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1.
JAMA Network Open ; 5(9):e2231790, 2022.
Article in English | MEDLINE | ID: covidwho-2027281

ABSTRACT

Importance: Relatively little is known about the persistence of symptoms in patients with COVID-19 for more than 1 year after their acute illness. Objective: To assess the health outcomes among hospitalized COVID-19 survivors over 2 years and to identify factors associated with increased risk of persistent symptoms. Design, Setting, and Participants: This was a longitudinal cohort study of patients who survived COVID-19 at 2 COVID-19-designated hospitals in Wuhan, China, from February 12 to April 10, 2020. All patients were interviewed via telephone at 1 year and 2 years after discharge. The 2-year follow-up study was conducted from March 1 to April 6, 2022. Statistical analysis was conducted from April 20 to May 5, 2022. The severity of disease was defined by World Health Organization guideline for COVID-19. Exposures: COVID-19. Main Outcomes and Measures: The main outcome was symptom changes over 2 years after hospital discharge. All patients completed a symptom questionnaire for evaluation of symptoms, along with a chronic obstructive pulmonary disease assessment test (CAT) at 1-year and 2-year follow-up visits. Results: Of 3988 COVID-19 survivors, a total of 1864 patients (median [IQR] age, 58.5 [49.0-68.0] years;926 male patients [49.7%]) were available for both 1-year and 2-year follow-up visits. The median (IQR) time from discharge to follow-up at 2 years was 730 (719-743) days. At 2 years after hospital discharge, 370 patients (19.8%) still had symptoms, including 224 (12.0%) with persisting symptoms and 146 (7.8%) with new-onset or worsening of symptoms. The most common symptoms were fatigue, chest tightness, anxiety, dyspnea, and myalgia. Most symptoms resolved over time, but the incidence of dyspnea showed no significant change (1-year vs 2-year, 2.6% [49 patients] vs 2.0% [37 patients]). A total of 116 patients (6.2%) had CAT total scores of at least 10 at 2 years after discharge. Patients who had been admitted to the intensive care unit had higher risks of persistent symptoms (odds ratio, 2.69;95% CI, 1.02-7.06;P = .04) and CAT scores of 10 or higher (odds ratio, 2.83;95% CI, 1.21-6.66;P = .02). Conclusions and Relevance: In this cohort study, 2 years after hospital discharge, COVID-19 survivors had a progressive decrease in their symptom burden, but those with severe disease during hospitalization, especially those who required intensive care unit admission, had higher risks of persistent symptoms. These results are related to the original strain of the virus, and their relevance to infections with the Omicron variant is not known.

2.
American Journal Of Translational Research ; 14(8):5719-5729, 2022.
Article in English | MEDLINE | ID: covidwho-2027183

ABSTRACT

Patients with major psychiatric disorders (MPD) that include schizophrenia (SCH), bipolar disorder (BP), and major depressive disorder (MDD) are at increased risk for coronavirus disease 2019 (COVID-19). However, the safety and efficacy of COVID-19 vaccines in MPD patients have not been fully evaluated. This study aimed to investigate adverse events (AEs)/side effects and efficacy of COVID-19 vaccines in MPD patients. This retrospective study included 2034 patients with SCH, BP, or MDD who voluntarily received either BBIBP-CorV or Sinovac COVID-19 vaccines, and 2034 matched healthy controls. The incidence of AEs/side effects and the efficacy of COIVD-19 vaccinations among the two groups were compared. The risk ratio (RR) of side effects in patients with MPD was 0.60 (95% confidence interval [CI]: 0.53-0.68) after the first dose and 0.80 (95% CI: 0.65-0.99) following the second dose, suggesting a significantly lower risk in the MPD group versus healthy controls. The RRs of AEs did not differ between patients and controls. Notably, fully vaccinated patients exhibited a decreased risk of influenza with or without fever compared with controls (RR=0.38, 95% CI: 0.31-0.46;RR=0.23, 95% CI: 0.17-0.30;respectively). Further subgroup comparisons revealed a significantly lower risk of influenza with fever in MDD (RR=0.13, 95% CI: 0.08-0.21) and SCH (RR=0.24, 95% CI: 0.17-0.34) than BP (RR=0.85, 95% CI: 0.69-1.06) compared to controls. We conclude that the benefit-risk ratio of COVID-19 vaccination was more favorable in SCH or MDD versus BP when compared with controls. These data indicate that COVID-19 vaccines are safe and protective in patients with MPD from COVID-19.

3.
J Med Virol ; 2022.
Article in English | PubMed | ID: covidwho-2013654

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic caused extensive loss of life worldwide. Further, the COVID-19 and influenza mix-infection had caused great distress to the diagnosis of the disease. To control illness progression and limit viral spread within the population, a real-time reverse-transcription PCR (RT-PCR) assay for early diagnosis of COVID-19 was developed, but detection was time-consuming (4-6 h). METHODS: To improve the diagnosis of COVID-19 and influenza, we herein developed a recombinase polymerase amplification (RPA) method for simple and rapid amplification of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19 and Influenza A (H1N1, H3N2) and B (influenza B). Genes encoding the matrix protein (M) for H1N1, and the hemagglutinin (HA) for H3N2, and the polymerase A (PA) for Influenza B, and the nucleocapsid protein (N), the RNA-dependent-RNA polymerase (RdRP) in the open reading frame 1ab (ORF1ab) region, and the envelope protein (E) for SARS-CoV-2 were selected, and specific primers were designed. We validated our method using SARS-CoV-2, H1N1, H3N2 and influenza B pseudovirus standards and RNA samples extracted from COVID-19 and Influenza A/B (RT-PCR-verified) positive patients. RESULTS: The method could detect SARS-CoV-2 pseudovirus standard DNA quantitatively between 10(2) and 10(5) copies/mL with a log linearity of 0.99 in 22 min. And this method also be very effective in simultaneous detection of H1N1, H3N2 and influenza B. Clinical validation of 100 cases revealed a sensitivity of 100% for differentiating COVID-19 patients from healthy controls when the specificity was set at 90%. CONCLUSION: These results demonstrate that this nucleic acid testing method is advantageous compared with traditional PCR and other isothermal nucleic acid amplification methods in terms of time and portability. This method could potentially be used for detection of SARS-CoV-2, H1N1, H3N2 and influenza B, and adapted for point-of-care (POC) detection of a broad range of infectious pathogens in resource-limited settings. This article is protected by copyright. All rights reserved.

4.
7th International Conference on Business and Industrial Research, ICBIR 2022 ; : 482-487, 2022.
Article in English | Scopus | ID: covidwho-1922663

ABSTRACT

This study intends to define communication science, specifically two-way communication performed by the church through pastors when worship is held online using the digital platforms YouTube and Facebook. Although social media platforms which offer numerous functions and alters the communication style of communicators and communicants has been widely applied in online worship service, however, from available published literature, we still have considerable of unanswered concerns regarding the adaptation of religious institutions during the Covid-19 Pandemic. Therefore, this study aims to discover answers about the question 'How does the Church as a Christian service institution implement two-way communication using the YouTube and Facebook during the Covid-19 Pandemic Period?' using a qualitative technique as well as a literature review. According to the findings of this study, there is a difference in the communication style of the Church to the congregation when they participate in online worship, particularly through digital platforms such as Facebook and YouTube. © 2022 IEEE.

5.
Journal of Transport Geography ; 102, 2022.
Article in English | Scopus | ID: covidwho-1907384

ABSTRACT

Seaports play an important role in the global shipping network. Shipping participants often attach great importance to the measurement of container port connectivity, as it reflects countries' access to world markets. As a result, various port connectivity index systems have been proposed by members of the shipping industry and scholars. In recent years, technological developments especially the advancement of high coverage and real-time Automatic Identification System (AIS) data, have provided a chance to improve the scope and frequency of the existing index systems. An improved system is expected to reflect the dynamic changes in a port's connectivity which may be induced by either local disruptions or shocks in the wider economy. This study builds a monthly container port connectivity index system by applying big data mining techniques, graph theory, and principal component analysis (PCA) to AIS data, taking both port factors and shipping network factors into consideration. AIS records from 2020 are used to calculate the connectivity score of 25 major container ports. We also compare our system with the connectivity index commonly used in the shipping industry, the Liner Shipping Connectivity Index (LSCI). Our results show that the measurement of connectivity can be improved over indices that depend primarily on indicators of traffic volume. Ports like Antwerp and Tanjung Pelepas rank high in the proposed system due to their sound performance on their accessibility and strategic position in the local region instead of their traffic volume. The monthly index system is also proven to reflect timely changes in the shipping industry through its accurate portrayal of changes in port connectivity during the COVID-19 outbreak. © 2022 Elsevier Ltd

6.
Ieee Transactions on Network Science and Engineering ; 9(3):1853-1865, 2022.
Article in English | Web of Science | ID: covidwho-1895933

ABSTRACT

With the development of modern technology, numerous economic losses are incurred by various spreading phenomena. Thus, it is of great significance to identify the initial sources triggering such phenomena. The investigation of source localization in social networks has gained substantial attention and become a popular topic of study. For practical spreading phenomena on social networks, the infection rates are relatively low. Hence, a high uncertainty of spreading trace might be incurred, which further incurs the reduction of localization accuracy obtained through existed source localization methods, especially the observer-based ones. Aiming to solve the source localization problem with a low infection rate, we propose a novel localization algorithm, i.e., path-based source identification (PBSI). First, a small number of nodes are selected and designated as observers. After the propagation process triggered by sources, we can obtain a snapshot. Later, a label is assigned to represent whether a node is infected or not, and observers are supposed to record the paths through which nodes are successfully infected. Based on source centrality theory, observers make the labels flow in the direction recorded during the label iteration process, which ensures the labels of nodes in the direction of the source increase gradually. Extensive experiments indicate that the proposed PBSI can handle source localization problems for both single and multi-source scenarios with better performance than that of state-of-the-art algorithms under different propagation models.

7.
Epidemiology ; 70(SUPPL 1):S306, 2022.
Article in English | EMBASE | ID: covidwho-1854027

ABSTRACT

Background: The psychological well-being of older adults may have been negatively affected by the outbreak of the COVID- 19 epidemic due to the presence of comorbidity, increased risk of complications, mortality, and difficulty in adapting to mhealth and social isolation. The study aimed to investigate the anxiety level of community older adults during the COVID-19 epidemic and explore its associated factors, so that there can be more evidence-based advice to improve the mental health status for the older adults. Methods: Online questionnaires and face to face communication were used to investigate 320 community older adults, who were selected randomly. The questionnaires were used to investigate the sociodemographic characteristics, anxiety and resilience level of the participants. One-way ANOVA, correlation and regression analysis were performed to explore the factors associated with the anxiety among the older adults. Results: The mean of the anxiety among the all participants is 44.03±10.89 and 128 persons (40%) suffer from the anxiety (mild anxiety: 84.38%, moderate anxiety: 14.06%, severe anxiety: 14.06%). The mean of resilience is 56.68±18.26, and the three dimensions of CD-RISC is negative correlation with the anxiety. The SAS can be influenced by the chronic disease history (P=0.045), physical health conditions (P=0.024), economic income (P=0.026), the health education of the COVID-19 epidemic (P<0.001) and the level of resilience (P=0.002). Conclusions: The morbidity and score of the anxiety among the community older adults are higher during the COVID-19 epidemic than the usual. While the score of the CD-RISC is lower than the previous studies. Anxiety emerged as a prominent issue for community- dwelling older adults during the COVID-19 epidemic. Interventions that targeted resilience may have the potential to reduce anxiety level and improve the psychological well-being of the older adults.

8.
Chinese Journal of Environmental Engineering ; 16(4):1068-1073, 2022.
Article in Chinese | Scopus | ID: covidwho-1847721

ABSTRACT

Three technical specifications for centralized treatment engineering of medical waste, which were issued in 2006, have played significant roles in guiding and standardizing the construction and operation of centralized treatment engineering of medical waste in over ten years period. However, with development of industry and upgrading of technologies, especially after the coronavirus disease 2019 (COVID-19) epidemic, the medical waste disposal industry faces new opportunities and challenges, and the construction and operation of the centralized treatment engineering of medical waste needs some adjustments. Under such circumstances, revised three technical specifications were issued and implemented in April 2021. Based on the review of the implementation situations of the technical specifications and the development status of the industry, this study analyzed the necessity of the revision of the technical specifications, and explained the revision ideas of the three technical specifications in terms of construction scale, disinfection treatment technical requirements, pollution control technical requirements and disinfection effect detection frequency. Moreover, to promote the implementation of the revised specifications, suggestions were put forward on clarifying the application scenarios, the technical positioning and the legal effect of the specifications. This study can provide a reference for the construction and operation of medical waste disinfection centralized treatment project in the new era. © 2022, Science Press. All right reserved.

9.
19th IEEE International Symposium on Biomedical Imaging, ISBI 2022 ; 2022-March, 2022.
Article in English | Scopus | ID: covidwho-1846116

ABSTRACT

Automatic medical report generation is an emerging field that aims to generate medical reports based on medical images. The report writing process can be tedious for senior radiologists and challenging for junior ones. Thus it is of great importance to expedite the process. In this work, we propose an EnricheD DIsease Embedding based Transformer (Eddie-Transformer) model, which jointly performs disease detection and medical report generation. This is done by decoupling the latent visual features into semantic disease embeddings and disease states via our state-aware mechanism. Then, our model entangles the learned diseases and their states, enabling explicit and precise disease representations. Finally, the Transformer model receives the enriched disease representations to generate high-quality medical reports. Our approach shows promising results on the widely-used Open-I benchmark and COVID-19 dataset. © 2022 IEEE.

10.
American Journal of Translational Research ; 14(3):2063-2072, 2022.
Article in English | EMBASE | ID: covidwho-1777100

ABSTRACT

We present a study protocol designed to test the safety and efficacy of the 2019 coronavirus disease (COVID-19) vaccine in patients with major psychotic disease. A secondary objective is to investigate optional vaccination methods for these patients. In a self-experiment, a Chinese psychiatrist examined the safety and efficacy of the COVID-19 vaccine under clinical use of typical antipsychotic agents and sedatives (olanzapine, duloxetine, and diazepam). For patients with extremely drug-resistant conditions, the safety of the COVID-19 vaccine under electroconvulsive therapy was also investigated. The entire study process was recorded on high-definition video. This clinical study protocol is, to our knowledge, the first of its kind. Our findings will shed new light on the protection of patients with psychotic diseases from COVID-19 infection.

11.
Journal of Virology ; 96(1):11, 2022.
Article in English | Web of Science | ID: covidwho-1756184

ABSTRACT

Over the past 20 years, the severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome CoV (MERS-CoV), and SARS-CoV-2 emerged, causing severe human respiratory diseases throughout the globe. Developing broad-spectrum drugs would be invaluable in responding to new, emerging coronaviruses and to address unmet urgent clinical needs. Main protease (Mpro;also known as 3CL(pro)) has a major role in the coronavirus life cycle and is one of the most important targets for anti-coronavirus agents. We show that a natural product, noncovalent inhibitor, shikonin, is a pan-main protease inhibitor of SARS-CoV-2, SARS-CoV, MERS-CoV, human coronavirus (HCoV)-HKU1, HCoV-NL63, and HCoV-229E with micromolar half maximal inhibitory concentration (IC50) values. Structures of the main protease of different coronavirus genus, SARS-CoV from the betacoronavirus genus and HCoV-NL63 from the alphacoronavirus genus, were determined by X-ray crystallography and revealed that the inhibitor interacts with key active site residues in a unique mode. The structure of the main protease inhibitor complex presents an opportunity to discover a novel series of broad-spectrum inhibitors. These data provide substantial evidence that shikonin and its derivatives may be effective against most coronaviruses as well as emerging coronaviruses of the future. Given the importance of the main protease for coronavirus therapeutic indication, insights from these studies should accelerate the development and design of safer and more effective antiviral agents. IMPORTANCE The current pandemic has created an urgent need for broad-spectrum inhibitors of SARS-CoV-2. The main protease is relatively conservative compared to the spike protein and, thus, is one of the most promising targets in developing anticoronavirus agents. We solved the crystal structures of the main protease of SARSCoV and HCoV-NL63 that bound to shikonin. The structures provide important insights, have broad implications for understanding the structural basis underlying enzyme activity, and can facilitate rational design of broad-spectrum anti-coronavirus ligands as new therapeutic agents.

12.
IEEE Transactions on Network Science and Engineering ; 2022.
Article in English | Scopus | ID: covidwho-1741294

ABSTRACT

With the development of modern technology, numerous economic losses are incurred by various spreading phenomena. Thus, it is of great significance to identify the initial sources triggering such phenomena. For practical spreading phenomena on social networks, the infection rates are relatively low. Hence, a high uncertainty of spreading trace might be incurred, which further incurs the reduction of localization accuracy obtained through existed source localization methods, especially the observer-based ones. Aiming to solve the source localization problem with a low infection rate, we propose a novel localization algorithm, i.e., path-based source identification (PBSI). First, a small number of nodes are selected and designated as observers. After the propagation process triggered by sources, we can obtain a snapshot. Later, a label is assigned to represent whether a node is infected or not, and observers are supposed to record the paths through which nodes are successfully infected. Based on source centrality theory, observers make the labels flow in the direction recorded during the label iteration process, which ensures the labels of nodes in the direction of the source increase gradually. Extensive experiments indicates that the proposed PBSI can handle source localization problems for both single and multi-source scenarios. IEEE

13.
2021 IEEE International Conference on Engineering, Technology and Education, TALE 2021 ; : 1017-1022, 2021.
Article in English | Scopus | ID: covidwho-1741265

ABSTRACT

The world has been upended by the ongoing COVID-19 pandemic which has posed significant impacts and challenges to the learning communities. Educational excellence for the new normal is calling for guiding students to "learn how to learn"and to develop their own individual talents and abilities along their educational journey. Through the preliminary baseline need assessments conducted in six universities, we observed that students are losing learning opportunities to a complete higher educational experience for their all-round development which they should have received in normal study years. Therefore, with the nature of students' educational experience radically changing-the demand for an improved virtual learning experience to attain educational excellence for this vulnerable population is magnified. The objectives of this case study are to 1) identify the learning obstacles that result in unfinished learning amid Covid-19, 2) explore the underlying learning mechanisms with online learning platforms to characterize students' anticipated level of educational excellence through the virtual learning environment, and 3) gain understanding about students' engagement, expectations, and satisfaction through students' feedbacks on the platform and evaluate potential impacts on educational effectiveness. This paper begins by summarizing and identifying limitations in the current higher education mentorship programs from both the mentors' and the mentees' perspectives. Then it introduces the innovative design and implementation of the Virtual Mentoring Platform built upon grounded theory, innovative technologies, evidence-based observations, and participants' feedbacks. Finally, it presented and discussed the preliminary results of the evaluation and implications of the case study. © 2021 IEEE.

14.
20th IEEE International Conference on Machine Learning and Applications, ICMLA 2021 ; : 233-238, 2021.
Article in English | Scopus | ID: covidwho-1741204

ABSTRACT

With the dramatic growth of hate speech on social media during the COVID-19 pandemic, there is an urgent need to detect various hate speech effectively. Existing methods only achieve high performance when the training and testing data come from the same data distribution. The models trained on the traditional hateful dataset cannot fit well on COVID-19 related dataset. Meanwhile, manually annotating the hate speech dataset for supervised learning is time-consuming. Here, we propose COVID-HateBERT, a pre-trained language model to detect hate speech on English Tweets to address this problem. We collect 200M English tweets based on COVID-19 related hateful keywords and hashtags. Then, we use a classifier to extract the 1.27M potential hateful tweets to re-train BERT-base. We evaluate our COVID-HateBERT on four benchmark datasets. The COVID-HateBERT achieves a 14.8%-23.8% higher macro average F1 score on traditional hate speech detection comparing to baseline methods and a 2.6%-6.73% higher macro average F1 score on COVID-19 related hate speech detection comparing to classifiers using BERT and BERTweet, which shows that COVID-HateBERT can generalize well on different datasets. © 2021 IEEE.

15.
2021 IEEE International Conference on Big Data, Big Data 2021 ; : 1692-1698, 2021.
Article in English | Scopus | ID: covidwho-1730892

ABSTRACT

The Coronavirus disease 2019 (COVID-19) pandemic has severely impacted countries around the world with unprecedented mortality and economic devastation and has disproportionately and negatively impacted different communities - especially racial and ethnic minorities who are at a particular disadvantage. Black Americans have a long-standing history of disadvantage (e.g., long-standing disparities in health outcomes) and are in a vulnerable position to experience the impact of this pandemic. Some studies indicate high-risk and vulnerability of the elderly and patients with underlying co-morbidities, however, little research paid attention to leveraging geographic information and machine learning (ML) to track the social and structural health determinants, which can provide a lower level of granularity. In this paper, we propose DeepTrack, a geospatial and ML-based approach to identify diverse determinants (including the structural, social, and constructural determinants) of health disparities in COVID-19 pandemic, which provides a lower level of granularity. We provide a thorough analysis of health disparities and diets based on multiple COVID-19 datasets and examine the structural, social, and constructural health determinants to assist in ascertaining why disparities (in racial and ethnic minorities who are particularly disadvantaged) occur in infection and death rates due to COVID-19 pandemic. We track determinants of nutrition and obesity through diet examination. Extensive experimental results show the effectiveness of our approach. The research provides new strategies for health disparity identification and determinant tracking with a goal to improve pandemic health care. © 2021 IEEE.

16.
13th International Conference on Education Technology and Computers, ICETC 2021 ; : 382-387, 2021.
Article in English | Scopus | ID: covidwho-1707888

ABSTRACT

This study reports on the employment data between 2017 and 2021 for the engineering students in a double degree joint programme between a university in Beijing and a university in London. The purpose was to use regression analysis to forecast the employment outcomes of the joint programme graduates for 2021. Data were collected from five cohorts of students from 2017 to 2021. The researcher found that although there had been an increase in employment rate before 2020, the year 2020 was the watershed where the employment rate went down both in work and in postgraduate education. The impact of COVID-19 might be the major reason for such a decrease. Data analysis also shows that other factors influencing employment results include place of origin and countries (overseas graduate schools). Furthermore, the regression analysis model forecasts the employment rate for 2021 graduates. © 2021 ACM.

17.
IEEE Transactions on Computational Social Systems ; 2021.
Article in English | Scopus | ID: covidwho-1621800

ABSTRACT

By regarding the Chinese financial and economic sectors as a system, this article studies the stock volatility spillover in the system and explores its effects on the overall performance of the macroeconomy in China. The recent outbreak of COVID-19, U.S.-China trade friction, and three historical financial turbulences are involved to distinguish the changes in the spillover in these distinct crises, which has seldom been unveiled in the literature. By considering that the stock volatility spillover may vary over distinct timescales, the spillovers are disclosed through innovatively constructing the multi-scale spillover networks, followed by connectedness computation, based on variational mode decomposition (VMD) and generalized vector autoregression (GVAR) process. Our empirical analysis first demonstrates the different levels of increases in the total sectoral volatility spillover and changes in the roles of the sectors in the system under the aforementioned crises. Besides, the increases in the sectoral spillover in the long-term are verified to negatively impact the macroeconomy and can thereby act as warning signals. IEEE

18.
Annals of the Academy of Medicine, Singapore ; 50(11):818-826, 2021.
Article in English | MEDLINE | ID: covidwho-1558253

ABSTRACT

INTRODUCTION: Inappropriate attendances (IAs) to emergency departments (ED) create an unnecessary strain on healthcare systems. With decreased ED attendance during the COVID-19 pandemic, this study postulates that there are less IAs compared to before the pandemic and identifies factors associated with IAs. METHODS: We performed a retrospective review of 29,267 patient presentations to a healthcare cluster in Singapore from 7 April 2020 to 1 June 2020, and 36,370 patients within a corresponding period in 2019. This time frame coincided with local COVID-19 lockdown measures. IAs were defined as patient presentations with no investigations required, with patients eventually discharged from the ED. IAs in the 2020 period during the pandemic were compared with 2019. Multivariable logistic regression was performed to identify factors associated with IAs. RESULTS: There was a decrease in daily IAs in 2020 compared to 2019 (9.91+/-3.06 versus 24.96+/-5.92, P<0.001). IAs were more likely with self-referrals (adjusted odds ratio [aOR] 1.58, 95% confidence interval [CI] 1.50-1.66) and walk-ins (aOR 4.96, 95% CI 4.59-5.36), and those diagnosed with non-specific headache (aOR 2.08, 95% CI 1.85-2.34), or non-specific low back pain (aOR 1.28, 95% CI 1.15-1.42). IAs were less likely in 2020 compared to 2019 (aOR 0.67, 95% CI 0.65-0.71) and older patients (aOR 0.79 each 10 years, 95% CI 0.78-0.80). CONCLUSION: ED IAs decreased during COVID-19. The pandemic has provided a unique opportunity to examine factors associated with IAs.

19.
Kexue Tongbao/Chinese Science Bulletin ; 66(31):3925-3931, 2021.
Article in Chinese | Scopus | ID: covidwho-1523391

ABSTRACT

Left unmitigated, climate change poses a catastrophic risk to human health, demanding an urgent and concerted response from every country. The 2015 Lancet Commission on Health and Climate Change and The Lancet Countdown: Tracking Progress on Health and Climate Change have been initiated to map out the impacts of climate change and the necessary policy responses. To meet these challenges, Tsinghua University, partnering with the University College London and 17 Chinese and international institutions, has prepared the Chinese Lancet Countdown report, which has a national focus and builds on the work of the global Lancet Countdown: Tracking Progress on Health and Climate Change. Drawing on international methodologies and frameworks, this report aims to deepen the understanding of the links between public health and climate change at the national level and track them with 23 indicators. This work is part of the Lancet's Countdown broader efforts to develop regional expertise on this topic, and coincides with the launch of the Lancet Countdown Regional Centre in Asia, based at Tsinghua University. The data and results of this report are presented at the provincial level, where possible, to facilitate targeted response strategies for local decision-makers. Based on the data and findings of the 2020 Chinese Lancet Countdown report, five recommendations are proposed to key stakeholders in health and climate change in China: (1) Enhance inter-departmental cooperation. Climate change is a challenge that demands an integrated response from all sectors, urgently requiring substantial inter-departmental cooperation among health, environment, energy, economic, financial, and education authorities. (2) Strengthen health emergency preparedness. Knowledge and findings on current and future climate-related health threats still lack the required attention and should be fully integrated into the emergency preparedness and response system. (3) Support research and raise awareness. Additional financial support should be allocated to health and climate change research in China to enhance health system adaptation, mitigation measures, and their health benefits. At the same time, media and academia should be fully motivated to raise the public and politicians' awareness of this topic. (4) Increase climate change mitigation. Speeding up the phasing out of coal is necessary to be consistent with China's pledge to be carbon neutral by 2060 and to continue to reduce air pollution. Fossil fuel subsidies must also be phased out. (5) Ensure the recovery from COVID-19 to protect health now and in the future. China's efforts to recover from COVID-19 will shape public health for years to come. Climate change should be a priority in these interventions. © 2021, Science Press. All right reserved.

20.
Anesthesia and Analgesia ; 133(3 SUPPL 2):918, 2021.
Article in English | EMBASE | ID: covidwho-1445109

ABSTRACT

Background and Aims: This research project aimed to determine the prevalence of cardiac complications in patients with COVID-19 presenting to University Hospital of North Tees (UHNT) with a view to determining compliance with NICE guidelines, comparing to other reported data on cardiac complications, and detecting useful trends that could be used to influence future guidelines. Methods: The notes of 80 patients with suspected/confirmed COVID-19 were reviewed for various factors, including cardiac complication markers (ECG, Troponin, cardiac imaging, BNP). Data was recorded on excel, anonymised, and analysed. Findings were compared to NICE guidelines and COVID- 19 research. Results: 63/80 patients were positive for COVID-19. On ECG: 10/63 (15.9%) had atrial flutter/ fibrillation (AF), 6/63 (9.5%) had ST depression/ T wave inversion (ST↓/TWI). The remainder had normal sinus rhythm, no ST↓/TWI or did not have a recorded ECG. Of the 16/63 (25.4%) patients with either AF or ST↓/TWI, 2/16 (12.5%) had a negative troponin, 14/16 (87.5%) had no troponin done/recorded. 2/63 (3.2%) had slightly elevated troponin but no ECG. No patients had a moderate to high troponin rise. Conclusion: Data is partially limited by no routine cardiac investigations. However we can infer that the majority of patients did not require these investigations. Where investigations did occur, we noted no cardiac complications in COVID-19 patients. This is in keeping with research by Linschoten et al, which shows a low incidence of cardiac complications in COVID-19 inpatients.1 Further work is required to determine what cardiac investigations should be routine in COVID-19 patients in order to meet NICE recommendations.

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