The relationship between internet use preference and loneliness among college students during COVID-19: The chain mediating effect of online social support and self-esteem.

The outbreak of COVID-19, especially the demands of social interaction and spatial distancing behavior, has led to a surge in Internet use, which has also led to an increase in loneliness. Therefore, we investigated the role of online social support and self-esteem in the relationship between Internet use preference and loneliness. In this study, 1053 college students were surveyed with a questionnaire based on the framework of Ecological System Theory, and a chain mediation model was established to clarify the mechanism between Internet use preference and loneliness. The results show that Internet use preference not only positively predicts loneliness, but also indirectly influences loneliness through the mediators of online social support and self-esteem, thereby impacting loneliness through the "online social support → self-esteem" chain. The results also indicate the need to pay attention to college students' mental health status during COVID-19. The advent of COVID-19 has impacted people's lifestyles and has changed the impact of the Internet on individual mental health. This study provides a new way to further understand college students' Internet use preferences, online social support, self-esteem, and loneliness status during COVID-19. It provides targeted interventions for college students' loneliness during COVID-19.

Changes in Physical Fitness during COVID-19 Pandemic Lockdown among Adolescents: A Longitudinal Study.

The negative impact of COVID-19 on physical activity has been improved, while the research on changes in physical fitness that may be caused by physical inactivity is still scarce. This study aims to explore the impact of the COVID-19 pandemic lockdown on physical fitness, and the impact of initial physical fitness indicators on their changes during the lockdown in adolescents. A longitudinal study including 265 adolescents aged 14.1 ± 0.4 years old was conducted in China. Physical fitness measurement at baseline and follow-up were respectively measured before (November 2019) and after the lockdown (July 2020). Several physical fitness indicators including aerobic fitness (i.e., 800-m or 1000-m run) and explosive force (i.e., 50-m sprint) deteriorated during the lockdown. Whereas the performances of vital capacity, flexibility (i.e., sit and reach), and muscular strength (i.e., pull-ups) were significantly improved during the lockdown. Furthermore, the reduction in physical fitness for adolescents with higher physical fitness before the lockdown was greater than that for others. These findings may contribute to the development of targeted intervention strategies for physical fitness promotion during the lockdown caused by the public health emergency.

Early kidney injury predicts disease progression in patients with COVID-19: a cohort study.

BACKGROUND: The receptor of severe respiratory syndrome coronavirus 2 (SARS-CoV-2), angiotensin-converting enzyme 2, is more abundant in kidney than in lung tissue, suggesting that kidney might be another important target organ for SARS-CoV-2. However, our understanding of kidney injury caused by Coronavirus Disease 2019 (COVID-19) is limited. This study aimed to explore the association between kidney injury and disease progression in patients with COVID-19. METHODS: A retrospective cohort study was designed by including 2630 patients with confirmed COVID-19 from Huoshenshan Hospital (Wuhan, China) from 1 February to 13 April 2020. Kidney function indexes and other clinical information were extracted from the electronic medical record system. Associations between kidney function indexes and disease progression were analyzed using Cox proportional-hazards regression and generalized linear mixed model. RESULTS: We found that estimated glomerular filtration rate (eGFR) and creatinine clearance (Ccr) decreased in 22.0% and 24.0% of patients with COVID-19, respectively. Proteinuria was detected in 15.0% patients and hematuria was detected in 8.1% of patients. Hematuria (HR 2.38, 95% CI 1.50-3.78), proteinuria (HR 2.16, 95% CI 1.33-3.51), elevated baseline serum creatinine (HR 2.84, 95% CI 1.92-4.21) and blood urea nitrogen (HR 3.54, 95% CI 2.36-5.31), and decrease baseline eGFR (HR 1.58, 95% CI 1.07-2.34) were found to be independent risk factors for disease progression after adjusted confounders. Generalized linear mixed model analysis showed that the dynamic trajectories of uric acid was significantly related to disease progression. CONCLUSION: There was a high proportion of early kidney function injury in COVID-19 patients on admission. Early kidney injury could help clinicians to identify patients with poor prognosis at an early stage.

Fasting plasma glucose and glucose fluctuation are associated with COVID-19 prognosis regardless of pre-existing diabetes.

AIMS: We aimed to investigate the role of Fasting Plasma Glucose (FPG) and glucose fluctuation in the prognosis of COVID-19 patients stratified by pre-existing diabetes. METHODS: The associations of FPG and glucose fluctuation indexes with prognosis of COVID-19 in 2,642 patients were investigated by multivariate Cox regression analysis. The primary outcome was in-hospital mortality; the secondary outcome was disease progression. The longitudinal changes of FPG over time were analyzed by the latent growth curve model in COVID-19 patients stratified by diabetes and severity of COVID-19. RESULTS: We found FPG as an independent prognostic factor of overall survival after adjustment for age, sex, diabetes and severity of COVID-19 at admission (HR: 1.15, 95% CI: 1.06-1.25, P = 1.02 × 10-3). Multivariate logistic regression analysis indicated that the standard deviation of blood glucose (SDBG) and largest amplitude of glycemic excursions (LAGE) were also independent risk factors of COVID-19 progression (P = 0.03 and 0.04, respectively). The growth trajectory of FPG over the first 3 days of hospitalization was steeper in patients with critical COVID-19 in comparison to moderate patients. CONCLUSIONS: Hyperglycemia and glucose fluctuation were adverse prognostic factors of COVID-19 regardless of pre-existing diabetes. This stresses the importance of glycemic control in addition to other therapeutic management.

Inflammation characteristics and anti-inflammation treatment with tocilizumab of severe/critical COVID-19 patients: A retrospective cohort study.

The efficacy of tocilizumab on the prognosis of severe/critical COVID-19 patients is still controversial so far. We aimed to delineate the inflammation characteristics of severe/critical COVID-19 patients and determine the impact of tocilizumab on hospital mortality. Here, we performed a retrospective cohort study which enrolled 727 severe or critical inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Huoshenshan Hospital (Wuhan, China), among which 50 patients received tocilizumab. This study confirmed that most recovered patients manifested relatively normal inflammation levels at admission, whereas most of the deceased cases presented visibly severe inflammation at admission and even progressed into extremely aggravated inflammation before their deaths, proved by some extremely high concentrations of interleukin-6, procalcitonin, C-reactive protein and neutrophil count. Moreover, based on the Cox proportional-hazards models before or after propensity score matching, we demonstrated that tocilizumab treatment could lessen mortality by gradually alleviating excessive inflammation and meanwhile continuously enhancing the levels of lymphocytes within 14 days for severe/critical COVID-19 patients, indicating potential effectiveness for treating COVID-19.

Sustainable innovation in the context of organizational cultural diversity: The role of cultural intelligence and knowledge sharing.

With the in-depth development of globalization, individuals are increasingly embedded in a culturally diverse environment. Effective communication and management ability (Cultural Intelligence) of employees in this type of diverse and heterogeneous environment impacts behavior and performance, affecting the sustainable innovation ability of organizations. Researchers have not yet fully assessed the impact of individuals' cross-cultural management ability on sustainable innovation. Using Cultural Intelligence Theory and Trait Activation Theory, this paper discusses the influence of individual cultural intelligence on sustainable innovation behavior. The results showed that employees' cultural intelligence positively affected their sustainable innovation behavior. Employee knowledge sharing plays an mediating role between intelligence and behavior. Differences in organizational culture have a negative moderating effect on the impact of employees' cultural intelligence on knowledge sharing and sustainable innovation behaviors. The research results provide theoretical guidance for managing organizational cultural diversity and advancing cultural intelligence and sustainable innovation behaviors among employees.

Associations of acute exposure to airborne pollutants with COVID-19 infection: evidence from China.

The outbreak of COVID-19, caused by SARS-CoV-2, has spread across many countries globally. Greatly, there are limited studies concerned with the effect of airborne pollutants on COVID-19 infection, while exposure to airborne pollutants may harm human health. This paper aimed to examine the associations of acute exposure to ambient atmospheric pollutants to daily newly COVID-19 confirmed cases in 41 Chinese cities. Using a generalized additive model with Poisson distribution controlling for temperature and relative humidity, we evaluated the association between pollutant concentrations and daily COVID-19 confirmation at single-city level and multicity levels. We observed a 10-µg/m3 rise in levels of PM2.5 (lag 0-14), O3 (lag 0-1), SO2 (lag 0), and NO2 (lag 0-14) were positively associated with relative risks of 1.050 (95% CI: 1.028, 1.073), 1.011 (1.007, 1.015), 1.052 (1.022, 1.083), and 1.094 (1.028, 1.164) of daily newly confirmed cases, respectively. Further adjustment for other pollutants did not change the associations materially (excepting in the model for SO2). Our results indicated that COVID-19 incidence may be susceptible to airborne pollutants such as PM2.5, O3, SO2, and NO2, and mitigation strategies of environmental factors are required to prevent spreading.

Risk stratification scores for hospitalization duration and disease progression in moderate and severe patients with COVID-19.

BACKGROUND: During outbreak of Coronavirus Disease 2019 (COVID-19), healthcare providers are facing critical clinical decisions based on the prognosis of patients. Decision support tools of risk stratification are needed to predict outcomes in patients with different clinical types of COVID-19. METHODS: This retrospective cohort study recruited 2425 patients with moderate or severe COVID-19. A logistic regression model was used to select and estimate the factors independently associated with outcomes. Simplified risk stratification score systems were constructed to predict outcomes in moderate and severe patients with COVID-19, and their performances were evaluated by discrimination and calibration. RESULTS: We constructed two risk stratification score systems, named as STPCAL (including significant factors in the prediction model: number of clinical symptoms, the maximum body temperature during hospitalization, platelet count, C-reactive protein, albumin and lactate dehydrogenase) and TRPNCLP (including maximum body temperature during hospitalization, history of respiratory diseases, platelet count, neutrophil-to-lymphocyte ratio, creatinine, lactate dehydrogenase, and prothrombin time), to predict hospitalization duration for moderate patients and disease progression for severe patients, respectively. According to STPCAL score, moderate patients were classified into three risk categories for a longer hospital duration: low (Score 0-1, median = 8 days, with less than 20.0% probabilities), intermediate (Score 2-6, median = 13 days, with 30.0-78.9% probabilities), high (Score 7-9, median = 19 days, with more than 86.5% probabilities). Severe patients were stratified into three risk categories for disease progression: low risk (Score 0-5, with less than 12.7% probabilities), intermediate risk (Score 6-11, with 18.6-69.1% probabilities), and high risk (Score 12-16, with more than 77.9% probabilities) by TRPNCLP score. The two risk scores performed well with good discrimination and calibration. CONCLUSIONS: Two easy-to-use risk stratification score systems were built to predict the outcomes in COVID-19 patients with different clinical types. Identifying high risk patients with longer stay or poor prognosis could assist healthcare providers in triaging patients when allocating limited healthcare during COVID-19 outbreak.

Lactic dehydrogenase-lymphocyte ratio for predicting prognosis of severe COVID-19.

ABSTRACT: To develop a useful score for predicting the prognosis of severe corona virus disease 2019 (COVID-19) patients.We retrospectively analyzed patients with severe COVID-19 who were admitted from February 10, 2020 to April 5, 2020. First, all patients were randomly assigned to a training cohort or a validation cohort. By univariate analysis of the training cohort, we developed combination scores and screened the superior score for predicting the prognosis. Subsequently, we identified the independent factors influencing prognosis. Finally, we demonstrated the predictive efficiency of the score in validation cohort.A total of 145 patients were enrolled. In the training cohort, nonsurvivors had higher levels of lactic dehydrogenase than survivors. Among the 7 combination scores that were developed, lactic dehydrogenase-lymphocyte ratio (LLR) had the highest area under the curve (AUC) value for predicting prognosis, and it was associated with the incidence of liver injury, renal injury, and higher disseminated intravascular coagulation (DIC) score on admission. Univariate logistic regression analysis revealed that C-reactive protein, DIC score ≥2 and LLR >345 were the factors associated with prognosis. Multivariate analysis showed that only LLR >345 was an independent risk factor for prognosis (odds ratio [OR] = 9.176, 95% confidence interval [CI]: 2.674-31.487, P < .001). Lastly, we confirmed that LLR was also an independent risk factor for prognosis in severe COVID-19 patients in the validation cohort where the AUC was 0.857 (95% CI: 0.718-0.997).LLR is an accurate predictive score for poor prognosis of severe COVID-19 patients.