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Purpose: To investigate mental health and self-management in glaucoma patients during the COVID-19 pandemic in China and to describe the correlation between anxiety, depression, glaucoma, and self-management., Methods: This cross-sectional study included glaucoma patients who enrolled in the case management platform and completed an online survey. The survey included the Generalized Anxiety Disorder (GAD-7), Patient Health Questionnaire (PHQ-9), and Glaucoma Self-Management Questionnaire (GSMQ)., Results: Among 109 glaucoma patients enrolled in this study, the proportions of patients suffering from depression and anxiety during the COVID-19 pandemic were 26.6% and 20.2%, respectively. A statistical association was found between depression and self-management behaviour in these glaucoma patients (r = -0.247, P = 0.010). The self-management scores in patients less than 35 years were lower than those in patients aged 35-60 years (P = 0.046). The scores of body function promotion in men were lower than those in women (P = 0.048). Patients with primary school education and below had lower scores in the medical management of disease than those with either middle school education (P = 0.032) or community college education or higher (P = 0.022)., Conclusion: A high proportion of anxiety and depression was found in glaucoma patients during the COVID-19 pandemic. Better self-management behaviour was associated with stronger mental health regulation. It is important to help glaucoma patients improve their self-management behaviours, especially for young men with low educational levels., (© 2022. The Author(s).)

Background: Patients with severe coronavirus disease 2019 (COVID-19) who develop acute kidney injury (AKI) in the intensive care unit (ICU) have extremely high rates of mortality. This study evaluated the prognostic impact of AKI duration on in-hospital mortality in elder patients., Methods: We performed a retrospective study of 126 patients with confirmed COVID-19 with severe or critical disease who treated in the ICU from February 4, 2020, to April 16, 2020. AKI was defined according to the Kidney Disease Improving Global Outcomes serum creatinine (Scr) criteria. AKI patients were divided into transient AKI and persistent AKI groups based on whether Scr level returned to baseline within 48 h post-AKI., Results: In total, 107 patients were included in the final analysis. The mean age was 70 (64-78) years, and 69 (64.5%) patients were men. AKI occurred in 48 (44.9%) during their ICU stay. Of these, 11 (22.9%) had transient AKI, and 37 (77.9%) had persistent AKI. In-hospital mortality was 18.6% ( n = 11) for patients without AKI, 72.7% ( n = 8) for patients with transient AKI, and 86.5% ( n = 32) for patients with persistent AKI ( P < 0.001). Kaplan-Meier curve analysis revealed that patients with both transient AKI and persistent AKI had significantly higher death rates than those without AKI (log-rank P < 0.001). Multivariate Cox regression analysis revealed that transient and persistent AKI were an important risk factor for in-hospital mortality in older patients with severe COVID-19 even after adjustment for variables ( hazard   ratio  [ HR ] = 2.582; 95% CI: 1.025-6.505; P = 0.044; and HR = 6.974; 95% CI: 3.334-14.588; P < 0.001)., Conclusions: AKI duration can be an important predictive parameter in elder patients suffering from COVID-19 and are admitted to ICU. Among these patients, those exhibiting persistent AKI have a lower in-hospital survival rate than those with transient AKI, emphasizing the importance of identifying an appropriate treatment window for early intervention., Competing Interests: The authors declare that they have no competing interests., (Copyright © 2022 Yue Cai et al.)

We conducted a randomized, open-label, parallel-controlled, multicenter trial on the use of Shuanghuanglian (SHL), a traditional Chinese patent medicine, in treating cases of COVID-19. A total of 176 patients received SHL by three doses (56 in low dose, 61 in middle dose, and 59 in high dose) in addition to standard care. The control group was composed of 59 patients who received standard therapy alone. Treatment with SHL was not associated with a difference from standard care in the time to disease recovery. Patients with 14-day SHL treatment had significantly higher rate in negative conversion of SARS-CoV-2 in nucleic acid swab tests than the patients from the control group (93.4% vs. 73.9%, P = 0.006). Analysis of chest computed tomography images showed that treatment with high-dose SHL significantly promoted absorption of inflammatory focus of pneumonia, which was evaluated by density reduction of inflammatory focus from baseline, at day 7 (mean difference (95% CI), -46.39 (-86.83 to -5.94) HU; P = 0.025) and day 14 (mean difference (95% CI), -74.21 (-133.35 to -15.08) HU; P = 0.014). No serious adverse events occurred in the SHL groups. This study illustrated that SHL in combination with standard care was safe and partially effective for the treatment of COVID-19., (© 2021. Higher Education Press.)

The coronavirus disease 2019 (COVID-19) spreads and rages around the world and threatens human life. It is disappointing that there are no specific drugs until now. The combination of traditional Chinese medicine (TCM) and western medication seems to be the current more effective treatment strategy for COVID-19 patients in China. In this review, we mainly discussed the relationship between COVID-19 and gut microbiota (GM), as well as the possible impact of TCM combined with western medication on GM in the treatment of COVID-19 patients, aiming to provide references for the possible role of GM in TCM against COVID-19. The available data suggest that GM dysbiosis did occur in COVID-19 patients, and the intervention of GM could ameliorate the clinical condition of COVID-19 patients. In addition, TCMs (e.g., Jinhua Qinggan granule, Lianhua Qingwen capsule, Qingfei Paidu decoction, Shufeng Jiedu capsule, Qingjin Jianghuo decoction, Toujie Quwen granules, and MaxingShigan) have been proven to be safe and effective for the treatment of COVID-19 in Chinese clinic. Among them, Ephedra sinica , Glycyrrhiza uralensis , Bupleurum chinense , Lonicera japonica , Scutellaria baicalensi , and Astragalus membranaceus are common herbs and have a certain regulation on GM, immunity, and angiotensin converting enzyme 2 (ACE2). Notably, Qingfei Paidu decoction and MaxingShigan have been demonstrated to modulate GM. Finally, the hypothesis of GM-mediated TCM treatment of COVID-19 is proposed, and more clinical trials and basic experiments need to be initiated to confirm this hypothesis.

Objective: In December 2019, coronavirus disease 2019 (COVID-19) occurred in Wuhan, China. Online fever clinics were developed by hospitals, largely relieving the hospital's burden. Online fever clinics could help people stay out of crowded hospitals and prevent the risk of cross infections. The objective of our study was to describe the patient characteristics of an online fever clinic and explore the most important concerns and question of online patients.Materials and Methods: Our study extracted data from fever clinic records in medical information systems from January 24 to February 18, 2020 in a tertiary hospital in Wuhan. We described the characteristics of patients in fever clinic, then we extracted and classified questions of patient consultations through the online fever clinic dataset.Results: For the 64 487 patients who attended the online fever clinic, the average age was 30.4 years, and 37 665 (58.4%) were female patients. The current state of patients from online were home without isolation (52 360 [81.2%]), home isolated (11 152 [17.29%]), and outpatient observation (975 [1.51%]). From the 594 patient questions analyzed, confirming diagnosis and seeking medical treatment account for 60.61% and 38.05%, respectively, followed by treating (25.59%), preventing (4.38%), and relieving anxiety (1.68%).Discussion: Online fever clinics can effectively relieve patients' mood of panic, and doctors can guide patients with suspected of COVID-19 to isolate and protect themselves through online fever clinic. Online fever clinics can also help to reduce the pressure of hospital fever clinics and prevent cross infection.Conclusions: This study indicated the importance of online fever clinics during the COVID-19 outbreak for prevention and control. [ABSTRACT FROM AUTHOR]

The rapid-developed COVID-19 has been defined as a global emergency by the World Health Organization. Meanwhile, various evidence indicates there is a positive correlation between the transmission and population density, especially in closed and semi-closed space. The urban rail transit, as one of the major mode choices for people to commute in big cities, carries thousands of passengers every day with relatively closed and limited space, which provides favorable conditions for the spread of the virus. If the surrounding area of any station was disrupted under COVID-19, not only the individual line but also the entire urban rail transit network will have the risk to be affected. Therefore, it is necessary to identify and explore the distribution law of key stations during the spreading process of the COVID-19 virus in the urban rail transit network during the COVID-19 pandemic. Based on the spatial distribution of epidemic area and the demand of urban rail transit passengers, we have proposed a construction method of the rail transit network and use the improved shortest path algorithm to determine the route diversity index of each station which indicates its importance in the urban rail transit network. On this basis, we identify the key stations of the Beijing rail transit network to ensure that passengers avoid high-risk stations during the epidemic. The results show that the number of reasonable routes between any two stations is 1 to 5 during the COVID-19 pandemic. Moreover, the routes diversity index of the Beijing rail transit network was 1.235 during the COVID-19 pandemic and 2.2574 in the normal period. According to the reasonable route diversity index, we have identified the key stations of the Beijing rail transit network during the COVID-19, such as Qi-Li-Zhuang station. • A construction method of the urban rail transit network considers the COVID-19. • The improved shortest path algorithm is used to obtain reasonable routes. • Propose a reasonable route diversity index to measure the importance of stations. [ABSTRACT FROM AUTHOR]

• Change point detection is effective in identifying policy lag on mobility. • Investigating the length of policy lag and magnitude of impact jointly is crucial. • The National declaration of emergency had immediate effect on mobility. • Stay-at-home and reopening policies had lead effect; public responded earlier. • Providing lessons learned in planning and resource allocation for future outbreaks. The unprecedented challenges caused by the COVID-19 pandemic demand timely action. However, due to the complex nature of policy making, a lag may exist between the time a problem is recognized and the time a policy has its impact on a system. To understand this lag and to expedite decision making, this study proposes a change point detection framework using likelihood ratio, regression structure and a Bayesian change point detection method. The objective is to quantify the time lag effect reflected in transportation systems when authorities take action in response to the COVID-19 pandemic. Using travel patterns as an indicator of policy effectiveness, the length of policy lag and magnitude of policy impacts on the road system, mass transit, and micromobility are investigated through the case studies of New York City (NYC), and Seattle—two U.S. cities significantly affected by COVID-19. The quantitative findings show that the National declaration of emergency had no policy lag while stay-at-home and reopening policies had a lead effect on mobility. The magnitude of impact largely depended on the land use and sociodemographic characteristics of the area, as well as the type of transportation system. [ABSTRACT FROM AUTHOR]

• We quantitatively explore the impacts of COVID-19 on the usage of bike sharing. • A novel method is proposed to estimate trip distances and trajectories of bike sharing. • Complex network theory is employed to explore the transformation of user behaviors. • COVID-19 impacts the user behaviors and environmental benefits of bike sharing significantly. The COVID-19 pandemic spreads rapidly around the world, and has given rise to huge impacts on all aspects of human society. This study utilizes big data techniques to analyze the impacts of COVID-19 on the user behaviors and environmental benefits of bike sharing. In this study, a novel method is proposed to calculate the trip distances and trajectories via a python package OSMnx so as to accurately estimate the environmental benefits of bike sharing. In addition, we employ the topological indices arising from complex network theory to quantitatively analyze the transformation of user behavior pattern of bike sharing during the COVID-19 pandemic. The results show that this pandemic has impacted the user behaviors and environmental benefits of bike sharing in Beijing significantly. During the pandemic, the estimated reductions of energy consumption and emissions on 6th Feb decreased to approximately 1 in 17 of those on a normal day, and the environmental benefits at most recovered to 70% of those in normal days. The impacts of COVID-19 on the environmental benefits in different districts are different. Furthermore, the decline of average strength and strength distribution obeying exponential distribution but with different slope rates suggests that people are less likely to take bike sharing to the places where were popular before. The pandemic has also increased the average trip time of bike sharing. Our research may facilitate the understanding of the impacts of COVID-19 pandemic on our society and environment, and also provide clues to adapt to this unprecedented pandemic so as to respond to similar events in the future. [ABSTRACT FROM AUTHOR]