Anxiety, depression, insomnia symptoms & associated factors among young to middle-aged adults during the resurgent epidemic of COVID-19: a cross-sectional study.

The coronavirus disease 2019 (COVID-19) pandemic is a public health emergency of international concern. However, its stress on the mental health of young to middle-aged adults is largely unexplored. This study aimed to evaluate the mental health difficulties during the resurgent phase of COVID-19 among young to middle-aged adults in China. There were 1,478 participants with a median age of 26 years (IQR, 23 - 30), including 535 males (36.2%). The prevalence of anxiety, depression, and insomnia were 8.6%, 11.4%, and 13.7%, respectively. Participants aged 29 - 59 years (OR, 95% CI: 2.46, 1.23 - 4.91) and females (2.49, 1.55 - 4.01) had a higher risk of anxiety. Education status, worried level about the current COVID-19, and the level of COVID-19's impact on life were significantly associated with the prevalence of anxiety. Besides, the level of COVID-19's impact on life was positively related to the prevalence of depression and insomnia. Our study provided novel evidence of psychological difficulties among young to middle-aged adults during the resurgent stage of the COVID-19 epidemic. Psychological intervention should be continuously implemented to prevent long-term psychological comorbidities during the COVID-19 epidemic.

Learning Clinical Concepts for Predicting Risk of Progression to Severe COVID-19

With COVID-19 now pervasive, identification of high-risk individuals is crucial. Using data from a major healthcare provider in Southwestern Pennsylvania, we develop survival models predicting severe COVID-19 progression. In this endeavor, we face a tradeoff between more accurate models relying on many features and less accurate models relying on a few features aligned with clinician intuition. Complicating matters, many EHR features tend to be under-coded degrading the accuracy of smaller models. In this study we develop two sets of high-performance risk scores: (i) an unconstrained model built from all available features;and (ii) a pipeline that learns a small set of clinical concepts before training a risk predictor. Learned concepts boost performance over the corresponding features (C-index 0.858 vs. 0.844) and demonstrate improvements over (i) when evaluated out-of-sample (subsequent time periods). Our models outperform previous works (C-index 0.844–0.872 vs. 0.598–0.810).

Administration of macrolide antibiotics increases cardiovascular risk.

Background: The increased risk of cardiovascular events in patients prescribed macrolides has been subject to debate for decades. Methods: Medline, EMBASE databases and ClinicalTrials.gov were searched from inception until August 31, 2022 for studies investigating the link between macrolides and cardiovascular risk. A meta-analysis was performed using a random-effects model. Results: A total of 80 studies involving 39,374,874 patients were included. No association was found between macrolides and all-cause death. However, compared with the non-macrolide group, macrolides were associated with a significantly increased risk of ventricular arrhythmia or sudden cardiac death (VA or SCD) (azithromycin, relative ratio [RR]: 1.53; 95% confidence interval [CI]: 1.19 to 1.97; clarithromycin, RR: 1.52; 95% CI: 1.07 to 2.16). Besides, administration of macrolides was associated with a higher risk of cardiovascular disease (CVD) death (azithromycin, RR: 1.63; 95% CI: 1.17 to 2.27) and a slightly increased risk of myocardial infarction (MI) (azithromycin, RR: 1.08; 95% CI: 1.02 to 1.15). Interestingly, no association was observed between roxithromycin and adverse cardiac outcomes. Increased risk of VA or SCD was observed for recent or current use of macrolides, MI for former use, and CVD death for current use. Conclusion: Administration of macrolide antibiotics and timing of macrolide use are associated with increased risk for SCD or VTA and cardiovascular death, but not all-cause death.

Synergic Effect of Intravitreal Bevacizumab and Systemic Corticosteroid in Treating Systemic Inflammatory Response Syndrome (SIRS) Associated Purtscher-like Retinopathy.

PURPOSE: To demonstrate the treatment effect of combined intravitreal bevacizumab (IVB) and systemic steroid for systemic inflammatory response syndrome (SIRS)-related Purtscher-like retinopathy (PuR). METHODS: Retrospective case report. RESULTS: A 19-year-old patient experienced bilateral blurred vision after urinary tract infection-induced SIRS. Typical bilateral PuR was found in fundus examination and fluorescein angiography. Optical coherence tomography (OCT) revealed severe cystoid macular edema (CME) and OCT angiography revealed marked vascular defects in both superficial and deep plexuses. Intravitreal injection of bevacizumab 1.25 mg was first performed in the right eye along with systemic corticosteroid therapy. One week later, marked improvement in visual acuity and CME was noted in the right eye, but not in the non-IVB-treated left eye. IVB was then performed in the left eye and achieved much improvement 8 days later. CONCLUSION: This report clearly demonstrated the synergic effect of IVB and systemic steroids for CME on SIRS-related PuR.

Takotsubo Syndrome Occurring after mRNA COVID-19 Vaccination in a Patient with Graves' Disease.

Cardiovascular events such as myocarditis following mRNA COVID-19 vaccination are increasing. We present a 67-year-old postmenopausal woman with Takotsubo Syndrome and Graves' disease after mRNA COVID-19 vaccination. She developed chest pain and shortness of breath one week after vaccination. An electrocardiogram revealed ST elevation in the precordial leads. Coronary angiography revealed the absence of obstructive coronary artery disease, and the left ventriculography showed a typical feature with apical ballooning. Laboratory workup showed the elevation of free T4 and thyrotropin receptor antibodies. It was presumed that Takotsubo Syndrome and Graves' disease were probably related to the COVID-19 mRNA vaccination. The patient was treated with low-dose bisoprolol, diuretics, carbimazole, and steroid and discharged uneventfully. The mRNA COVID-19 vaccination is still safe and effective to defend against COVID-19 pandemic. However, clinicians should be aware of the possible cardiovascular adverse events other than myocarditis following vaccination.

Use of WeChat to gratify information needs of the Chinese community in Portugal during the COVID-19 outbreak

This paper seeks to characterize the main themes of COVID-19-related posts delivered by WeChat official accounts targeting Portuguese news and explore their subscribers' information needs and preferences. Furthermore, the current study set out to evaluate the influence of the coronavirus situation in Portugal on the number of posts, view frequency and total engagement on the WeChat platform. Following the selection of COVID-19-related posts published in 2021 by four official accounts targeting Portuguese news, Chi-square tests were conducted to quantitively describe the differences between the four developmental stages of the COVID-19 pandemic in Portugal. Negative binomial regression was employed to establish an association between categorical variables and count data. Regression analysis was used to explore the relationship between COVID-19 infection cases in Portugal and the metrics of selected posts. A total of 3292 COVID-19-related posts remained. The posts regarding the latest epidemic situation in Portugal, COVID-19 vaccination and the economic news were more prevalent. However, the predominant posts were not consistent with followers' information demands, and the most in-demand information did not generate more engagement. In addition, thematic categories were found to be significantly associated with view frequency and total engagement. Furthermore, a significant difference in thematic categories was identified among the four developmental stages, which in turn was related to the overall engagement of posts. The COVID-19 official case counts in Portugal are predictive of post frequency, view frequency and total engagement. The results of thisstudy support the view that social media provided diverse information sources for the Chinese community during the ongoing COVID-19 pandemic. However, it is evidently clear from the findings that communicators have to leverage the characteristics of social media not only for delivering real-time news but also to gratify public information needs and attract more followers.

Antecedents of technological readiness in times of crises: A comparison between before and during COVID-19

We examine how individual characteristics of employees such as digital self-efficacy, workforce agility, innovativeness, and commitment to change influence technological readiness in different stages of a crisis, i.e., before a crisis and during a crisis. We carried out a fuzzy set qualitative comparative analysis (fsQCA) on data from 2892 employees representing companies across several sectors and countries. Our results show that specific characteristics of employees can be beneficial for reaching technological readiness in organisations before a crisis and during a crisis. Our results, e.g., show that digital self-efficacy has a differential impact on technological readiness prior to a crisis and during a crisis while workforce agility is essential for both phases.

Risk of adverse outcomes in inflammatory bowel disease patients infected with SARS-CoV-2: a systematic review and meta-analysis.

BACKGROUND: Between people with and without inflammatory bowel disease (IBD), there was no statistically significant difference in the probability of contracting the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). However, the risk of adverse outcomes in IBD patients after virus infection remains unclear. METHODS: Eligible studies conducted from January 1, 2020 to March 17, 2022 were obtained by searching PubMed, Embase, and Web of Science. Information was collected in tables from the included studies. Random-effects and fixed-effects models were used as measures for the pooled estimates. All data were estimated by R version 4.1.3. RESULTS: Twenty-four studies were included. The risk ratio (RR) of adverse outcomes in COVID-19 patients with IBD increased by 32% (RR 1.32; 95% CI 1.06-1.66) relative to COVID-19 patients without IBD. The RR of mortality was higher in COVID-19 patients with IBD from Europe (RR 1.72; 95% CI 1.11-2.67) than in those that were not from Europe (RR 1.00; 95% CI 0.79-1.26; χ2 = 4.67; P = 0.03). Patients with ulcerative colitis were at higher risk of adverse outcomes after SARS-CoV-2 infection than patients with Crohn's disease patients (RR1.38; 95% CI 1.27-1.50). The IBD drugs treatment was associated with the risk of adverse outcomes, the pooled odds ratio (OR) of mesalazine (1.79; 95% CI 1.59-2.02), immunomodulators (1.30; 95% CI 1.10-1.53), and anti-TNF (0.47; 95% CI 0.41-0.53) were assessed. CONCLUSION: COVID-19 patients with IBD had an increased risk of adverse outcomes than those without IBD, whereas anti-TNF treatment might reduce the risk.

Learning Clinical Concepts for Predicting Risk of Progression to Severe COVID-19 (preprint)

With COVID-19 now pervasive, identification of high-risk individuals is crucial. Using data from a major healthcare provider in Southwestern Pennsylvania, we develop survival models predicting severe COVID-19 progression. In this endeavor, we face a tradeoff between more accurate models relying on many features and less accurate models relying on a few features aligned with clinician intuition. Complicating matters, many EHR features tend to be under-coded, degrading the accuracy of smaller models. In this study, we develop two sets of high-performance risk scores: (i) an unconstrained model built from all available features; and (ii) a pipeline that learns a small set of clinical concepts before training a risk predictor. Learned concepts boost performance over the corresponding features (C-index 0.858 vs. 0.844) and demonstrate improvements over (i) when evaluated out-of-sample (subsequent time periods). Our models outperform previous works (C-index 0.844-0.872 vs. 0.598-0.810).

CFD Numerical Simulation in Building Drainage Stacks as an Infection Pathway of COVID-19.

Being aware of global pandemics, this research focused on the potential infection routes in building drainage systems. Case studies have found that dysfunctional building drainage systems not only failed to block contaminants but also potentially became a route for the spreading of viruses. Several fluid simulations in pipelines were conducted in this research using COMSOL Multiphysics. In particular, virus transmission from one patient's room to other uninfected residential units through pipelines was visualized. A 12-story building, which is commonly seen in the local area, was designed as a simulation model to visualize the transmission and analyze its hazards. Furthermore, five environmental factors were filtered out for discussion: distance, time span, pressure, initial concentration, and environment temperature. By manipulating these factors, the relationship between the factors and the behavior of the contaminant could be explored. In addition, a simulation with a different pipeline arrangement was included to observe the virus diffusion behavior under different scenarios. The visualized simulation concluded that the contaminant would spread through the drainage system and arrive at the neighboring four floors within an hour under the circumstances of a 12-story building with broken seals and constant pressure and contaminant supply on the seventh floor. Meanwhile, the whole building would be exposed to infection risks by the continuous virus spreading through a drainage system. Distance, time span, and pressure were considered critical factors that affected indoor contamination in the system. On the other hand, initial concentration and environmental temperature did not have significant roles. Visualizing the behavior of viruses provides a glimpse of what happens behind walls, paving the way for recognizing the importance of maintaining functional drainage systems for individuals' health.

A semi-supervised learning approach for COVID-19 detection from chest CT scans.

COVID-19 has spread rapidly all over the world and has infected more than 200 countries and regions. Early screening of suspected infected patients is essential for preventing and combating COVID-19. Computed Tomography (CT) is a fast and efficient tool which can quickly provide chest scan results. To reduce the burden on doctors of reading CTs, in this article, a high precision diagnosis algorithm of COVID-19 from chest CTs is designed for intelligent diagnosis. A semi-supervised learning approach is developed to solve the problem when only small amount of labelled data is available. While following the MixMatch rules to conduct sophisticated data augmentation, we introduce a model training technique to reduce the risk of model over-fitting. At the same time, a new data enhancement method is proposed to modify the regularization term in MixMatch. To further enhance the generalization of the model, a convolutional neural network based on an attention mechanism is then developed that enables to extract multi-scale features on CT scans. The proposed algorithm is evaluated on an independent CT dataset of the chest from COVID-19 and achieves the area under the receiver operating characteristic curve (AUC) value of 0.932, accuracy of 90.1%, sensitivity of 91.4%, specificity of 88.9%, and F1-score of 89.9%. The results show that the proposed algorithm can accurately diagnose whether a chest CT belongs to a positive or negative indication of COVID-19, and can help doctors to diagnose rapidly in the early stages of a COVID-19 outbreak.

CFD Numerical Simulation in Building Drainage Stacks as an Infection Pathway of COVID-19

Being aware of global pandemics, this research focused on the potential infection routes in building drainage systems. Case studies have found that dysfunctional building drainage systems not only failed to block contaminants but also potentially became a route for the spreading of viruses. Several fluid simulations in pipelines were conducted in this research using COMSOL Multiphysics. In particular, virus transmission from one patient's room to other uninfected residential units through pipelines was visualized. A 12-story building, which is commonly seen in the local area, was designed as a simulation model to visualize the transmission and analyze its hazards. Furthermore, five environmental factors were filtered out for discussion: distance, time span, pressure, initial concentration, and environment temperature. By manipulating these factors, the relationship between the factors and the behavior of the contaminant could be explored. In addition, a simulation with a different pipeline arrangement was included to observe the virus diffusion behavior under different scenarios. The visualized simulation concluded that the contaminant would spread through the drainage system and arrive at the neighboring four floors within an hour under the circumstances of a 12-story building with broken seals and constant pressure and contaminant supply on the seventh floor. Meanwhile, the whole building would be exposed to infection risks by the continuous virus spreading through a drainage system. Distance, time span, and pressure were considered critical factors that affected indoor contamination in the system. On the other hand, initial concentration and environmental temperature did not have significant roles. Visualizing the behavior of viruses provides a glimpse of what happens behind walls, paving the way for recognizing the importance of maintaining functional drainage systems for individuals' health.

When telecommuters are willing to be good soldiers during COVID-19.

COVID-19 pandemic can be regarded as a game changer, it has changed the way people work or live. How has the telecommuter's psychology changed under coronavirus? Accordingly, this study contributes to clarify the relationships among telecommuter's organizational citizenship behavior, happiness, work-family conflict, and job performance under COVID-19. The first purpose of present study is to evaluate the impacts of telecommuter's organizational citizenship behavior. To explore the roles of happiness and work-family conflict, the second purpose is to explore the relationships among the organizational citizenship behavior, happiness, and work-family conflict. In addition, the influences of telecommuter's happiness and work-family conflict on job performance deserve further consideration. To assess the applicability of this conceptual model, this study develops a questionnaire and distributed it to a sample consisted of telecommuters of firms. The statistical techniques adopt contain descriptive statistics, factor analysis, reliability analysis, structural equation modeling (SEM), and fuzzy set qualitative comparative analysis (fsQCA). Based on the empirical analyses, telecommuter's extra-role organizational citizenship behavior enhances in-role job performance, telecommuter's organizational citizenship also associates with happiness and work-family conflict. Both happiness and work-family conflict associate with the job performance. In addition, there are three causal configurations found to be sufficient for high job performance.

A Simulation-Based Evaluation of a Cargo-Hitching Service for E-Commerce Using Mobility-on-Demand Vehicles

Time-sensitive parcel deliveries—shipments requested for delivery in a day or less—are an increasingly important aspect of urban logistics. It is challenging to deal with these deliveries from a carrier perspective. These require additional planning constraints, preventing the efficient consolidation of deliveries that is possible when demand is well known in advance. Furthermore, such time-sensitive deliveries are requested to a wider spatial scope than retail centers, including homes and offices. Therefore, an increase in such deliveries is considered to exacerbate negative externalities, such as congestion and emissions. One of the solutions is to leverage spare capacity in passenger transport modes. This concept is often denominated as cargo hitching. While there are various system designs, it is crucial that such a solution does not deteriorate the quality of service of passenger trips. This research aims to evaluate the use of mobility-on-demand (MOD) services that perform same-day parcel deliveries. To test the MOD-based solutions, we utilize a high-resolution agent- and activity-based simulation platform of passenger and freight flows. E-commerce demand carrier data collected in Singapore are used to characterize simulated parcel delivery demand. We explore operational scenarios that aim to minimize the adverse effects of fulfilling deliveries with MOD service vehicles on passenger flows. Adverse effects are measured in fulfillment, wait, and travel times. A case study on Singapore indicates that the MOD services have potential to fulfill a considerable amount of parcel deliveries and decrease freight vehicle traffic and total vehicle kilometers travelled without compromising the quality of MOD for passenger travel. Insights into the operational performance of the cargo-hitching service are also provided.

Study on the Correlation Between Indoor Light Environment and Human Fatigue

Due to the continuing impact of COVID-19, people spend an increasing amount of time on working or studying from home. The indoor light environment became quite important since it can affect people's physical and mental health. In order to reduce human fatigue resulting from continuous indoor working or studying and to improve work efficiency, and also hope to contribute to the research of indoor light environment design, this paper explores the correlation between indoor light environments and fatigue. Through laboratory simulation of indoor light environment. Participants are asked to complete the task stimulation test and filled in the subjective fatigue questionnaire with three different illumination levels. Their EEG (ElectroEncephaloGraphy), eye movement, and other physiological data are also monitored at the same time. The participants’ fatigue degree is statistically analyzed under the 300 lx, 570 lx, and 870 lx illumination. The results showed that the lighting environment has a strong correlation with human fatigue. Fatigue degree varies the most from 570 to 870 lx. There is a largest error rate gap of task test up to 20% under 300 lx and 870 lx illumination. As the illuminance increases, the fatigue degree has a visible trend of increase as well, and it is the most obvious under the 870 lx illumination. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Artificial Intelligence-Enabled Electrocardiography Predicts Left Ventricular Dysfunction and Future Cardiovascular Outcomes: A Retrospective Analysis.

BACKGROUND: The ejection fraction (EF) provides critical information about heart failure (HF) and its management. Electrocardiography (ECG) is a noninvasive screening tool for cardiac electrophysiological activities that has been used to detect patients with low EF based on a deep learning model (DLM) trained via large amounts of data. However, no studies have widely investigated its clinical impacts. OBJECTIVE: This study developed a DLM to estimate EF via ECG (ECG-EF). We further investigated the relationship between ECG-EF and echo-based EF (ECHO-EF) and explored their contributions to future cardiovascular adverse events. METHODS: There were 57,206 ECGs with corresponding echocardiograms used to train our DLM. We compared a series of training strategies and selected the best DLM. The architecture of the DLM was based on ECG12Net, developed previously. Next, 10,762 ECGs were used for validation, and another 20,629 ECGs were employed to conduct the accuracy test. The changes between ECG-EF and ECHO-EF were evaluated. The primary follow-up adverse events included future ECHO-EF changes and major adverse cardiovascular events (MACEs). RESULTS: The sex-/age-matching strategy-trained DLM achieved the best area under the curve (AUC) of 0.9472 with a sensitivity of 86.9% and specificity of 89.6% in the follow-up cohort, with a correlation of 0.603 and a mean absolute error of 7.436. In patients with accurate prediction (initial difference < 10%), the change traces of ECG-EF and ECHO-EF were more consistent (R-square = 0.351) than in all patients (R-square = 0.115). Patients with lower ECG-EF (≤35%) exhibited a greater risk of cardiovascular (CV) complications, delayed ECHO-EF recovery, and earlier ECHO-EF deterioration than patients with normal ECG-EF (>50%). Importantly, ECG-EF demonstrated an independent impact on MACEs and all CV adverse outcomes, with better prediction of CV outcomes than ECHO-EF. CONCLUSIONS: The ECG-EF could be used to initially screen asymptomatic left ventricular dysfunction (LVD) and it could also independently contribute to the predictions of future CV adverse events. Although further large-scale studies are warranted, DLM-based ECG-EF could serve as a promising diagnostic supportive and management-guided tool for CV disease prediction and the care of patients with LVD.

Vaccination with SARS-CoV-2 spike protein lacking glycan shields elicits enhanced protective responses in animal models.

A major challenge to end the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is to develop a broadly protective vaccine that elicits long-term immunity. As the key immunogen, the viral surface spike (S) protein is frequently mutated, and conserved epitopes are shielded by glycans. Here, we revealed that S protein glycosylation has site-differential effects on viral infectivity. We found that S protein generated by lung epithelial cells has glycoforms associated with increased infectivity. Compared to the fully glycosylated S protein, immunization of S protein with N-glycans trimmed to the mono-GlcNAc-decorated state (SMG) elicited stronger immune responses and better protection for human angiotensin-converting enzyme 2 (hACE2) transgenic mice against variants of concern (VOCs). In addition, a broadly neutralizing monoclonal antibody was identified from SMG-immunized mice that could neutralize wild-type SARS-CoV-2 and VOCs with subpicomolar potency. Together, these results demonstrate that removal of glycan shields to better expose the conserved sequences has the potential to be an effective and simple approach for developing a broadly protective SARS-CoV-2 vaccine.