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PURPOSE: Patients with type 2 diabetes (T2D) have demonstrated a higher risk for developing more severe cases of COVID-19, but the complex genetic mechanism between them is still unknown. The aim of the present study was to untangle this relationship using genetically based approaches. METHODS: By leveraging large-scale genome-wide association study (GWAS) summary statistics of T2D and COVID-19 severity, linkage disequilibrium score regression and Mendelian randomization (MR) analyses were utilized to quantify the genetic correlations and causal relationships between the two traits. Gene-based association and enrichment analysis were further applied to identify putative functional pathways shared between T2D and COVID-19 severity. RESULTS: Significant, moderate genetic correlations were detected between T2D and COVID-19 hospitalization (rg = 0.156, SE = 0.057, p = 0.005) or severe disease (rg = 0.155, SE = 0.057, p = 0.006). MR analysis did not support evidence for a causal effect of T2D on COVID-19 hospitalization (OR 1.030, 95% CI 0.979, 1.084, p = 0.259) or severe disease (OR 0.999, 95% CI 0.934, 1.069, p = 0.982). Genes having pgene < 0.05 for both T2D and COVID-19 severe were significantly enriched for biological pathways, such as response to type I interferon, glutathione derivative metabolic process and glutathione derivative biosynthetic process. CONCLUSIONS: Our findings further confirm the comorbidity of T2D and COVID-19 severity, but a non-causal impact of T2D on severe COVID-19. Shared genetically modulated molecular mechanisms underlying the co-occurrence of the two disorders are crucial for identifying therapeutic targets.
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During the new coronavirus epidemic in 2020, the number of online learning platform users grew explosively, with secondary school students becoming the main group of online learning platform users. Especially the virtual clinical learning environment of online learning platform for secondary school students, as one of the main factors affecting users' sustained use, has become an important issue companies and researchers are faced with. This paper, taking secondary school student users as the research object, constructed a model of factors influencing users' intention to continuously use the online learning platform for secondary school students. The model, based on TAM model and ECM model, consisted of 10 variables, including TP-Teaching presence, resource quality, system quality, perceived usefulness, perceived ease of use, academic identity, self-efficacy, users' satisfaction, teacher-student relationship, and behavioral intention. Results of this study empirically showed that TP-Teaching presence had the most significant effect on perceived usefulness, which in turn indirectly influenced users' continuance intention of using the platform;secondary school student's self-efficacy has the most significant impact on users' continuous intention. Therefore, when developing the platform, enterprises should pay attention to the construction of the platform learning environment and enhance the self-efficacy of secondary school students.
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Objective: To analyze the course of disease and epidemiological parameters of COVID-19 and provide evidence for making prevention and control strategies. Methods: To display the distribution of course of disease of the infectors who had close contacts with COVID-19 cases from January 1 to March 15, 2020 in Guangdong Provincial, the models of Lognormal, Weibull and gamma distribution were applied. A descriptive analysis was conducted on the basic characteristics and epidemiological parameters of course of disease. Results: In total, 515 of 11 580 close contacts were infected, with an attack rate about 4.4%, including 449 confirmed cases and 66 asymptomatic cases. Lognormal distribution was fitting best for latent period, incubation period, pre-symptomatic infection period of confirmed cases and infection period of asymptomatic cases; Gamma distribution was fitting best for infectious period and clinical symptom period of confirmed cases; Weibull distribution was fitting best for latent period of asymptomatic cases. The latent period, incubation period, pre-symptomatic infection period, infectious period and clinical symptoms period of confirmed cases were 4.50 (95%CI:3.86-5.13) days, 5.12 (95%CI:4.63-5.62) days, 0.87 (95%CI:0.67-1.07) days, 11.89 (95%CI:9.81-13.98) days and 22.00 (95%CI:21.24-22.77) days, respectively. The latent period and infectious period of asymptomatic cases were 8.88 (95%CI:6.89-10.86) days and 6.18 (95%CI:1.89-10.47) days, respectively. Conclusion: The estimated course of COVID-19 and related epidemiological parameters are similar to the existing data.
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COVID-19 , Contact Tracing , Cohort Studies , Humans , Incidence , Prospective StudiesABSTRACT
Objective To analyze the epidemiological characteristics and laboratory tests of coro-navirus diseases 2019(COVID-19) cases in Fujian province and to explore the risk factors for their progression to severe cases. Methods The clinical and epidemiological data of COVID-19 confirmed patients with clinical final outcome (including recovery death, etc.) from January 22 to March 7 in 2020 in Fujian were collected. The risk factors of the severe cases were analyzed by univariate and multivariate Logistic regression. Results Up to March 7, 2020, a total of 231 patients were collected in Fujian province, among which, 39(16.88%) were severe and critical cases. The univariate analysis showed that most patients in the severe group had underlying diseases (71. 80%), which was significantly higher than that in the non-severe group (34. 40%) (%2 = 18. 808, P<0. 001). Among them, hypertension, cardiovascular disease, lung disease, other chronic diseases and other factors were statistically different between the two groups (all P<0. 05). Then, numbers of hematological tests were statistical differences between the two groups. Multivariate Logistic regression analysis revealed that age =5 65 years old (OR =17. 067, 95%CI: 2. 640-110. 327), low level of lymphocyte (OR = 4. 731, 95%>CI: 1. 175-19. 046), liver dysfunction (OR = 12. 458, 95% CI: 2. 559-60. 649), high level of calcitonin (OR = 3. 577, 95% CI: 1. 733-7. 384) and high level of C-reaction protein (OR = 2. 354, 95%CI:1. 012-5. 478) were risk factors for the progression of COVID-19 patients to severe illness. The obtained regression equation fits the training sample well (AUC = 0. 941). Conclusions Low level of lymphocyte,liver dysfunction, high level of calcitonin and high level of C-reaction protein could be used as the early warning indicators for severe cases. More attention should be paid to elderly patients age
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Objective During the COVID-19 epidemic period, we investigated the cognitive level of COVID-19 knowledge of medical staffs in Anhui Province and analyzed the influencing factors of cognitive level of COVID-19 knowledge. Methods From February 12, 2020 to March 4, 2020, a self-made questionnaire was used to evaluate the knowledge of COVID-19 among medical staff in Anhui Province. A total of 15 342 valid questionnaires were obtained. By SPSS 17.0 statistical software, and descriptive analysis, t-test, ANOVA analysis, and multiple linear regression were used to analyze the cognitive level of COVID-19 knowledge of medical staffs and the influencing factors. Results The total score of COVID-19 knowledge of medical staffs in Anhui Province was (6.95±2.67) points, the average score of diagnosis knowledge was (2.58±1.74) points, the average score of treatment knowledge was (1.53±1.03) points, and the score of nosocomial infections knowledge was (2.84±1.01) points. There were significant differences in COVID-19 diagnosis knowledge, nosocomial infections knowledge and total score between doctors and nurses (all P < 0.05). Multivariate linear regression analysis showed that the scores in senior and intermediate professional title groups were higher than those in primary professional title group;the scores in master′s degree group and above and undergraduate education group were higher than those in junior college education group;the knowledge scores in municipal, county-level hospitals, primary medical institutions and private medical institutions were lower than those in provincial hospital group;the scores in patients aged 30~ years and ≥40 years were lower than those in group < 30 years. The scores in senior and intermediate professional title groups were higher than those in junior professional title group;the scores in municipal, county-level hospitals, primary medical institutions and private medical institutions were lower than those in provincial hospitals;the scores of 30~ years old and ≥40 years old were lower than those of < 30 years old group, and the scores of nurses with bachelor′s degree were higher than junior college degree or below (all P < 0.05). Conclusions The score of COVID-19 knowledge of medical staffs in Anhui Province is low, so we should train them COVID-19 knowledge systematically. We should pay attention to the influencing factors like occupation, title, education background, age and hospital rank when selecting and training anti-epidemic medical staffs. © 2021, Publication Centre of Anhui Medical University. All rights reserved.