Development and validation of a prediction nomogram for academic burnout among Chinese adolescents: a cross-sectional study.

OBJECTIVES: This study aimed to screen the potential risk factors for academic burnout among adolescents during the COVID-19 pandemic, develop and validate a predictive tool based on the risk factors for predicting academic burnout. DESIGN: This article presents a cross-sectional study. SETTING: This study surveyed two high schools in Anhui Province, China. PARTICIPANTS: A total of 1472 adolescents were enrolled in this study. OUTCOME MEASURES: The questionnaires included demographic characteristic variables, living and learning states and adolescents' academic burnout scale. Least absolute shrinkage and selection operator and multivariate logistic regression analyses were employed to screen the risk factors for academic burnout and develop a predictive model. The receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to assess the accuracy and discrimination of the nomogram. RESULTS: In this study, 21.70% of adolescents reported academic burnout. Multivariable logistic regression analysis showed that single-child family (OR=1.742, 95% CI: 1.243 to 2.441, p=0.001), domestic violence (OR=1.694, 95% CI: 1.159 to 2.476, p=0.007), online entertainment (>8 hours/day, OR=3.058, 95% CI: 1.634 to 5.720, p<0.001), physical activity (<3 hours/week, OR=1.686, 95% CI: 1.032 to 2.754, p=0.037), sleep duration (<6 hours/night, OR=2.342, 95% CI: 1.315 to 4.170, p=0.004) and academic performance (<400 score, OR=2.180, 95% CI: 1.201 to 3.958, p=0.010) were independent significant risk factors associated with academic burnout. The area under the curve of ROC with the nomogram was 0.686 in the training set and 0.706 in the validation set. Furthermore, DCA demonstrated that the nomogram had good clinical utility for both sets. CONCLUSIONS: The developed nomogram was a useful predictive model for academic burnout among adolescents during the COVID-19 pandemic. It is essential to emphasise the importance of mental health and promote a healthy lifestyle among adolescents during the future pandemic.

Promotion strategy for online healthcare platform during the COVID-19 pandemic: Evidence from Spring Rain Doctor in China.

Introduction: Online healthcare platform (OHP) is a new form of medical treatment that solves the problems of an unbalanced distribution of medical resources in China. Especially during the COVID-19 pandemic, OHP has greatly reduced the medical pressure of the hospital and the risk of cross-infection. Methods: Based on self-determination theory (SDT) (Ryan and Deci, 2000), privacy calculus theory (PCT) (Culnan, 1999) and perceived value theory (PVT) (Choi, 2004), this study uses evolutionary game theory to analyze behavioral strategies and their dynamic evolution in the promotion of OHP. Moreover, we conduct numerical simulations with the help of program compilation. Results: The results demonstrate that (1) both the qualification inspection of doctors and the investment in information protection influence doctors' participation in and patients' usage of OHP; (2) both the initial probabilities of doctor participation and patient usage influence the multi-game results; (3) the trend of doctors joining OHP is affected by registration cost, time cost, and reputation loss; and (4) the trend of patients using online healthcare is mainly decided by the cost. Conclusion: This study takes the Spring Rain Doctor as an example to verify the game results. To further popularize online medical treatment among patients, the platform should attach importance to the inspection of doctors and the protection of privacy information and strengthen its publicity in remote places.

Statin Use in Hospitalized Patients with COVID-19: A Comprehensive Analysis of the New York City Public Hospital System.

INTRODUCTION: Statins have been commonly used for primary and secondary cardiovascular prevention. We hypothesized that statins may improve in-hospital outcomes for hospitalized patients with Coronavirus disease 2019 (COVID-19) due to its known anti-inflammatory effects. METHODS: We conducted a retrospective study at the largest municipal health care system in the United States, including adult patients who were hospitalized for COVID-19 between March 1 and December 1, 2020. The primary endpoint was in-hospital death. Propensity score matching was conducted to balance possible confounding variables between patients receiving statins during hospitalization (statin group) and those not receiving statins (non-statin group). Multivariate logistic regression was used to evaluate the association of statin use and other variables with in-hospital outcomes. RESULTS: There were 8897 patients eligible for study enrollment, with 3359 patients in the statin group and 5538 patients in the non-statin group. After propensity score matching, both the statin and non-statin groups included 2817 patients. Multivariate logistic regression analysis showed that the statin group had a significantly lower risk of in-hospital mortality (odds ratio 0.71; 95% confidence interval, 0.63-0.80; P < .001) and mechanical ventilation (OR 0.80; 95% confidence interval, 0.71-0.90; P < .001) compared with the non-statin group. CONCLUSION: Statin use was associated with lower likelihood of in-hospital mortality and invasive mechanical ventilation in hospitalized patients with COVID-19.

Echocardiography Abnormal Findings and Laboratory Operations during the COVID-19 Pandemic at a High Volume Center in New York City.

(1) Background: This study sought to explore how the novel coronavirus (COVID-19) pandemic affected the echocardiography (TTE) laboratory operations at a high volume medical center in New York City. Changes in cardiac imaging study volume, turn-around time, and abnormal findings were analyzed and compared to a pre-pandemic period. (2) Methods: Volume of all cardiac imaging studies and TTE reports between 11 March 2020 to 5 May 2020 and the same calendar period in 2019 were retrospectively identified and compared. (3) Results: During the pandemic, our center experienced a 46.72% reduction in TTEs, 82.47% reduction in transesophageal echocardiograms, 83.16% reduction in stress echo, 70.32% reduction in nuclear tests, 46.25% reduction in calcium score, 73.91% reduction in coronary computed tomography angiography, and 87.23% reduction in cardiac magnetic resonance imaging. TTE findings were overall similar between 2020 and 2019 (all p ≥ 0.05), except for a significantly higher right ventricular systolic pressure in 2020 (39.8 ± 14.2 vs. 34.6 ± 11.2 mmHg, p = 0.012). (4) Conclusions: Despite encountering an influx of critically ill patients, our hospital center experienced a reduction in the number of cardiac imaging studies, which likely represents a change in both patient mindset and physician management approach.

Diabetes is associated with increased risk for in-hospital mortality in patients with COVID-19: a systematic review and meta-analysis comprising 18,506 patients.

PURPOSE: Infectious diseases are more frequent and can be associated with worse outcomes in patients with diabetes. The aim of this study was to systematically review and conduct a meta-analysis of the available observational studies reporting the effect of diabetes on mortality among hospitalized patients with COVID-19. METHODS: The Medline, Embase, Google Scholar, and medRxiv databases were reviewed for identification of eligible studies. A random effects model meta-analysis was used, and I2 was utilized to assess the heterogeneity. In-hospital mortality was defined as the endpoint. Sensitivity, subgroup, and meta-regression analyses were performed. RESULTS: A total of 18,506 patients were included in this meta-analysis (3713 diabetics and 14,793 non-diabetics). Patients with diabetes were associated with a higher risk of death compared with patients without diabetes (OR 1.65; 95% CI 1.35-1.96; I2 77.4%). The heterogeneity was high. A study-level meta-regression analysis was performed for all the important covariates, and no significant interactions were found between the covariates and the outcome of mortality. CONCLUSION: This meta-analysis shows that that the likelihood of death seems to be higher in diabetic patients hospitalized with COVID-19 compared with non-diabetic patients. Further studies are needed to assess whether this association is independent or not, as well as to investigate the role of adequate glycemic control prior to infection with COVID-19.