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Mental stress has been recognized as an essential risk factor for hypertension. Therefore, experts specializing in cardiology, psychiatry, and Traditional Chinese Medicine organized by the Psycho-cardiology Group, College of Cardiovascular Physicians of Chinese Medical Doctor Association, and Hypertension Group of the Chinese Society of Cardiology proposed the expert consensus on the diagnosis and treatment of adult mental stress-induced hypertension in March 2021, which includes the epidemiology, etiology, diagnosis, and treatment of the mental stress-induced hypertension. This consensus will hopefully facilitate the clinical practice of this disorder. In addition, the COVID-19 pandemic has become one of the primary global sources of psychosocial stressors since the beginning of 2020, and the revision of this expert consensus in 2022 has increased the relevant content. This consensus consists of two parts. The sections of Part A include (I) Background and epidemiological characteristics, (II) Pathogenesis, and (III) Diagnosis. The sections of Part B contain (IV) Treatment recommendations, and (V) Prospects. This article presents Part B of the consensus. © 2022 Heart and Mind ;Published by Wolters Kluwer - Medknow.
ABSTRACT
Mental stress has been recognized as an essential risk factor for hypertension. Therefore, experts specializing in cardiology, psychiatry, and Traditional Chinese Medicine organized by the Psycho-Cardiology Group of College of Cardiovascular Physicians of Chinese Medical Doctor Association and Hypertension Group of Chinese Society of Cardiology proposed the expert consensus on the diagnosis and treatment of adult mental stress-induced hypertension in March 2021, which includes the epidemiology, etiology, diagnosis, and treatment of the mental stress-induced hypertension. This consensus will hopefully facilitate the clinical practice of this disorder. In addition, the COVID-19 pandemic has become one of the primary global sources of psychosocial stressors since the beginning of 2020, and the revision of this expert consensus in 2022 has increased the relevant content. This consensus consists of Part A and Part B. Part A includes (I) Background and epidemiological characteristics, (II) Pathogenesis, and (III) Diagnosis and Part B includes (IV) Treatment recommendations and (V) Prospects. This part presents the content of Part A. © 2022 Heart and Mind ;Published by Wolters Kluwer - Medknow.
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Online discussions are abundant with opinions towards a common topic, and identifying (dis)agreement between a pair of comments enables many opinion mining applications. Realizing the increasing needs to analyze opinions for emergent new topics that however tend to lack annotations, we present the first meta-learning approach for few-shot (dis)agreement identification that can be quickly applied to analyze opinions for new topics with few labeled instances. Furthermore, we enhance the meta-learner's domain generalization ability from two perspectives. The first is domain-invariant regularization, where we design a lexicon-based regularization loss to enable the meta-learner to learn domain-invariant cues. The second is domain-aware augmentation, where we propose domain-aware task augmentation for meta-training to learn domain-specific expressions. In addition to using an existing dataset, we also evaluate our approach on two very recent new topics, mask mandate and COVID vaccine, using our newly annotated datasets containing 1.5k and 1.4k SubReddits comment pairs respectively. Extensive experiments on three domains/topics demonstrate the effectiveness of our meta-learning approach. © 2022 Association for Computational Linguistics.
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Research on student engagement has recently gained popularity as it can address problems such as early dropout and poor achievement. The growing interest in investigating student engagement during the Covid-19 pandemic is reflected in increased publications addressing this topic. However, no review provided research evidence and an overview of existing literature on student engagement during emergency remote teaching (ERT). We reviewed how student engagement studies were undertaken during ERT from three perspectives: (1) the landscape of studies, (2) methodologies issues, and (3) the strategies used to facilitate student engagement. 42 articles were analysed from an initial pool of 436 search results. The findings illustrate that current studies were predominately undertaken in the United States (36%) and China (22%) with focusing on STEM subjects as a dominant discipline. The literature was largely inconsistent in defining and measuring student engagement. In addition, the majority of studies (57%) investigated students' engagement from the perspective of students, unlike other stakeholders. The most prominent finding is that ERT promoted several important engagement strategies, including motivational factors, teachers' facilitation, a hybrid learning model, and using learning technologies to boost students' engagement. © 2023, The Author(s).
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Along with the development of edge computing and Artificial Intelligence (AI), there has been an explosion of health-care system. As COVID-19 spread globally, the pandemic created significant challenges for the global health system. Therefore, we proposed an edge-based framework for risk assessment of communicable disease called CDM-FL. The CDM-FL consists of two modules, the common data model (CDM) and federated learning (FL). The CDM can process and store multi-source heterogeneous data with standardized semantics and schema. This provides more data for model training using medical data globally. The model is deployed on edge nodes that can measure patients' status locally and with low latency. It also keeps patient privacy from being disclosed that patient are more likely to share their medical data. The results based on real-world data show that CDM-FL can help physicians to evaluate the risk of communicable disease as well as save lives during severe epidemic situations. © 2022 IEEE.
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Background:Coronavirus disease 2019 (COVID-19) is an emerging infectious disease and has spread worldwide. Clinical risk factors associated with the severity in COVID-19 patients have not yet been well delineated. The aim of this study was to explore the risk factors related with the progression of severe COVID-19 and establish a prediction model for severity in COVID-19 patients.Methods:We retrospectively recruited patients with confirmed COVID-19 admitted in Enze Hospital, Taizhou Enze Medical Center (Group) and Nanjing Drum Tower Hospital between January 24 and March 12, 2020. Take the Taizhou cohort as the training set and the Nanjing cohort as the validation set. Severe case was defined based on the World Health Organization Interim Guidance Report criteria for severe pneumonia. The patients were divided into severe and non-severe groups. Epidemiological, laboratory, clinical, and imaging data were recorded with data collection forms from the electronic medical record. The predictive model of severe COVID-19 was constructed, and the efficacy of the predictive model in predicting the risk of severe COVID-19 was analyzed by the receiver operating characteristic curve (ROC).Results:A total of 402 COVID-19 patients were included in the study, including 98 patients in the training set (Nanjing cohort) and 304 patients in the validation set (Nanjing cohort). There were 54 cases (13.43%) in severe group and 348 cases (86.57%) in non-severe group. Logistic regression analysis showed that body mass index (BMI) and lymphocyte count were independent risk factors for severe COVID-19 (all P < 0.05). Logistic regression equation based on risk factors was established as follows: Logit (BL)=-5.552-5.473 ×L + 0.418 × BMI. The area under the ROC curve (AUC) of the training set and the validation set were 0.928 and 0.848, respectively (all P < 0.001). The model was simplified to get a new model (BMI and lymphocyte count ratio, BLR) for predicting severe COVID-19 patients, and the AUC in the training set and validation set were 0.926 and 0.828, respectively (all P < 0.001).Conclusions:Higher BMI and lower lymphocyte count are critical factors associated with severity of COVID-19 patients. The simplified BLR model has a good predictive value for the severe COVID-19 patients. Metabolic factors involved in the development of COVID-19 need to be further investigated. © 2021 The Chinese Medical Association, Published by Wolters Kluwer Health, Inc.
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As a typical representative of the regional economies' integration, the Yangtze River Delta region presents the development trend of emergency logistics integration under the background of the global epidemic of COVID-19, especially the outbreak in Shanghai. A scientific evaluation of the integration level of regional emergency logistics is crucial to the accurate construction of a post-epidemic emergency logistics system in the Yangtze River Delta region. This paper defines regional integration of emergency logistics as two dimensions of high-quality development and equilibrium development, and constructs a regional emergency logistics integration level evaluation index system containing 14 indicators for four factors: emergency logistics infrastructure, resource support, information sharing and mechanisms. A two-stage evaluation model is used to evaluate the integration level of emergency logistics in the Yangtze River Delta region, and the results are compared with the Beijing-Tianjin-Hebei region. According to the results, the integration of emergency logistics in the Yangtze River Delta region is at a medium level, with the highest integration level of emergency logistics infrastructure, the lowest integration level of emergency logistics information sharing, and the medium integration level of emergency logistics resource support and emergency logistics institutional mechanism. The density of integrated transport network and the efficiency of single-vehicle freight completion have the highest and lowest integration levels in the Yangtze River Delta region, respectively. And the integrated development level of emergency logistics in the Yangtze River Delta region is better than that in the Beijing-Tianjin-Hebei region, but there is little difference between the two, mainly due to the high level of integration of emergency logistics infrastructure and emergency logistics resource support. © 2022 IEEE.
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Study Objective To evaluate success of universal SDD after minimally invasive hysterectomy. The COVID pandemic presented a unique scenario in which universal SDD was implemented abruptly across study institutions. This allowed for evaluation of patients with characteristics under-represented in SDD literature: large uteri due to leiomyoma, obesity defined as body mass index (BMI) ≥30, and later surgical end time. Design Retrospective chart review with before/after study design comparing pre-COVID to COVID cohorts. Setting High-volume, academic and academic-affiliated medical centers. Due to COVID, in the after-cohort, surgery could only be scheduled if SDD was planned. Patients or Participants Patients undergoing benign, laparoscopic or robotic-assisted hysterectomy during two 11-month periods: September 2018-July 2019 and May 2020-March 2021. Interventions Minimally invasive hysterectomy performed by three Minimally Invasive Gynecologic Surgeons. Measurements and Main Results 320 patients met inclusion criteria, 107 pre-COVID and 213 COVID. Mean age for both groups was 44.9. Patients were predominately non-Hispanic Black (40.2% pre- vs. 34.7% COVID) and non-Hispanic White (55.1% pre- vs. 63.4% COVID). Mean BMI was 33 for both groups. Pre-COVID, 2% of patients were discharged same day, whereas COVID 92% were discharged same day. Mean specimen weight was 478.2gm vs. 436.3gm for the two periods. In the COVID cohort, there was no difference in SDD success based on BMI (p 0.678), BMI <30 (49.5%), 30-39.9 (29.1%), 40-49.9 (15.3%), and ≥50 (6.1%). There was no difference in SDD success by specimen weight (p 0.077) stratified as <250gm (48.5%), 250-499gm (15.3%), or ≥500gm (36.2%). SDD success was not dependent on surgical end time (p 0.678) with end time stratified into ≤12:00 (45.4%), 12:01-14:59 (35.7%), and ≥15:00 (18.9%). There were no re-admissions in either cohort. Conclusion Abrupt transition to SDD is safe and feasible, including for patients with obese BMI and enlarged uterus. SDD success was not affected by later surgical end time.
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The COVID-19 pandemic has forced schools to close and shift to remote education. However, this might create new challenges, as students might have poor self-directed learning skills to keep up with the learning process from home. Although many studies have focused on remote education during said pandemic, there is limited information on the strategies implemented to support and encourage self-directed learning and assessment. Therefore, in this study – focusing on a case in China – focus group interviews were conducted to collect data from different stakeholders on the implemented self-directed learning strategies during the COVID-19 pandemic. The results might help different education stakeholders in future to effectively maintain education in crises, leading to better learning outcomes. © Italian e-Learning Association.
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Massive Open Online Courses (MOOCs) have been around for some time, but several studies highlighted different issues associated with them, including quality. The COVID-19 pandemic catalyzed their second blooming, where MOOCs have seen a surge in enrollments since March 2020. This study intended to explore how this enrollment reflected on the research studies included in scientific publications, indexed by Web of Science. Specifically, the bibliometric mapping analyses of 108 studies have revealed an ongoing trend in the countries contributing to the MOOCs research, namely USA, China, UK and Spain. Additionally, MOOCs research coming from US, UK and other western countries was decreasing before the pandemic and showed a continuous dramatic reduction also during the COVID-19 pandemic. Growing attention in MOOCs research among less represented countries was also observed. Besides, most of the topics focused on by MOOCs research during the pandemic were mainly related to education and engineering. © 2022. Turkish Online Journal of Distance Education. All Rights Reserved.
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This study aims to explore Chinese residents' outbound travel intentions and preparations in the post-pandemic world that are influenced by media coverage and risk perception. A conceptual model is proposed to test the structural relationships among media coverage, risk perception, outbound travel intentions and preparations. This study administered an online survey to Chinese residents who had outbound travel experiences, and a total of 441 valid responses were collected for data analysis. The results indicated that media coverage exerted significant impact on cognitive and affective risk perceptions, outbound travel intentions and preparations. Furthermore, cognitive risk perception was positively related to affective risk perception, which significantly influenced outbound travel intentions and preparations. Outbound travel intentions were verified as the determinant of outbound travel preparations. Additionally, the mediating roles of affective risk perception and outbound travel intentions were confirmed. This study is amongst the first to introduce the concept of outbound travel preparations as a new research avenue for post-pandemic outbound travel behaviour.
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The COVID-19 pandemic has a significant impact on renewable energy. This work investigates the effect of pandemic on the renewable energy research from four aspects: the regional cooperation model of renewable energy research, the research hotspots of renewable energy during the pandemic, the development trend of renewable energy research hotspots in the post-pandemic, policy recommendations for development in the postepidemic era. Systematic literature review (SLR), latent semantic analysis (LSA), and machine learning-based analysis (principle component analysis) are used to analyze the relevant literature on the COVID-19 and renewable energy in the Scopus database. The results of geographic visualization analysis show the COVID-19 pandemic has not hindered but promoted bilateral cooperation in the field of renewable energy among the " the Belt and Road " partner countries, with China at the core. The results of visual analysis of research hotspots show the research in the field of renewable energy during pandemics is divided into two categories: "opportunities" and "crisis", and further obtained five categories: sustainable development, environmental management, carbon emission, solar photovoltaic power, and wind power. The results of the keyword evolution map indicate the two main directions of renewable energy research in the post-pandemic: (1) Clean energy investment has become an important measure to revitalize the economy after the epidemic. (2) Energy efficiency research will effectively promote the sustainable development of renewable energy. Finally, we put forward policy suggestions on how to build a smart energy system in the post-epidemic era.
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In the version of this article initially published, the first name of Chuansheng Zheng was misspelled as Chuangsheng. The error has been corrected in the HTML and PDF versions of the article. © The Author(s) 2022.
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Background. Few studies reported the risk factors of fatal outcome of hospitalized patients with coronavirus disease 2019 (COVID-19). We aimed to identify the independent risk factors associated with fatal outcome of hospitalized COVID-19 patients. Methods. The clinical data of 109 consecutive COVID-19 patients including 40 (36.7%) common cases and 69 (63.3%) severe cases were included and analyzed. Results: Multivariate regression analysis indicated that platelets (PLT, OR, 0.988;95% CI, 0.978-0.998;P=0.017) and C-reactive protein (CRP) (OR, 1.047;95% CI, 1.026-1.068;P<0.001) levels were the independent risk factors of fatal outcome in COVID-19 patients. The optimal cut-off value of PLT counts for predicting fatal outcome was 161x109/L with the area under receiver operating characteristic curve (AUROC) of 0.824 (95% CI, 0.739-0.890). The optimal cut-off value of CRP for the prediction of fatal outcome was 46.2 mg/L with the AUROC of 0.954 (95% CI, 0.896-0.985). The CRP levels had higher predictive values for fatal outcome than PLT (P=0.016). The cumulative survival rate was significantly higher in patients with PLT>161x10(9)/L compared with patients with PLT <= 161x10(9)/L (89.4% vs. 12.5%, log-rank test chi(2)=72.17;P<0.001). Survival rate of COVID-19 patients was prominently higher in CRP <= 46.2 mg/L patients compared with patients with CRP>46.2 mg/L (95.9% vs. 22.9%, log-rank test chi(2)=77.85;P<0.001). Conclusions. PLT counts and CRP levels could predict fatal outcome of hospitalized COVID-19 patients with relatively high accuracy.
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BACKGROUND: The follow-up data of discharged patients with coronavirus disease 19 (COVID-19) have not yet been fully analyzed and reported. This study aimed to evaluate the clinical features, test results, and outcomes of COVID-19 patients after discharge. METHODS: 149 COVID-19 patients with follow-up data after discharge were included. Post-hospitalization data related to clinical features and outcomes were obtained by following the patients up to 6 weeks. RESULTS: The COVID-19 patients were followed for a median of 28.0 days (range of 22 days to 42 days) after discharge from hospital. At the end of follow-up, four patients (2.7%) still had cough. The proportions of leukopenia and lymphopenia were 7.4% and 4.7%, respectively. The proportions of ALT, AST, and Cr abnormalities were 26.2%, 6.0%, and 0%, respectively. Abnormal chest CT was detected in 94 (63.1%) patients, including 14 (9.4%) unilateral pneumonia and 80 (53.7%) bilateral pneumonia. However, the proportion of chest CT abnormality significantly decreased compared to that at the time of admission. CONCLUSIONS: One month after discharge, few patients with COVID-19 had clinical symptoms;however, a substantial proportion of COVID-19 patients harbored abnormal laboratory and radiological examinations. Moderately long-term medical follow-up would justifiably benefit COVID-19 patients after discharge.
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Background The COVID-19 pandemic has brought significant challenges to clinicians caring for liver transplant (LT) recipients. Researchers have sought to better understand the risk and clinical outcomes of LT recipients infected with COVID-19 globally, however, there is a paucity of data from within Canada. Aims Our multi-center study aims to examine the characteristics and clinical outcomes of LT patients with COVID-19 in Canada. Methods We identified a retrospective cohort of adult LT recipients with RT-PCR confirmed COVID-19 from 7 Canadian tertiary care centers between March 2020 and June 2021. Demographic and clinical data were compiled by clinicians within those centers. We identified liver enzyme profile at the time of COVID-19 infection, immunosuppression type and post-infection adjustments, rate of hospitalization, ICU admission, mechanical ventilation, and death. Results A total of 49 patients with a history of LT and COVID-19 infection were identified. Twenty nine patients (59%) were male, the median time from LT was 66 months (1, 128) and the median age at COVID-19 infection was 59 years (52, 65). At COVID-19 diagnosis, the median ALT was 37 U/L (21, 41), AST U/L was 34 (20, 37), ALP U/L was 156 (88, 156), Total Bilirubin was 11 umol/L (7, 14), and INR was 1.1 (1.0, 1.1). The majority of patients (92%) were on tacrolimus monotherapy or a combination of tacrolimus and mycophenolate mofetil (MMF);median tacrolimus level at COVID-19 diagnosis was 5.3 ug/L (4.0, 8.1). Immunosuppression was modified in 8 (16%) patients post-infection;either the tacrolimus dose was reduced or MMF was held. One patient developed acute cellular rejection which recovered after re-initiation of the prior regimen. Eighteen patients (37%) required hospitalization, 6 (12%) were treated with dexamethasone, and 3 (6%) required ICU admission and mechanical ventilation. Four patients (8%) died due to complications of COVID-19. On univariate analysis, neither age, sex, co-morbidities nor duration post-transplant were associated with risk of hospitalization. Conclusions In our national retrospective study, approximately 40% of patients required hospitalization with a mortality rate of < 10%. Previous studies have shown proximity to LT as an independent factor for mortality with COVID-19;the median time from LT for our patients was 5 years, which may explain the lower mortality rate. Of note, the median tacrolimus levels were much lower in comparison to the target of 8–10 ug/L used in the first year post-transplant. As the landscape of COVID-19 changes with vaccination, evolving treatments, and increasing rates of variant transmission, additional studies are required to continue identifying trends in clinical outcomes. Funding Agencies None
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Background: The COVID-19 pandemic interfered with delivery of childhood weight management programs. Get Up & Go is a community group program for children 6-14 years with BMI≥85th%ile and their families that provides fun learning about healthy nutrition, physical activity, and behavior change at no cost to families. The program is effective in improving %BMIp95, reported healthy lifestyle, and physical endurance. This study evaluates the participation and effect of a virtual delivery option offered starting winter 2021. Methods: Groups of 5-12 families met in-person at a YMCA or via synchronous virtual delivery. Parents chose setting. Each of the 10 weekly lessons lasted 60-90 minutes. Data include demographics and pre-and post-measured weights, heights, and parent-completed behavior assessment questionnaires (BAQ), with score range of 0-100, higher indicating healthier behavior. Graduation criterion is attendance at 6 of 9 non-orientation classes. Results: Among the registered families, 46 of 82 (56%) who chose virtual actually attended vs 40 of 56 (71%) who chose in-person (p = 0.07). Baseline characteristics of attenders did not differ (we report virtual, then in-person): mean age (SD) 11.1 (2.5) vs 11.1 (2.2) years, male 29 (63.0%) vs 23 (57.5%), Spanish-speaking 18 (39.1%) vs 12 (31.6%), severe obesity (≥120% BMIp95) in 39 (84.8%) vs 30 (75.0%), and baseline BAQ scores 34.9 (13.2) vs 37.2 (12.1). Virtual participants attended more classes than in-person participants: 7.3 (2.3) vs 6.1 (2.9), p = 0.04. More virtual participants met graduation criterion: 35 (87.5%) vs 24 (63.2%), p = 0.01. Among graduates with post-measures, mean change in %BMIp95 was -3.27 (6.20) for n = 32 virtual vs -1.09 (3.84) for n = 23 in-person, p = 0.11, and mean BAQ increase was 15.4 (13.1) for n = 34 virtual vs 11.4 (10.6) for n = 21 in-person, p = 0.25. Conclusions: The synchronous, group virtual delivery of the Get Up & Go program engaged similar participants, with higher attendance and no difference in %BMIp95 and BAQ outcomes, compared with contemporaneous in-person delivery. Continued virtual delivery option could expand the availability of this program without compromising effect.