Screening compounds for treating the diabetes and COVID-19 from Miao medicine by molecular docking and bioinformatics.

Both diabetes and Corona Virus Disease 2019 (COVID-19) are seriously harmful to human health, and they are closely related. It is of great significance to find drugs that can simultaneously treat diabetes and COVID-19. Based on the theory of traditional Chinese medicine for treating COVID-19, this study first sorted out the compounds of Guizhou Miao medicine with "return to the lung channel" and "clear heat and detoxify" effects in China. The active components against COVID-19 were screened by molecular docking with SARS-CoV-2 PLpro and angiotensin-converting enzyme II as targets. Furthermore, the common target dipeptidyl peptidase 4 (DPP4) of diabetes and COVID-19 was used as a screening protein, and molecular docking was used to obtain potential components for the treatment of diabetes and COVID-19. Finally, the mechanism of potential ingredients in the treatment of diabetes and COVID-19 was explored with bioinformatics. More than 80 kinds of Miao medicine were obtained, and 584 compounds were obtained. Further, 110 compounds against COVID-19 were screened, and top 6 potential ingredients for the treatment of diabetes and COVID-19 were screened, including 3-O-ß-D-Xylopyranosyl-(1-6)-ß-D-glucopyranosyl-(1-6)-ß-D-glucopyranosyl oleanolic acid 28-O-ß-D-glucopyranosyl ester, Glycyrrhizic acid, Sequoiaflavone, 2-O-Caffeoyl maslinic acid, Pholidotin, and Ambewelamide A. Bioinformatics analysis found that their mechanism of action in treating diabetes and COVID-19 may be related to regulating the expression of DPP4, angiotensin II type 1 receptor, vitamin D receptor, plasminogen, chemokine C-C-motif receptor 6, and interleukin 2. We believe that Guizhou Miao medicine is rich in potential ingredients for the treatment of diabetes and COVID-19.

Psychological experience of Juvenile patients' parents in Fangcang shelter hospital during the Omicron wave of COVID-19 pandemic in Shanghai, China: a qualitative study.

OBJECTIVE: To explore the psychological experience of Juvenile patient's parents in Fangcang shelter hospital during the Omicron wave of COVID-19 pandemic. METHODS: A qualitative study was conducted by using a phenomenological research method. Sixteen parents of juvenile patients with COVID-19 were recruited from National Exhibition and Convention Center (Shanghai, China) Fangcang shelter hospital (FSH) using purposive sampling. Data were collected by face-to-face in-depth interviews over 27 days, from April 9 to May 6, 2022. The interview data were analyzed using Colaizzi seven-step analysis method. RESULTS: The psychological experiences of the parents of juvenile patients in the Fangcang shelter hospital were summarized into three themes: "perception regarding the FSH", "worried about the unmet needs of juvenile patients ", and "the psychological burden after discharge". These themes were classified into 9 sub-themes, including the acceptance of FSH, adaptability to FSH, concerns about cross-infection in the FSH, special needs of infants and young children, psychological needs of preschool children, the learning demands of school-age children, concern about re-positive, fear of sequelae, worry about social acceptance. CONCLUSION: Juvenile patients and their parents in the Fangcang shelter hospitals have both positive and negative experiences. It is suggested that facilities for minors should be planned in advance. Humanistic care for adolescent patients and health education for the public are also critical.

Using machine learning models to predict the duration of the recovery of COVID-19 patients hospitalized in Fangcang shelter hospital during the Omicron BA. 2.2 pandemic.

Background: Factors that may influence the recovery of patients with confirmed SARS-CoV-2 infection hospitalized in the Fangcang shelter were explored, and machine learning models were constructed to predict the duration of recovery during the Omicron BA. 2.2 pandemic. Methods: A retrospective study was conducted at Hongqiao National Exhibition and Convention Center Fangcang shelter (Shanghai, China) from April 9, 2022 to April 25, 2022. The demographics, clinical data, inoculation history, and recovery information of the 13,162 enrolled participants were collected. A multivariable logistic regression model was used to identify independent factors associated with 7-day recovery and 14-day recovery. Machine learning algorithms (DT, SVM, RF, DT/AdaBoost, AdaBoost, SMOTEENN/DT, SMOTEENN/SVM, SMOTEENN/RF, SMOTEENN+DT/AdaBoost, and SMOTEENN/AdaBoost) were used to build models for predicting 7-day and 14-day recovery. Results: Of the 13,162 patients in the study, the median duration of recovery was 8 days (interquartile range IQR, 6-10 d), 41.31% recovered within 7 days, and 94.83% recovered within 14 days. Univariate analysis showed that the administrative region, age, cough medicine, comorbidities, diabetes, coronary artery disease (CAD), hypertension, number of comorbidities, CT value of the ORF gene, CT value of the N gene, ratio of ORF/IC, and ratio of N/IC were associated with a duration of recovery within 7 days. Age, gender, vaccination dose, cough medicine, comorbidities, diabetes, CAD, hypertension, number of comorbidities, CT value of the ORF gene, CT value of the N gene, ratio of ORF/IC, and ratio of N/IC were related to a duration of recovery within 14 days. In the multivariable analysis, the receipt of two doses of the vaccination vs. unvaccinated (OR = 1.118, 95% CI = 1.003-1.248; p = 0.045), receipt of three doses of the vaccination vs. unvaccinated (OR = 1.114, 95% CI = 1.004-1.236; p = 0.043), diabetes (OR = 0.383, 95% CI = 0.194-0.749; p = 0.005), CAD (OR = 0.107, 95% CI = 0.016-0.421; p = 0.005), hypertension (OR = 0.371, 95% CI = 0.202-0.674; p = 0.001), and ratio of N/IC (OR = 3.686, 95% CI = 2.939-4.629; p < 0.001) were significantly and independently associated with a duration of recovery within 7 days. Gender (OR = 0.736, 95% CI = 0.63-0.861; p < 0.001), age (30-70) (OR = 0.738, 95% CI = 0.594-0.911; p < 0.001), age (>70) (OR = 0.38, 95% CI = 0292-0.494; p < 0.001), receipt of three doses of the vaccination vs. unvaccinated (OR = 1.391, 95% CI = 1.12-1.719; p = 0.0033), cough medicine (OR = 1.509, 95% CI = 1.075-2.19; p = 0.023), and symptoms (OR = 1.619, 95% CI = 1.306-2.028; p < 0.001) were significantly and independently associated with a duration of recovery within 14 days. The SMOTEEN/RF algorithm performed best, with an accuracy of 90.32%, sensitivity of 92.22%, specificity of 88.31%, F1 score of 90.71%, and AUC of 89.75% for the 7-day recovery prediction; and an accuracy of 93.81%, sensitivity of 93.40%, specificity of 93.81%, F1 score of 93.42%, and AUC of 93.53% for the 14-day recovery prediction. Conclusion: Age and vaccination dose were factors robustly associated with accelerated recovery both on day 7 and day 14 from the onset of disease during the Omicron BA. 2.2 wave. The results suggest that the SMOTEEN/RF-based model could be used to predict the probability of 7-day and 14-day recovery from the Omicron variant of SARS-CoV-2 infection for COVID-19 prevention and control policy in other regions or countries. This may also help to generate external validation for the model.

Clinical characteristics and a decision tree model to predict death outcome in severe COVID-19 patients.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) spreads rapidly among people and causes a pandemic. It is of great clinical significance to identify COVID-19 patients with high risk of death. METHODS: A total of 2169 adult COVID-19 patients were enrolled from Wuhan, China, from February 10th to April 15th, 2020. Difference analyses of medical records were performed between severe and non-severe groups, as well as between survivors and non-survivors. In addition, we developed a decision tree model to predict death outcome in severe patients. RESULTS: Of the 2169 COVID-19 patients, the median age was 61 years and male patients accounted for 48%. A total of 646 patients were diagnosed as severe illness, and 75 patients died. An older median age and a higher proportion of male patients were found in severe group or non-survivors compared to their counterparts. Significant differences in clinical characteristics and laboratory examinations were found between severe and non-severe groups, as well as between survivors and non-survivors. A decision tree, including three biomarkers, neutrophil-to-lymphocyte ratio, C-reactive protein and lactic dehydrogenase, was developed to predict death outcome in severe patients. This model performed well both in training and test datasets. The accuracy of this model were 0.98 in both datasets. CONCLUSION: We performed a comprehensive analysis of COVID-19 patients from the outbreak in Wuhan, China, and proposed a simple and clinically operable decision tree to help clinicians rapidly identify COVID-19 patients at high risk of death, to whom priority treatment and intensive care should be given.

Prevalence and Risk Factors of Mental Health Problems Among Healthcare Workers During the COVID-19 Pandemic: A Systematic Review and Meta-Analysis.

Objective: The purpose of this meta-analysis was to summarize the prevalence and risk factors of mental health problems among healthcare workers during the COVID-19 pandemic. Methods: We applied an optimized search strategy across the PubMed, EMBASE, Scopus, PsycINFO, and four Chinese databases, with hand searching supplemented to identify relevant surveys. Studies were eligible for inclusion if they were published in peer-reviewed literature and used a validated method to assess the prevalence and risk factors of mental health problems among healthcare workers during the COVID-19 pandemic. Heterogeneity was quantified using Q statistics and the I 2 statistics. The potential causes of heterogeneity were investigated using subgroup analysis and meta-regression analysis. Sensitivity analysis was performed to examine the robustness of the results. Results: We pooled and analyzed data from 20 studies comprising 10,886 healthcare workers. The prevalence of depression, anxiety, insomnia, post-traumatic stress symptoms, phobia, obsessive-compulsive symptoms, and somatization symptoms was 24.1, 28.6, 44.1, 25.6, 35.0, 16.2, and 10.7%, respectively. Female and nurses had a high prevalence of depression and anxiety. Frontline healthcare workers had a higher prevalence of anxiety and a lower prevalence of depression than the those in the second-line. Furthermore, the proportion of moderate-severe depression and anxiety is higher in the frontline. Additionally, four studies reported on risk factors of mental health problems. Conclusions: In this systematic review, healthcare workers have a relatively high prevalence of depression, anxiety, insomnia, post-traumatic stress symptoms, phobia, obsessive-compulsive symptoms, and somatization symptoms during the COVID-19 pandemic, and focus should be on the healthcare workers at high risk of mental problems. Mental health problems in healthcare workers should be taken seriously, and timely screening and appropriate intervention for the high-risk group are highly recommended. Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020179189.

Multicenter investigation of current status of use of personal protective equipment among healthcare workers during diagnosis and treatment of COVID-19

OBJECTIVE: To investigate the use of personal protective equipment (PPE) of healthcare workers (HCWs) in the room where confirmed COVID-19 patients are admitted and understand the current status of prevention. METHODS: The healthcare workers who from medical aid teams in Hubei in 30 hospitals were randomly selected by the trained staff for hospital infection prevention, the basic characteristics of the enrolled subjects and the use of PPE were recorded, and the questionnaires were filled out through questionnaire star. RESULTS: The survey found that all the healthcare workers received theoretical training and practical training on the use of PPE before entering the isolation ward, 95.56% (2 433) of them were inspected or supervised by someone when they put on or took off PPE. 86.57% (2 204) of the healthcare workers wore two layers of masks at the same time, most of whom (1621, 63.67%) wore medical surgical mask and respirator at the same time. 57.50% (1 464) of the healthcare workers used goggles or face shield, 42.50% (1 082) of whom used goggles and face shield at the same time. 95.25% (2 425) of the healthcare workers wore coverall and disposable gown at the same time. 96.62% (2 460) of the healthcare workers wore boot covers and shoe covers at the same time. The proportion of the healthcare workers who wore two-layer hats was the highest (70.54%), and the proportion of the healthcare workers who wore two-layer gloves was also the highest (57.31%). CONCLUSION The use of PPE of the HCWs who are from the medical aid teams has effectively prevented the COVID-19 infection, achieving a 'zero infection' among the 42.6 thousand HCWs. However, there are excessive use of PPE, and the rational use of PPE needs to be further standardized and explored.