Novel real world evidence from mSGo, a digital support program for secondary Progressive multiple sclerosis patients in Australia using siponimod

Introduction: Siponimod is approved in Australia for adults with secondary progressive multiple sclerosis (SPMS). Prescreen requirements for siponimod include a CYP2C9 genotype test to determine maintenance dosing. An integrated digital platform, 'MSGo', was developed by Novartis and RxMx to support Healthcare Professionals and their multiple sclerosis patients. Objective(s): Data derived exclusively from MSGo was utilised to explore the onboarding experience of siponimod patients in Australia. Aim(s): To provide real world evidence on siponimod for SPMS patients in Australia. Method(s): The study enrolled >350 adults with SPMS registered in MSGo for siponimod in Australia. Primary endpoint is the average time for onboarding with key secondary endpoints addressing adherence and variables that influence onboarding and adherence. Result(s): Final data extraction on April 20th, 2022 included 368 patients (median age of 59y).CYP2C9 genotype testing took a median of 19 days (95%CI 17-21) from registration and maintenance doses of 2mg (n=166) or 1mg (n=27) were initiated as per label recommendations;1mg was initiated for two rare allele genotypes (*1*5 and*1*11) in the absence of label recommendations. Mixture-cure modelling estimated that 58% of patients will ever initiate siponimod, with a median time to initiation of 56d (95%CI 47-59) from registration. Among those who initiated siponimod the most common reported reason for delayed initiation was 'waiting for vaccination'. Self-reporting of daily treatment, captured under the treatment reminder function in MSGo, had a drop-off of ~25% after the first week of initiation;a continued decline in reporting over time limited assessment of adherence. Continued self-reporting of daily dosing trended lower with older patients with only 28% of those >70y continuing to self-report at day 90 compared to 47-69% with the younger age groups. The study uncovered the important role of care partners, with Cox regression analyses demonstrating that SPMS patients who nominated a care partner were more likely to initiate (HR:2.1, 95%CI 1.5-3.0) and to continue self-reporting their daily medication (HR:2.2, 95%CI 1.3-3.7). A total of 90 patients discontinued the study;48 prior to and 42 after siponimod exposure. Conclusion(s): This study provides insights into siponimod onboarding for adults living with SPMS in Australia and demonstrates the impact of MSGo and care partner support during a period challenged by the COVID-19 pandemic.

A Study of Increasing Adoption Trends of Digital Technologies - An Evidence from Indian Banking

The banking sector in India is one of the paramount drivers for the magnification event of the economy. The word digitalization is almost used in every sector of the economy and banking is no exception to it. The twenty-first centur in which we are living is highly regulated by the digitalization process. The govt. of Indian also announced Digital India Programme with the vision that the financial sector move to increase their knowledge with technological innovation. The process of digitalization in banking is also important for the smooth functioning of transactions and enhanced customer satisfaction. The digitalization process in banking helped in the process of financial inclusion. Keeping a similar objective the Prime Minister Mr. Narender Modi also started the Jan Dhan Yojana for opening the saving account for the unbanked person. In the scenario of Covid 19, most of the banks in the pandemic time have reduced the banking hours for their customers and insist them to go for digital banking, but fulfilling the customers demand and their expectations is a big challenge for the banks. Banks to ensure their continuity and to mitigate the impact of this pandemic have to make structural and operational changes in the delivery of the banking services online and also increased their digital offerings, including an enhancement in the number of digital touchpoints offered to their customers. After this Covid 19, it's been expected that the Indian public will experience new digital banking apps with a simplified interface and enhanced security features along with the fast execution of banking services. Further, these changes will change the behavior of the bank customers, such as shifting from physical banking to online banking. This implies that if banks want to grasp the opportunities that emerged out of this Covid-19 banks will have to re-devise their strategies and shift their efforts and resources towards digitization. © 2022 American Institute of Physics Inc.. All rights reserved.

COVID-19 AND PERFORMANCE OF COSMETICS COMPANIES

Skincare, hair care, make-up, perfumes, toiletries and deodorants, and oral cosmetics are the main product categories of the cosmetic market. Since the early twentieth century, the production of cosmetics and beauty products has been controlled by a handful of multi-national corporations. COVID-19 impacted the cosmetics industry in several different and sometimes conflicting ways. This study benchmarks the performance of 20 largest cosmetics companies against their competition as well as against their previous years to analyze the impact of COVID-19. We find that only one company has consistently performed than its peers over the period of 2015–2020. We also find that average efficiency score of cosmetics companies declines in 2020 relative to 2019. © Emerald Group Holdings Ltd.. All rights reserved.

The smart anti COVID cradle with geometrical interventions

Assisting the parents sweating relentlessly in pursuit of securing their child's future, the authors have engineered the Smart Anti COVID Cradle, designed by following the basic concepts of mathematics, trigonometry and elementary fundamentals of physics. From calming the baby through the automatic swinging feature to keeping an eye on the baby through live camera feed and audio, this cradle can do it all. Another highlighting facet of this cradle is aiding the baby's feeding through automatic inclination. Toil proof feeding of the baby has been assured by the unique attached bottle holder. Specially designed characteristics like electronic swinging which makes the child feel like rocking in mother's lap, pleasant sounds of nature, recordings of the assuring voice of parents and the automated eye catching circular moving toys will be self-activated to comfort and cheer the baby when it starts crying. In consideration of the prevailing COVID-19 situation, exceptional aspects like regular body temperature alerts, a pre-fitted air purification system and to top it all, a protective covering to avoid infection have been installed. The cradle is completed by a smart mattress equipped with humidity sensors to keep in check the excretion by the baby. The cradle works on the principles of Internet of Things (IoT) helping parents' shuttle effortlessly in a smart way between work and home. This is the revolutionary step to rewrite the history of advanced childcare post pandemic not only at home but also in pediatric hospitals imparting care for neonates and infants. © 2022 Author(s).

A study of assessment of knowledge, perception and attitude of using tele health services among college going students of Uttarakhand

Tele medicine or Tele health services are available in the world before 1970. Recent surge has been observed in the tele medicine during Covid 19. It is observed that tele health services usage has increased from 11% to 70% and the satisfaction level among the patients is around 78% in US and China. As per the Press information bureau report, in India around 35000 patients use E Sanjeevni portal for tele health services. The purpose of the study is to assess the knowledge perception and attitude towards tele health services by the students because they are young generation and their adoption rate of technology and skill set in technology is very high. A questionnaire was floated through Google forms to students of various colleges in Uttarakhand primarily in the district of Dehradun, Haridwar and Nainital. Around 1000 students were targeted through their Gmail accounts and WhatsApp groups. It was found that there is lack of awareness among students about telemedicine apps and related aspects;there perception towards it is positive as they want to use it as well as willing to refer it as well. It is concluded that the tele health services can be boon for the state like Uttarakhand as the health infrastructure is poor in the state because of its geography. If the organisation providing tele health services will try to improve the awareness, the willingness to adapt tele health services will be very high. © The author(s) 2021.

Tele health in the digital era during covid -19 a case study of Uttarakhand

Tele-health services area very old facility available, but it never became a forefront technology or option for patients. During Covid 19 lockdown, when all the hospitals OPD and Private Clinics were closed then there was certainly a need for a therapy that could be available, keeping the social distancing in mind. This study on Tele-health is both a primary and secondary data-based study. The first objective of the study is based on a survey of patients and service providers. The other two objectives are studied through secondary data. Options left for chronic patients were explored, their awareness and satisfaction regarding these options were studied if there is a surge in Tele-health services usage, then what strategies should organizations adopt for the continuous use of these services after covid was also studied. The study shows a surge in the usage of Tele-Health services and remote monitoring of patients. Approximately 80% of the patients have cancelled their personal visits to doctors, and patients' satisfaction rate is more than 70%. A survey on service providers was also carried out, and the satisfaction level of doctors in providing Tele-health services were more than 65%. The study reflects that Tele-health services can be a boon for a state like Uttarakhand, where health services are scarce and were treating patients in remote areas is challenging. © 2021 The authors.

NOTTO guidelines for vaccine-induced thrombotic thrombocytopenia in organ donation and transplantation

From the context of organ donation, COVID-19 vaccine-induced thrombotic thrombocytopenia (VITT) is important as there is an ethical dilemma in utilizing versus discarding organs from potential donors succumbing to VITT. This consensus statement is an attempt by the National Organ and Tissue Transplant Organization (NOTTO) apex technical committees, India, to formulate the guidelines for deceased organ donation and transplantation in relation to VITT to help in appropriate decision-making. VITT is a rare entity, but a meticulous approach should be taken by the organ procurement organization's (OPO) team in screening such cases. All such cases must be strictly notified to the national authorities (NOTTO) as a resource for data collection and ensuring compliance with protocols in the management of adverse events following immunization. Organs from any patient who developed thrombotic events up to 4 weeks after adenoviral vector-based vaccination should be considered to be linked to VITT and investigated appropriately. The viability of the organs must be thoroughly checked by the OPO, and the final decision in relation to organ use should be decided by the expert committee of the OPO team consisting of a virologist, a hematologist, and a treating team. Considering the organ shortage, in case of suspected/confirmed VITT, both clinicians and patients should consider the riskbenefit equation based on limited experience. An appropriate written informed consent of potential recipients and family members should be obtained before the transplantation of organs from suspected or proven VITT donors.

COVID-19 Fake News Detection System

This article deals with the problem of the rapidly increasing COVID-19 infodemic in the world. Thus, there is a need for an effective framework of detecting fake information or misleading news related to COVID-19 virus/disease. To resolve this, we have used a dataset obtained from ConstraintAI'21. The dataset consists of 10,700 tweets and online posts of fake and real news concerning COVID-19. Machine Learning (ML) algorithms compared in this paper to classify the given news or tweet into real or fake are Logistic Regression (LR), K-Nearest Neighbor (KNN), Linear Support Vector Machine (LSVM), Random Forest Classifier (RFC), Decision Tree (DT), Naive Bayes (NB) and Stochastic Gradient Descent (SGD) algorithm. Two feature extraction techniques were used count vectorization and TF-IDF. Deep Learning (DL) algorithms implemented using Adam optimizer are Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). The best testing accuracy was achieved with the LSVM model using TF-IDF feature extraction method followed by Stochastic Gradient Descent classifier with TF-IDF feature extraction technique. LR, DT, and RFC performed better with the Count vectorization feature extraction technique, whereas LSVM, KNN, NB and SGD had better accuracy with TF-IDF feature extraction technique. The LSTM model performed slightly better among the DL algorithms. © 2022 IEEE.

COVID-19 Outbreak Prediction Using Machine Learning

The recent global outbreak of the coronavirus has thrown new challenges for the research community. First case was registered in China, and then, it got spread in most of the countries of the world. Initially, the speed of spread was slow but later on, its spread rate was very really high and on analysis it turned out to be exponential. Governments all across the world imposed lockdowns, and people were asked to practice social distancing in order to prevent the spread of the COVID-19 virus. Later on, it was announced as pandemic by World Health Organization (WHO). Machine learning-driven methods can prove to be really vital in predicting risks, effects and parameters of this pandemic. These predictions will help in making strategies to control its spread and understand its nature. More research is beginning to anticipate and a remarkable amount of machine learning models are being talked about to predict COVID-19 cases used by experts or researchers around the globe. In this research project, we have used univariate LSTM model to make predictions. The number of confirmed cases, number of recovered cases and the number of death cases in the coming days are being predicted. Mean absolute error (MAE) is used as the measure of performance metric of the predicted results. The results produced are quite accurate. These results prove that univariate LSTM is a promising model to make predictions for COVID-19 outbreak. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Assessing snowball effect of COVID-19 pandemic on Indian dairy sector

Dairy sector experienced supply setback as well as demand uncertainties owing to restrictive measures imposed for the control of COVID-19 pandemic. The present paper attempts to assess the multi-dimensional impact of pandemic on dairying by reviewing the emerging literature. The assessment shows that availability of feed and fodder declined by 11% during the initial months of lockdown making it the most affected supply chain. The dairy farmers incurred dual losses due to increase in cost of milk production (+6%) and simultaneous fall in milk prices (-5.6%). Major challenge for the dairy processors was posed by the fall in demand which declined steeply particularly for the ice-creams and milk based beverages. The estimated loss incurred by the dairy farmers is (sic)4,000 per milch animal in the initial 40 days of lockdown which can further rise if losses due to missed artificial insemination and change in animal prices arc also taken into account. Assessment of impact on the unorganized dairy sector is still unavailable without which the loss estimation from the perspective of milk buyers stands incomplete. Huge inventories of the Skimmed Milk Powder (SMP) are the immediate challenge which requires proper policy intervention for arresting further losses in the dairy sector.

Novel generation of real world evidence through MSGo, a digital support program supporting the use of siponimod in secondary progressive multiple sclerosis patients in Australia

Introduction: Siponimod is approved in Australia for adults with secondary progressive multiple sclerosis (SPMS). Initiating siponimod involves prescreening tests, including a CYP2C9 genotype test to determine siponimod maintenance dosing. Furthermore, patients undergo a 6-day titration prior to the maintenance phase. To support onboarding, an integrated digital platform, 'MSGo', has been developed by Novartis and RxMx® for Healthcare Professionals and their multiple sclerosis patients. Objective: Data derived exclusively from MSGo will be utilised to characterise the onboarding experience of siponimod patients in Australia. Aims: To provide real world evidence on siponimod for SPMS patients in Australia. Methods: The study will enrol 500 adults with SPMS registered in MSGo for siponimod treatment in Australia. The primary endpoint is the average time for onboarding with key secondary endpoints addressing adherence and the variables that influence onboarding and adherence. Results: As of April 19th, 2021, 211 patients have enrolled in the RWE study, with baseline patient characteristics revealing more females than males (70% vs 30%) and a median age range of 51-60 years. A total of 88 patients proceeded to at least the first titration dose;75 with at least one day of maintenance. Mixturecure modelling estimated a median time to initiation of 53 days in the predicted population of patients who will ever initiate on siponimod. Univariate Cox regression analyses demonstrated that patients who nominated a care partner at registration (n=27, 13%) appeared more likely to initiate siponimod earlier (p=0.017). A total of 163 CYP2C9 genotype assessments were performed through MSGo and the median time to receiving results from registration was 21 days (95% CI: 18 to 28 days). Of these, 87 patients had their maintenance dose selected in MSGo, with all but one patient having the recommended maintenance dose selected: 2 mg for CYP2C9∗1∗1 (n=58), ∗1∗2 (n=13), ∗2∗2 (n=1) and 1 mg for ∗1∗3 (n=10) and ∗2∗3 (n=4). 1 mg maintenance was selected for a patient with a rare ∗1∗5 genotype which currently has no dose recommendation. A total of 7 patients unenrolled from MSGo prior to siponimod initiation whilst 10 patients ceased after siponimod initiation. Conclusions: These interim results provide early insights into the siponimod onboarding experience for SPMS patients in Australia and demonstrate the utility of MSGo during a period challenged by the COVID-19 pandemic.

AKI in kuwait: Incidence, causes, management, and outcomes-a prospective observational study

Background: Little is known about AKI epidemiology, causes, management and outcome in Kuwait. We report that. Methods: Demographics, comorbidities, treatment and 4 weeks outcome data for nephrology referrals for AKI in 7 public hospitals from 1/Jan-30/Apr/2021 prospectively collected and analyzed Results: Total number of AKI referrals was 1298, that is 3.3% of hospital admissions. Community acquired cases were 12.5%. Males were 57%, mean age 64 (52% > 65), and Kuwaiti citizens 65%. DM affected 71%, HTN 74%, and cardiac disease 36% of patients. Mean baseline eGFR before AKI was 62. Baseline eGFR < 60 seen in 52%, and those compared to patients with eGFR > 60, had mean baseline eGFR of 35 (vs 90), were older (68 vs 60 with 61% above age 65 vs 41%), 81% had DM (vs 60%), 85% had HTN (vs 63%), 46% had cardiac disease (vs 24%). Cause of AKI was pre-renal / ischemic ATN in 87%, COVID-19 related in 8%, contrast-associated in 6%, drug-induced AIN in 5% of cases. Many had more than one possible cause. Sepsis was most common precipitating factor seen in 67% then volume depletion in 50%. Many had more than one factor. IV fluids used in 73% (less in lower eGFR group), IV diuretics in 46% (more in lower eGFR group), IV vasopressors in 40% (less in lower eGFR group) and steroids in 33%. KRT needed in 33%, more in patients who used diuretics or vasopressors. Volume overload and electrolytes / acid-base disorders were most common indication (75% and 79% respectively). CKRT was modality of choice in 85%, however, in 52% of CKRT, conventional HD not used due to lack of dialysate source in some sites. At 30 days, mean eGFR was 42%, with complete recovery in 34%, and 38% failed to recover at all. Death occurred in 31%, 55% had baseline eGFR > 60, and 50% of deaths occurred while still on KRT. Non-survivors were older and had higher use of vasopressors. AKI associated mortality in 25% of total hospital mortality and in 31% of ICU / CCU mortality. Conclusions: AKI is common. Most cases hospital-acquired. Use of resources (medications, critical care, KRT) and rates of mortality are high. Kuwaiti citizens represent 1/3 of the population and 2/3 of AKI cases and almost 70% of deaths.

Prediction of COVID-19 Disease with Chest X-Rays Using Convolutional Neural Network

With the rising of the new pandemic, problems to detect the presence of Covid-19 also emerged. To track the infections, RT-PCR and rapid testing are followed in the current situation which is time-consuming and could be an important time for severe patients. To decrease the amount of time for COVID-19 prediction, Chest X-rays could play an important role in determining the result. So by using Chest X-rays with Artificial Intelligence, the COVID-19 disease can be detected in a lesser amount of time under the guidance of the specialist. For this, the Deep Learning techniques like Convolutional Neural Networks (CNN) have been proved quite successful for image recognition and classification. In this experiment, Covid-19 was detected with the help of ResNet architecture whose accuracy increases while going into deeper layers by using skip connections. ResNet is a pre-trained model on the ImageNet database. During the experiment, ResNet18 architecture was used because it has the least number of layers as compared to other CNN architectures and so, for determining the best accuracy obtained with lesser computations. Methods like k-fold cross-validation, confusion matrices, etc were used in obtaining the accuracy of around 89% for COVID-19 prediction. Hence, CNN could be a useful tool for the prediction of COVID-19 and saving time for both patients and doctors for further treatment. © 2021 IEEE.

COVID-19: Current Knowledge and Best Practices for Orthopaedic Surgeons

Background: A mysterious cluster outbreak of pneumonia in Wuhan, China in December 2019 was traced to Severe Acute Respiratory Syndrome Coronavirus 2 and declared a Pandemic by WHO on 11th March 2020. The pandemic has spread rapidly causing widespread devastation globally. Purpose: This review provides a brief understanding of pathophysiology, clinical features, diagnosis and management of COVID-19 and highlights the current knowledge as well as best practices for orthopaedic surgeons. These are likely to change as knowledge and evidence is gained. Results: Orthopaedic surgeons, like other front-line workers, carry the risk of getting infected during their practice, which as such is already substantially affected. Implementation of infection prevention and control as well as other safety measures for health care workers assumes great importance. All patients/visitors and staff visiting the hospital should be screened. Conservative treatment should be the first line of treatment except for those requiring urgent/emergent care. During lockdown all elective surgeries are to be withheld. All attempts should be made to reduce hospital visits and telemedicine is to be encouraged. Inpatient management of COVID-19 patients requires approval from concerned authorities. All patients being admitted to the hospital in and around containment zones should be tested for COVID-19. There are special considerations for anaesthesia with preference for regional anaesthesia. A separate Operation room with specific workflow should be dedicated for COVID-19 positive cases. Conclusions: Despite the magnitude of challenge, the pandemic offers significant lessons for the orthopaedic surgeon who should seek the opportunity within the adversity and use this time wisely to achieve his/her Ikigai.