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INTRODUCTION: To carry out a retrospective bibliometric analysis of articles, published since the beginning of the pandemic, which addressed the topic of physical exercise and COVID-19, in order to provide a reference of origin for research on the topic. EVIDENCE ACQUISITION: This is a bibliometric study, which addressed the production / dissemination, through information recorded in the PubMed database, about physical exercise and COVID-19, published since the beginning of the pandemic. EVIDENCE SYNTHESIS: 111 publications in total were retrieved from PubMed in the first round of research and 93 publications were identified after reviewing the study titles and s. Eligibility was assessed for these 93 publications throughout the text and 76 were entered after removing duplicates and irrelevant records. According to Bradford's Law, we identified 76 publications in 53 journals from seven different countries. The countries of the journals that published the most were the United States (20, 37.7%) and the United Kingdom (15, 28.3%). The journals that most published on the subject were: European Journal of Physical and Rehabilitation Medicine, Obesity, Encephale and Progress in Cardiovascular Diseases, each with 03 studies. According to Lotka's Law, the most productive authors: Lavie CJ Smith I, with 4 articles published. When evaluating the word frequencies by Zipf's Law, it was observed that 16 words had at least 10 occurrences, with the words Covid-19, Exercise and Pandemic with 80, 39 and 38 occurrences respectively. CONCLUSION(S): According to our analysis, this research provides a current scenario of how studies related to physical exercise and COVID-19 are going on in the world, serving as a reference for researchers on this topic.Copyright © 2020 EDIZIONI MINERVA MEDICA.
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Background: Following the pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), and considering its capacity for rapid mutation, there have been many studies and articles on this novel coronavirus over the past three years. Therefore, providing knowledge and directions for management of SARS-CoV-2, for hospital staff is crucial. Hence, we collected the research information from different perspectives and summarized the guidelines for perinatal care on the topic of SARS-CoV-2, and for possible future viral pandemics. Method(s): A systematic review aimed at assessing the publications written in English and Chinese, offering different perspectives on the topic of perinatal care concerning SARS-CoV-2, was conducted using PubMed and Google Scholar from 2020 to 2022. In addition, we summarized the guidelines from the Taiwan Association of Obstetrics and Gynecology, American College of Obstetricians and Gynecologists, Society for Maternal-Fetal Medicine, Maternal Immunization Task Force and Partners, and Academy of Breastfeeding Medicine. Result(s): Due to physiological changes, pregnant patients may be prone to have complications, especially pre-eclampsia, affecting morbidity and mortality. Most neonates of coronavirus disease (COVID-19) infected mothers did not show any clinical abnormalities due to the infection. However, compared to the general population, infected neonates needed more invasive ventilation care, while the proportion of asymptomatic neonates was less than that in the general population. Further, long term complications are still under investigation. Evidence of vertical transmission via the placenta and umbilical cord is rare but not absent. Paxlovid (nirmatrelvir/ritonavir) can be administered to patients with comorbidities, and indications for cesarean delivery does not include COVID-19 infection. Vaccination against COVID-19 should not be delayed during pregnancy and lactation. Conclusion(s): Obstetricians and gynecologists should pay more attention to pregnant women with SARS-CoV-2 because of the physiological changes and higher risks of complications, morbidity, and mortality. Early prevention with vaccination in pregnant women is the key to controlling the COVID-19 pandemic, from which we can learn how to manage the next pandemic.Copyright © 2023 The Author(s).
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Intuitionistic fuzzy set (IFS) theory can be applied for multi-aspect systems due to its capability to address uncertainty and incomplete information in terms of membership and non-membership degrees. Unfortunately, classical Γ-structures cannot handle fuzzy and imprecise information in real problems. In fact, there is no rigorous base to practically express the effectiveness of multi-attribute systems in IFS environment. Here, we develop a generalized IFS with the notion of Γ-module called intuitionistic fuzzy Γ-submodule (IFΓM) to establish a novel "Global electronic (e)-Commerce (GeC) Theory”. To simplify the analysis of parameters, (α,β)-cut representation is proposed in terms of comprehensive distribution of fuzzy number for the classification of components. On the other hand, Cartesian product is implemented to correspond the elements. Substantial properties of IFΓM including (α,β)-cut, Cartesian product and t-intuitionistic fuzzy Γ-submodule (t-IFΓM) are characterized with illustrative examples to extend the framework of IFΓM, where (α,β)-cut and support t-IFΓM are verified to be Γ-submodules based on the properties of IFΓM. Through Γ-module homomorphism, image and inverse image, the parametric connections between (α,β)-cuts are systematically investigated. In addition, a mathematical relationship between the Cartesian product and (α,β)-cut is determined. The overlapping intersection of a collection of t-IFΓM is proved to be t-IFΓM, and the image and inverse image are preserved under Γ-module homomorphism. As global e-trades are increasingly expanding after the recent coronavirus disease 2019 (COVID-19) hit, with the growth of 26.7-trillion dollars, businesses are required to transform their traditional functional natures to online (or blended) strategies for cost efficiency and self-survival in the present competitive environment. Therefore, compared to recent studies on IFS in the context of Γ-structures, the main contribution of this study is to provide a theoretical basis for the establishment of a new GeC Theory through the developed IFΓM method and Γ-module M which targets the purchasing rate of customers through e-commerce companies. In the end, the performance of the proposed method in terms of upper and lower cut, t-intuitionistic fuzzy set, support and IFΓM model, is analyzed in the developed GeC Theory. The proposed GeC Theory is validated using real datasets of e-commerce mega companies, i.e., Amazon, Alibaba, eBay, Shopify. They are characterized based on the amount of online shopping by samples (individuals). Compared to the existing methods, the GeC approach is an effective IFS-based method for complex systems with uncertainty. © 2023 Elsevier Ltd
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BACKGROUND: Seven-day clinical pharmacy services in the acute sector of the National Health Service are limited. There is a paucity of evidential patient benefit. This limits investment and infrastructure, despite United Kingdom wide calls. AIM: To optimise medicines seven-days a week during surge-2 of the COVID-19 pandemic through implementation of a seven-day clinical pharmacy service. This paper describes service development, evaluation and sustainability. SETTING: A tertiary-referral teaching hospital, London, United Kingdom. DEVELOPMENT: The seven-day clinical pharmacy service was developed to critical care, acute and general medical patients. Clinical leads developed the service specification and defined priorities, targeting complex patients and transfer of care. Contributing staff were briefed and training materials developed. IMPLEMENTATION: The service was implemented in January 2021 for 11 weeks. Multidisciplinary team communication brought challenges; strategies were employed to overcome these. EVALUATION: A prospective observational study was conducted in intervention wards over two weekends in February 2021. 1584 beds were occupied and 602 patients included. 346 interventions were reported and rated; 85.6% had high or moderate impact; 56.7% were time-critical. The proportion of medicines reconciliation within 24-h of admission was analysed across the hospital between November 2020 and May 2021. During implementation, patients admitted Friday-Sunday were more likely to receive medicines reconciliation within 24-h (RR 1.41 (95% CI 1.34-1.47), p < 0.001). Rostered services were delivered sustainably in terms of shift-fill rate and medicines reconciliation outcome. CONCLUSION: Seven-day clinical pharmacy services benefit patient outcome through early medicines reconciliation and intervention. Investment to permanently embed the service was sustained.
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Advances in technology have resulted in increasing adoption of virtual dermatology services across the National Health Service. This has accelerated dramatically during the COVID-19 pandemic. Providing remote consultation alternatives empowers many patients to manage their health away from traditional in-person services. However, there is concern that universal implementation of such services may potentially widen healthcare inequalities for some patient groups. Reliably identifying at-risk groups is challenging. Co-design of health services has been proposed as a method to ensure equality and appropriateness of provision for all patients accessing a service by including them in the design process. In this study we profile the digital health literacy of patients with chronic skin conditions with the aim of using this information to redesign virtual services to support their long-term skin health. The Multidimensional Readiness and Enablement Index for Health Technology (READHY), comprising the eHealth Literacy Questionnaire (eHLQ), Health Literacy Questionnaire (HLQ) and Health Education Impact Questionnaire (heiQ), was used to assess patient skills, confidence and experience in using technology to manage their health. Consecutive patients under long-term follow-up in two specialist clinics supporting chronic skin conditions (organ transplant surveillance and biologics monitoring) completed questionnaires either in person or over the telephone. Between July and November 2021, 99 of 128 (77.3%) of patients invited to participate took part. Overall, these patients showed high levels of self-management skills, determination not to let health problems control their life and good support from family and healthcare professionals. In the domains related to digital skills, the responses were diverse. A cluster analysis identified multiple groups of patients with varying combinations of higher or lower level of digital health literacy, social and healthcare support, as well as capabilities in handling health condition and emotional responses. These preliminary data have provided important information for optimizing a co-design process aimed at tailoring services to support patients with chronic skin diseases. In particular, it has identified patient groups with distinct differences in terms of digital health literacy. Recognition of these groups and their differing profiles in terms of barriers to accessing virtual healthcare will be a key consideration in ensuring equitable representation in the service co-design process. It provides opportunities to target support to those patients with lower digital health literacy skills so that they may benefit from virtual services or adaptation of these services to address their specific needs. Alternatively, it allows recognition of patient groups who have higher digital health literacy and may safely benefit from alternative approaches to service provision such as patient-initiated follow-up.
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The pandemic outbreak of COVID-19 created panic all over the world. As therapeutics that can effectively wipe out the virus and terminate transmission are not available, supportive therapeutics are the main clinical treatments for COVID-19. Repurposing available therapeutics from other viral infections is the primary surrogate in ameliorating and treating COVID-19. The therapeutics should be tailored individually by analyzing the severity of COVID-19, age, gender, comorbidities, and so on. We aim to investigate the effects of COVID-19 therapeutics and to search for laboratory parameters indicative of severity of illness. Multi-center collaboration and large cohort of patients will be required to evaluate therapeutics combinations in the future. This study is a single-center retrospective observational study of COVID-19 clinical data in China. Information on patients' treatment modalities, previous medical records, individual disease history, and clinical outcomes were considered to evaluate treatment efficacy. After screening, 2,844 patients are selected for the study. The result shows that treatment with TCM (Hazard Ratio (HR) 0.191 [95% Confidence Interval (CI), 0.14–0.25];p < 0.0001), antiviral therapy (HR 0.331 [95% CI 0.19–0.58];p = 0.000128), or Arbidol (HR 0.454 [95% CI 0.34–0.60];p < 0.0001) is associated with good prognostic of patients. Multivariate Cox regression analysis showed TCM treatment decreased the mortality hazard ratio by 69.4% (p < 0.0001). © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
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Medical image diagnosis system by using deep neural networks (DNN) can improve the sensitivity and speed of interpretation of chest CT for COVID-19 screening. However, DNN based medical image diagnosis is known to be influenced by the adversarial perturbations. In order to improve the robustness of medical image diagnosis system, this paper proposes an adversarial attack training method by using multi-loss hybrid adversarial function with heuristic projection. Firstly, the effective adversarial attacks which contain the noise style that can puzzle the network are created with a multi-loss hybrid adversarial function (MLAdv). Then, instead of adding these adversarial attacks to the training data directly, we consider the similarity between the original samples and adversarial attacks by using an adjacent loss during the training process, which can improve the robustness and the generalization of the network for unanticipated noise perturbations. Experiments are finished on COVID-19 dataset. The average attack success rate of this method for three DNN based medical image diagnosis systems is 63.9%, indicating that the created adversarial attack has strong attack transferability and can puzzle the network effectively. In addition, with the adversarial attack training, the augmented networks by using adversarial attacks can improve the diagnosis accuracy by 4.75%. Therefore, the augmented network based on MLAdv adversarial attacks can improve the robustness of medical image diagnosis system. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The crisis of COVID-19 significantly disrupted global education and overturned our understanding of classroom setting in secondary education. This study adopted a mixed methods design to categorize the daily instructional practices of teachers in the early stages of school closure using content analysis and to test the resulting framework using ANOVA. A total of 48 teachers provided five-day diary entries in which they recorded episodic activities and subjective experiences, reported daily teaching techniques, and rated their subjective teaching quality. Four emergent online teaching orientations emerged from the data: 1 nonreciprocal knowledge understanding (1NRKU), 2 nonreciprocal knowledge construction (2NRKC), 3 reciprocal knowledge understanding (3RKU), and 4 reciprocal knowledge construction (4RKC). The results also showed that teachers adopting different online teaching orientations described their experiences differently. Teachers adopting 2NRKC, 3RKU, and 4RKC experienced significantly higher daily teaching satisfaction;teachers adopting 3RKU and 4RKC perceived significantly better student engagement. In terms of teaching readiness, teachers adopting 2NRKC, 3RKU, and 4RKC had significantly more experiences of online professional development and significantly better distance teaching TPCK. This study is innovative in presenting momentary data, which sheds light on future programs for customized professional development that will help prepare teachers for the next educational crisis. © 30th International Conference on Computers in Education Conference, ICCE 2022 - Proceedings.
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Xhaul, a mobile transport network, is a critical lifeline in imminent global crises: the combination of the COVID-19 pandemic and geopolitical conflict. Not only did the Russia-Ukraine war cause a global energy crisis, but it also put more energy stress on the 5G Xhaul. It also shows that the sustainability of a country depends on the unbroken Xhaul. Meanwhile, the COVID-19 outbreak has triggered the largest human-virus war of this century. It needs the ubiquitous 5G Xhaul to monitor the spread of COVID-19. Once crises occur, turning them into opportunities often requires new ways of seeing, considering, and responding to the 5G Xhaul provisioning. Facing more unpredictable situations, Chunghwa Telecom (CHT), the largest service provider in Taiwan, embraces the challenges and proposes practical solutions. This study aims to discuss the new 5G Xhaul provisioning strategies to achieve sustainable development goals in this turbulent era. © 2022 IEEE.
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This study collected epidemic data of COVID-19 in Zhengzhou from January 1 to January 20 in 2022. The epidemiological characteristics of the local epidemic in Zhengzhou High-tech Zone caused by the SARS-CoV-2 Delta variant were analyzed through epidemiological survey and big data analysis, which could provide a scientific basis for the prevention and control of the Delta variant. In detail, a total of 276 close contacts and 599 secondary close contacts were found in this study. The attack rate of close contacts and secondary close contacts was 5.43% (15/276) and 0.17% (1/599), respectively. There were 10 confirmed cases associated with the chain of transmission. Among them, the attack rates in close contacts of the first, second, third, fourth and fifth generation cases were 20.00% (5/25), 17.86% (5/28), 0.72% (1/139) and 14.81% (4/27), 0 (0/57), respectively. The attack rates in close contacts after sharing rooms/beds, having meals, having neighbor contacts, sharing vehicles with the patients, having same space contacts, and having work contacts were 26.67%, 9.10%, 8.33%, 4.55%, 1.43%, and 0 respectively. Collectively, the local epidemic situation in Zhengzhou High-tech Zone has an obvious family cluster. Prevention and control work should focus on decreasing family clusters of cases and community transmission.
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COVID-19 , Epidemics , Humans , SARS-CoV-2 , IncidenceABSTRACT
After the outbreak of COVID-19, mask detection, as the most convenient and effective means of prevention, plays a crucial role in epidemic prevention and control. An excellent automatic real-time mask detection system can reduce a lot of work pressure for relevant staff. However, by analyzing the existing mask detection approaches, we find that they are mostly resource-intensive and do not achieve a good balance between speed and accuracy. And there is no perfect face mask dataset at present. In this paper, we propose a new architecture for mask detection. Our system uses SSD as the mask locator and classifier, and further replaces VGG-16 with MobileNetV2 to extract the features of the image and reduce a lot of parameters. Therefore, our system can be deployed on embedded devices. Transfer learning methods are used to transfer pre-trained models from other domains to our model. Data enhancement methods in our system such as MixUp effectively prevent overfitting. It also effectively reduces the dependence on large-scale datasets. By doing experiments in practical scenarios, the results demonstrate that our system performed well in real-time mask detection. © 2022 IEEE.
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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.
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After the outbreak of COVID-19, mask detection, as the most convenient and effective means of prevention, plays a crucial role in epidemic prevention and control. An excellent automatic real-time mask detection system can reduce a lot of work pressure for relevant staff. However, by analyzing the existing mask detection approaches, we find that they are mostly resource-intensive and do not achieve a good balance between speed and accuracy. And there is no perfect face mask dataset at present. In this paper, we propose a new architecture for mask detection. Our system uses SSD as the mask locator and classifier, and further replaces VGG-16 with MobileNetV2 to extract the features of the image and reduce a lot of parameters. Therefore, our system can be deployed on embedded devices. Transfer learning methods are used to transfer pre-trained models from other domains to our model. Data enhancement methods in our system such as MixUp effectively prevent overfitting. It also effectively reduces the dependence on large-scale datasets. By doing experiments in practical scenarios, the results demonstrate that our system performed well in real-time mask detection. © 2022 IEEE.
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Background: During the COVID-19 health crisis, there is a recognized need for addressing vaccine hesitancy to increase vaccination rates globally. In this context, exploring the underlying public behavioral mechanism related to COVID-19 vaccine decisions has been the focus of much investigation. Objective: This thesis seeks to investigate and explain the impact of COVID-19-related information scanning via social media on health perceptions and behavioral intentions to receive COVID-19 vaccine doses in China. Methods: By distributing a questionnaire online, 483 respondents were recruited. Then, the present study applied partial least squares structural equation modeling (PLS-SEM) by using Smart PLS 3.3. Finally, the variance of path relationships among different socio-demographic groups was tested by performing multigroup analysis. Results: COVID-19 information scanning via social media has positive influence on four constructs, including perceived severity (β = 0.355, p < 0.01), perceived vulnerability (β = 0.140, p < 0.05), self-efficacy (β = 0.360, p < 0.01) and response efficacy (β = 0.355, p < 0.01). No significant correlation was found between threat appraisal and behavioral intentions to get vaccinated, including perceived severity and perceived vulnerability. And scanned information exerts influence through other significant factors, including self-efficacy (β = 0.379, p < 0.01), response efficacy (β = 0.275, p < 0.01) and response cost (β = −0.131, p < 0.05). Additionally, response efficacy exerts stronger influences on men's behavioral intentions, whereas response cost and perceived vulnerability are stronger mediators among women. Surprisingly, scanned information is positively associated with response cost among older adults, and perceived vulnerability was negatively associated with behavioral intentions to receive the coronavirus vaccines among younger adults. And there were significant differences in the association of perceived vulnerability and behavioral intentions between lower and higher educated groups. Conclusion: The present results highlight the key roles of COVID-19-related scanned information on public health perceptions and behavioral intentions. Tailored health communication must deliver factual information, address the public uncertainty regarding adverse effect of COVID-19 vaccine, and clarify vaccine schedules. Copyright © 2023 Cheng and Espanha.
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The recent COVID-19 pandemic reveals the vulnerability of global supply chains: the unforeseen supply crunches and unpredictable variability in customer demands lead to catastrophic disruption to production planning and management, causing wild swings in productivity for most manufacturing systems. Therefore, a smart and resilient manufacturing system (S & RMS) is promised to withstand such unexpected perturbations and adjust promptly to mitigate their impacts on the system's stability. However, modeling the system's resilience to the impacts of disruptive events has not been fully addressed. We investigate a generalized polynomial chaos (gPC) expansion-based discrete-event dynamic system (DEDS) model to capture uncertainties and irregularly disruptive events for manufacturing systems. The analytic approach allows a real-time optimization for production planning to mitigate the impacts of intermittent disruptive events (e.g., supply shortages) and enhance the system's resilience. The case study on a hybrid bearing manufacturing workshop suggests that the proposed approach allows a timely intervention in production planning to significantly reduce the downtime (around one-fifth of the downtime compared to the one without controls) while guaranteeing maximum productivity under the system perturbations and uncertainties.
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Introduction: Depression is a debilitating disorder affecting individuals' level of bio-psychosocial functioning across different age groups around the globe. The recent development of a new NIBS called Transcranial Pulse Stimulation (TPS), also known as low-intensity extracorporeal shock wave therapy (Li-ESWT), has been proven effective for only a 2-week treatment of 35 patients with Alzheimer's disease (AD). Patients' cognition and memory have shown significant improvement which lasted up to 3 months. However, there is a lack of scientific evidence on the efficacy of this TPS intervention on other psychiatric population such as Major Depressive Disorder (MDD), which is increasingly prevalent in Hong Kong and nationwide especially during the COVID-19 pandemic. Nonetheless, there is no trial evaluating the efficacy of TPS on other neuropsychiatric disorders. This gave us the impetus to evaluate the efficacy of TPS on young adults with Major Depressive Disorder (MDD) in Hong Kong. Method(s): In this single-blinded, randomized controlled trial, participants had a confirmed clinical diagnosis of MDD, recruited from the community, NGOs and private enterprise. The intervention was a 2-week TPS treatment comprised six 30-min TPS sessions, delivered by trained mental health professionals. A total of 30 participants were recruited and randomized into either the TPS group or the Waitlist Control (WC) group. Randomization was stratified by gender and age by an independent statistician on a 1:1 ratio. Our primary outcome was determined by whether participants' depressive symptom severity demonstrated significant reduction, compared with the WC group, using the Hamilton Depression Rating Scale-17 (HDRS17). This trial is registered with Clin.Trials.gov, number NCT05006365. Result(s): We recruited 30 participants from 1 August to 31 Oct 2021. They were between 18-54 years old and were predominantly female (73%), ethnically Chinese. There was a significant group x time interaction (F(1, 28) = 818.8, p <.001). Compared with the WC group, there was a significant reduction in the depressive symptom severity in the TPS group (mean difference = -6.60, p = 0.02, Cohen's d = -0.93). Results showed a significant intervention effect and the effect was large. Conclusion(s): TPS is safe and effective to reduce depressive symptoms among young individuals with MDD in this trial. Therefore, TPS may be considered as a top treatment option for neuropsychiatric disorders in clinical psychiatry. Funding(s): This trial is funded by the Departmental General Research Fund, the Hong Kong Polytechnic University, Hong Kong SAR, China. Copyright © 2022
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Introduction: Ozanimod is a sphingosine 1-phosphate receptor 1 and 5 modulator approved in multiple countries for treatment of adults with relapsing forms of MS (RMS) or moderately to severely active ulcerative colitis. Objective(s): To describe incidence rates (IRs) of treatmentemergent adverse events (TEAEs) in patients with RMS treated with ozanimod 0.92 mg in phase 3 and open-label extension (OLE) trials. Method(s): In phase 3 trials, adults with RMS were randomised to oral ozanimod 0.46 or 0.92 mg/d or intramuscular interferon beta-1a 30 mug/wk for >=12 months (SUNBEAM-NCT02294058) or 24 months (RADIANCE-NCT02047734). Completers were eligible to enrol in the ongoing OLE trial (DAYBREAK-NCT02576717) of ozanimod 0.92 mg/d. IRs and 95% confidence intervals (CI)/1000 person years (PY;100,000 PY for malignancies) were calculated for TEAEs during the pooled phase 3 trials and at yearly intervals during the OLE (2 Feb 2021 cutoff). Result(s): In patients treated with continuous ozanimod 0.92 mg (n=882), the IR [95%CI]/1000 PY decreased over time (from phase 3 to OLE >36 months) for overall TEAEs (896.1 [826.8-971.3] vs 259.1 [180.0-372.8]);infections (300.5 [268.9-335.9] vs 144.9 [109.2-192.3]);opportunistic infections (12.0 [7.4-19.6] vs 4.3 [1.4-13.3]);cardiac disorder TEAEs (22.8 [16.0-32.7] vs 4.2 [1.4-13.0]);and hepatic disorder TEAEs (77.0 [63.1-94.0] vs 15.1 [8.1-28.1]). The most common opportunistic infections in phase 3 trials and the OLE were oral herpes and herpes zoster (including varicella zoster virus). IRs remained relatively stable for serious TEAEs (31.2 [23.0-42.4] vs 30.5 [19.7-47.3]), malignancies (372.2 [120.8-868.5] vs 276.7 [33.5-999.6]/100,000 PY), confirmed macular edema (n/N, 1/882;0.7 [0.1-5.3] vs n/N, 1/687;1.4 [0.2-9.8]), and pulmonary TEAEs (11.3 [6.8-18.7] vs 0.0 [0.0-9.9]). The IR for serious infections remained relatively stable until OLE >36 months, at which time the IR increased (6.7 [3.5-12. 9] vs 9.8 [4.7-20.6]), which may be partially due to the COVID-19 pandemic. The most common serious infections were appendicitis (n/N, 3/882) and pyelonephritis acute (n/N, 1/882) (phase 3), and pneumonia (n/N, 4/762) and coronavirus infection (n/N, 3/762) (OLE). Most coronavirus infections were nonserious (31/34 [91.2%]). Conclusion(s): In this post hoc analysis, IRs of TEAEs in patients with RMS treated with continuous ozanimod 0.92 mg in phase 3 and OLE trials generally declined or remained stable over up to 5 years of observation time.
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Introduction: Ozanimod, an oral sphingosine 1-phosphate receptor 1 and 5 modulator, is approved in multiple countries for the treatment of adults with either relapsing forms of multiple sclerosis (RMS) or moderately to severely active ulcerative colitis. Objective(s): To report the safety and efficacy of extended exposure to ozanimod from an ongoing open-label extension (OLE) trial. Method(s): Patients with RMS who completed a phase 1, 2, or 3 ozanimod trial were eligible to enrol in DAYBREAK (NCT02576717), where they received ozanimod 0.92 mg/d. The primary objective was to evaluate safety in the overall population;treatment-emergent adverse events (TEAE) were monitored. Efficacy was evaluated with annualised relapse rate (ARR), calculated via negative binomial regression and pooled for all parent-trial treatment groups. Number of new/ enlarging T2 and gadolinium-enhancing (GdE) magnetic resonance imaging (MRI) brain lesions were reported for patients who entered the OLE from an active-controlled phase 3 trial. Result(s): In total, 2639 patients completed the parent trials;this interim analysis (datacut 1 February 2022) included 2494 patients with mean (range) ozanimod exposure of 56.4 (0.03- 74.7) months (11732.2 patient-years) in the OLE. In the OLE, 2199 patients (88.2%) had any TEAE, 352 (14.1%) had a serious TEAE (SAE), and 89 (3.6%) discontinued due to a TEAE. Similar rates of TEAEs and SAEs occurred when assessed by parent trial treatment group. The most common TEAEs (based on preferred terms) were nasopharyngitis (20.6%), headache (16.9%), upper respiratory tract infection (11.9%), COVID- 19 infection (11.5%), and lymphopenia (10.5%), which were generally similar to parent trial observations (excluding COVID-19 infection). Adjusted ARR in the OLE was 0.099 (95% CI, 0.083-0.119). After 60 months of treatment, 68% of patients were relapse free in the OLE. Three- and 6-month confirmed disability progression was observed in 15.9% and 14.0% of patients in the OLE, respectively. Mean number of new/enlarging T2 lesions per scan at 60 months was similar, regardless of parent trial treatment group (range, 0.77-0.98), as was mean number of GdE lesions at month 60 (range, 0.057-0.065). Conclusion(s): The safety and tolerability profile of ozanimod in DAYBREAK was consistent with prior reports. Ozanimod treatment demonstrated sustained efficacy on clinical and MRI measures of disease activity and on disability progression.
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Introduction: COVID-19 emerged in late 2019. It is unclear whether selective sphingosine 1-phosphate (S1P) receptor modulators affect clinical outcomes of COVID-19 in patients with relapsing multiple sclerosis (RMS), including those who received SARS-CoV-2 vaccination. Objective(s): To characterise COVID-19 outcomes and vaccine breakthrough infections during ozanimod use, an S1P1 and S1P5 modulator, for treatment of RMS in an ongoing open-label extension (OLE) study. Method(s): DAYBREAK (NCT02576717), an OLE study of ozanimod 0.92 mg/d, began 16Oct2015. Patients who completed a phase 1-3 ozanimod RMS trial were eligible;>90% are from Eastern Europe. In this post hoc analysis, COVID-19 events from 1Nov2019 to 28Jan2022 in DAYBREAK were identified by MedDRA 24.1 COVID-19 SMQ (narrow scope). Each patient's most recent infection and all postvaccination infections were characterised. Result(s): Of 2181 patients in DAYBREAK during the analysis period, 319 (14.6%) developed COVID-19 (274 confirmed, 45 suspected). COVID-19 was nonserious in 291 (91.2%). During COVID-19, ozanimod was continued in 220 (69.0%) patients, interrupted in 94 (29.5%), and permanently discontinued in 3 (0.9%);action was unknown in 2 (0.6%) patients. At data cutoff, 285 (89.3%) had recovered (including 195 who had continued ozanimod), 6 (1.9%) recovered with sequelae, 5 (1.6%) were recovering, 16 (5.0%) had not recovered, and 5 (1.6%) died;a sixth COVID-19-related death due to lung abscess occurred after recovery with sequelae from COVID-19 infection. Of 1984 patients in DAYBREAK on 11Dec2020, when COVID-19 vaccines emerged, 596 (30.0%) received >=1 vaccine dose (415 [69.6%] mRNA;99 [16.6%] replication-defective viral vector;65 [10.9%] inactivated SARS-CoV-2;26 [4.4%] other);504 (25.4%) were fully vaccinated. COVID-19 occurred in 39/596 (6.5%) vaccinated patients and 213/1388 (15.3%) unvaccinated patients;3 postvaccination cases (including 1 case after 2 mRNA doses) were serious. Of 39 patients with postvaccination infections, 28 (71.8%) recovered (including 2/3 serious cases), 1 (2.6%) recovered with sequelae, 3 (7.7%) were recovering, and 7 (17.9%, including the third serious case) had not recovered at data cutoff. There were no COVID-19-related deaths among vaccinated patients. Conclusion(s): COVID-19 cases were largely nonserious, and the majority of infected patients recovered while continuing ozanimod. Few vaccinated patients developed COVID-19;most who did recovered without sequelae.
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The number of pediatric emergency department (PED) visits fell significantly during the coronavirus disease 2019 (COVID-19) pandemic. However, the impact of the ongoing pandemic on PED patients suffering from asthma attacks in Taiwan has not been studied. We thus analyzed patients with asthma attacks visiting a PED during the early stage of the COVID-19 pandemic and the following (resurgent) waves. We retrospectively studied pediatric patients with asthma attacks who visited the PED from 01 January 2019 to 30 September 2021. We retrieved patient numbers, demographic characteristics, triage acuities, medications, and PED dispositions during the various waves of the COVID-19 pandemic. A total of 1842 patients with asthmatic attacks presented to the PED during the study period. PED visits caused by asthmatic attacks declined by 55% after the first COVID-19 outbreak in early 2020 (p = 0.009) and fell even more remarkably (by 85%) in mid-2021 (p = 0.038), during the time when the numbers of confirmed COVID-19 cases skyrocketed (the second wave). However, neither the high-triage acuity rate nor the rate of admission differed between the two periods (p = 0.08 and 0.406, respectively). However, the proportion of systemic corticosteroid (SCS) prescriptions increased during the pandemic (81.90 vs. 77.77%, p = 0.029). The COVID-19 pandemic notably impacted the number of asthmatic PED visits not only during the first peak period but also during the following waves, but asthma severity did not vary over time. Physicians tended to prescribe more SCSs during the pandemic to control respiratory symptoms. We suggest that SCSs should be used cautiously even during the pandemic to minimize their adverse effects. Copyright © 2022 The Author(s). Published by MRE Press.