribution, marital status, occupation, medical insurance type, caregiver type, whether there was an urgent need for hospitalization and whether treatment was delayed or interrupted among the 3 groups (all P<0.05). The average SAS score of 65 PD patients was 38.15+/-15.83, including 53 (81.5%) patients without anxiety, 7 (10.8%) patients with mild anxiety, and 5 (7.7%) patients with moderate to severe anxiety. The average SAS score of 104 patients in the HD group was 36.86+/-14.03, including 81 (77.9%) patients without anxiety, 18 (17.3%) patients with mild anxiety, and 5 (4.8%) patients with moderate to severe anxiety. There were no significant differences in the mean score of SAS or anxiety severity grading between the 2 groups (both P>0.05). The mean SDS scores of 65 PD patients were 53.42+/-13.30, including 22 (33.8%) patients without depression, 21 (32.3%) patients with mild depression, and 22 (33.8%) patients with moderate to severe depression. The mean SDS scores of 104 patients in the HD group were 50.79+/-10.76, including 36 (34.6%) patients without depression, 56 (53.8%) patients with mild depression, and 12 (11.6%) patients with moderate to severe depression. There were no significant differences in mean SDS scores or depression severity grading between the 2 groups (both P>0.05). The results of intra-group comparison showed that the incidence and severity of depression were higher than those of anxiety in both groups. Multivariate binary logistic regression analysis showed that high school education level (odds ratio [OR]=5.618, 95% confidence interval [CI]) 2.136-14.776, P<0.01), and unmarried (OR=6.916, 95% CI 1.441-33.185, P=0.016), divorced (OR= 5.588, 95% CI 1.442-21.664, P=0.013), urgent need for hospitalization (OR=8.655, 95% CI 3.847-19.476, P<0.01) could positively promote the continuity of treatment in maintenance dialysis patients under the regular epidemic prevention and control of COVID-19. In the non-dialysis group, no sociodemographic and psychological factors were found to be associated with the interruption or delay of treatment (P>0.05). Conclusion Education, marital status, and urgent need for hospitalization are correlated with the continuity of treatment in patients with chronic kidney disease on maintenance dialysis.Copyright © 2022, Second Military Medical University Press. All rights reserved.

An Improved Lightweight YOLOv5 Model Based on Attention Mechanism for Face Mask Detection

Coronavirus 2019 has brought severe challenges to social stability and public health worldwide. One effective way of curbing the epidemic is to require people to wear masks in public places and monitor their mask-wearing states by suitable automatic detectors. However, existing models struggle to simultaneously achieve the requirements of both high precision and real-time performance. To solve this problem, we propose an improved lightweight face mask detector based on YOLOv5, which can achieve an excellent balance of precision and speed. Firstly, a novel backbone ShuffleCANet that combines ShuffleNetV2 network with Coordinate Attention mechanism is proposed as the backbone. Afterward, an efficient path aggression network BiFPN is applied as the feature fusion neck. Furthermore, the localization loss is replaced with alpha-CIoU in model training phase to obtain higher-quality anchors. Some valuable strategies such as data augmentation, adaptive image scaling, and anchor cluster operation are also utilized. Experimental results on AIZOO face mask dataset show the superiority of the proposed model. Compared with the original YOLOv5, the proposed model increases the inference speed by 28.3% while still improving the precision by 0.58%. It achieves the best mean average precision of 95.2% compared with other seven existing models, which is 4.4% higher than the baseline.

A GARCH Framework Analysis of COVID-19 Impacts on SMEs Using Chinese GEM Index

Stock market return analysis and forecasting are an important topic in econometric finance research. Since the traditional ARIMA models do not consider the variation of volatility, their prediction accuracy is not satisfactory to represent highly volatile periods of any stock market. The GARCH model family resolves the heteroskedasticity of a time series, and hence, it performs better in periods of high volatility. This paper explores the impact of the COVID-19 epidemic on Chinese small- and medium-sized enterprises (SMEs) using a GARCH model for Business as usual (BAU) simulation. We use the Chinese Growth Enterprise Market (GEM) stock index to represent the economic situation of SMEs during the COVID-19 period. Then, we extract, analyze, and predict changes in GEM stock volatility, explore the impact on and recovery status of SMEs, and predict their future trends. For BAU simulation, we first preprocess the GEM stock index between 2018 and 2020 and determine the order of autocorrelation and lags of the data to build the mean model. An ARCH effect test on the residual term of the mean equation was found to be significant and help to decide the order of the GARCH framework. Using the model, a BAU simulation was created and compared statistically with the actual GEM index during 2020. The comparison successfully demonstrated that the GEM index has increased volatility during the pandemic, which is in line with our prior hypothesis.

Design of the service robot applied to undergraduate laboratory of pharmacy major

During the COVID-19 outbreak, service robots have provided good service for teachers and students in universities. In order to improve the safety and convenience of pharmaceutical undergraduate laboratory, a service robot for pharmaceutical undergraduate teaching laboratory was designed from the aspects of path planning, positioning and navigation, human-computer interaction etc., which can solve practical problems such as epidemic prevention and control, laboratory safety etc.

The Navigation Design of Mobile Robot in the Man-Machine Environment for Service Assist

The global novel coronavirus COVID-19 has spread far beyond any previous cases in the world, due to its high infect ability, robots are in high demand all over the world, which can help hospital services, protect the health and safety of front-line medical workers. This paper investigates the use of an autonomous service robot in an indoor complex environment, such as a hospital ward or a retirement home. The research is based on the method of fusing lidar and image information to identify, locate, and track the human body in the indoor environment. Use lidar SLAM to obtain the pose of pedestrians in the environment, and incorporate the predicted pedestrian trajectory into the planning constraints of the navigation algorithm to ensure that human behavior intentions are respected, and verify the humanized navigation of the mobile robot in the human-machine inclusive indoor environment through online simulation and experimental platform. The main advantages of the design of this mobile robot are that it can improve the friendliness of humanmachine integration in order to do better serves in public environments such as medical institutions.