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Objectives: To provide an overview of trends in the current evidence landscape of products and services in development that support remote patient monitoring (RPM) and remote therapeutic monitoring (RTM), given the release of new billing codes for RPM and RTM by Centers for Medicare and Medicaid Services (CMS) in 2019. Method(s): A focused literature review was conducted in PubMed. Articles published between January 1, 2013 and January 1, 2023 were eligible for inclusion if reported technologies were classified as RPM (defined as the collection and interpretation of physiologic data digitally stored and/or transmitted by patients and/or caregivers to qualified health care professionals) or RTM (defined as the use of medical devices to monitor a patient's health or response to treatment using non-physiological data), following CMS definitions. RPM and RTM technologies included hardware, software, telehealth, and blockchain applications. Articles were then categorized using a semi-automated software platform (AutoLit, Nested Knowledge, St. Paul, MN) based on disease area, study design, intervention, and outcomes studied. Result(s): Of the 673 records screened, 245 articles were included. Observational studies (19.6%) were the most common study design, followed by systematic or focused literature reviews (11.0%) and narrative reviews (10.6%). The most common disease areas included cardiology (25.7%), coronavirus disease of 2019 (COVID-19;13.9%), and diabetes (9.4%). The most frequent clinical, non-clinical, and patient-reported outcomes were symptom monitoring (20.8%), all cause readmission and hospitalization rates (both 7.3%), and patient experience (7.8%), respectively. Conclusion(s): CMS policy and coding practices for RPM and RTM are evolving, and this trend is likely to continue into the future. This review provides details on the current evidence trends associated with RPM/RTM technologies. Evidence development of RPM and RTM should be assessed as evidence needs for coverage and reimbursement may receive increased payer management.Copyright © 2023
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Widely considered safe, effective, and essential for pathogenic immunity, vaccines have proven to be one of the most important discoveries to date in medicine. Adverse reactions to vaccines are typically trivial but there have been extremely rare reports of vaccine induced myocarditis, particularly with the Tdap vaccine. This is thought to be due to a hypersensitivity reaction. In efforts to combat the SARS-CoV-2, prompt response from Pfizer-BioNTech and Moderna lead to vaccine development with a novel method, synthesized from modified messenger RNA. Despite minimal side effects on initial trials, reports of vaccine induced myocarditis have resulted. A majority of these cases occurred following subsequent doses for those previously inoculated. A descriptive study published in JAMA in January 2022 reviewed the Vaccine Adverse Event Reporting System (VAERS) in collaboration with the CDC described only 1626 cases of myocarditis, of which the majority occurred within days of the second dose. This review was limited by reviewing a passive reporting syndrome with variable quality data and without follow up data post diagnosis of myocarditis. Here we present a case of myocarditis occurring less than 24 hours after the second dose of Pfizer-BioNTech vaccine with 3 month follow up. A 23 year old man received his second dose of the COVID-19 vaccine in the morning. Within a few hours he experienced chest pain, chills, weakness, and fatigue. These dissipated by 7pm. He is a member of the National Guard and during drills the next day experienced stabbing substernal chest pain for which he sought evaluation. The pain radiated into his left jaw, worse with deep inspiration and worse in the left lateral decubitus position. He is a 1 PPD smoker with no personal or family history or cardiac disease. A friction rub was heard on physical exam. His troponin I peaked at 2.6ng/mL. His EKG showed normal sinus rhythm, a TTE showed a normal EF with no pericardial effusion. He was given aspirin 81 mg and started on a heparin drip for possible NSTEMI. The next day his pain decreased and a cardiac MRI demonstrated no inflammation. His serum coxsackie and parvovirus titers were negative. He was instructed to continue the aspirin, limit exercise for 8 weeks, and stop smoking. Upon follow up 3 months later the patient denied any recurrent chest pain and was advised to continue the aspirin. But the original bout of myocarditis limited his participation in the National Guard. Our case illustrates that exposure to an immunological trigger, the COVID-19 vaccine, leading to myocarditis was extremely short compared to typical cases of viral induced or vaccine hypersensitivity reaction. A proposed mechanism is molecular mimicry between the spike protein and myocardial contraction proteins. It also demonstrates that the vaccine can cause morbidity in patients, especially younger males. It also exemplifies that this may be a short lived phenomenon, long term follow up is still needed. With the rate of vaccination increasing, there needs to be a low threshold to consider myocarditis in young adults who have new chest pain after receiving an mRNA based vaccine.Copyright © 2022
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In acute care settings hearing loss (HL) is associated with impaired patient-provider communication, increased length of stay, and increased mortality. COVID-19 has exacerbated this problem with the widespread use of masks and eye shields which muffle speech and prevent lip reading. Our 800-bed tertiary care medical center lacked a standardized approach to identify patients with HL and address communication barriers. Three first year medical students spearheaded the initiative as part of a health systems improvement curriculum with support from a faculty coach and a faculty researcher. From September 2020 to October 2021, the students met with stakeholders, leadership and champions and unit staff, identified the current state and completed a gap analysis through interviews, surveys, and direct observation. The pilot in May 2021 included two week-long PDSA cycles on one hospital unit to: 1) screen patients aged 65 and older using the validated 10-item HHIE-S questionnaire, 2) implement an education and awareness campaign with bedside signage, posters, and conferences and 3) provide a personal amplifier (purchased in bulk by the medical center) with verbal and written instructions. A total of 29 patients screened positive and were given personal amplifiers. Post-pilot interviews reported increased provider awareness and knowledge around best communication practices. Patients and staff reported limited amplifier use due to poor sound quality, small dials, poorly fitting ear buds and a short battery life. Based on these results the team recommended discontinuing the personal amplifiers and identifying other communication tools including higher quality personal amplifiers and speech to text applications.
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Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, a plethora of ultraviolet-C (UV-C) disinfection products have come to market, especially in emerging economies. UV-C–based disinfection products for mobile phones, food packaging, face masks and personal protective equipment (PPE), and other everyday objects are available in popular electronic-commerce platforms as consumer products. Product designers from multinational to startup companies began to design UV-C disinfection products but had no prior-art reference, user feedback, or validation of product efficacy, which are important stages in product design. A UV-C disinfection product cannot be assessed by most consumers for its viricidal efficacy. Many firms entered the domain of UV-C products and were unaware of the necessary validation requirements. Lack of availability and access to virology laboratories, due to lockdowns in countries, and lack of standards and certification for UV-C disinfection products limited product designers and firms in benchmarking their UV-C–based devices before market release. This work evaluates two UV-C disinfection devices for viricidal efficacy on PPE fabric and National Institute for Occupational Safety and Health (NIOSH)–certified N95 respirators through controlled experiments using the H1N1 virus, which is enveloped and is transmitted via the respiratory route similar to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of COVID-19. The experiment also evaluated the effectiveness of chemical disinfectants along with and versus UV-C disinfection. Experiments for material selection, UV dose calculation, and UV endurance of PPE samples to be disinfected are also discussed. The outcome of this work establishes a systematic method to validate the efficacy of UV-C disinfection products. The design guidelines would benefit product designers in designing UV-C–based disinfection products.
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We welcome readers to this special issue of Journal of International Women’s Studies (JIWS). The articles presented in this special issue are topics discussed during the 8th Virtual International Conference on “Gender Equity: Barriers, Inclusion and Enablers,” conducted by the Womens’ Empowerment Cell of Kristu Jayanti College (Autonomous), Bangalore, India. A gender gap is defined as gender-based inequality or any disparity in treatment or situation between genders in social, cultural and legal norms and customs. Gender gaps create barriers to gender equity by limiting or restricting women’s access to resources and decisionmaking opportunities. Means such as violence are used against women to control resources and opportunities, reinforcing power imbalances and gender inequality. Living solely offline in 2022 resembles a bygone era as connectivity and technology have indubitably become integral parts of most people’s daily lives. With governments around the globe imposing lockdowns and movement restrictions to curb COVID-19 infections, businesses and organizations have swiftly adapted to reinvent themselves to survive. This has worsened social, gender, and racial inequality in addition to taking a heavy toll on the global economy, public health, and policymaking. It is now estimated that it would take 135.6 years to achieve gender equality, one generation leap backward from the 99.5 years estimated in 2020. © 2022, Journal of International Women''s Studies. All Rights Reserved.
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The demand for carbon nanomaterials (CNMs) in the development of sensors is rising from various end-use sectors such as chemical, medical, automotive, food safety, and energy due to their advantageous intrinsic properties that include chemical resistance, electrical conductivity, optical clarity, flame retardance, thermal stability, surface appearance, decreased water permeability, dimensional stability, and more. These inherent characteristics of zero-, one-, two-, and three-dimensional CNMs, such as graphene, fullerenes, carbon nanotubes (CNTs), nanodiamonds (NDs), carbon quantum dots (CDs), graphene quantum dots (GQDs) carbon nanofibers (CNFs), carbon nanohorns (CNHs), carbon nano-onions (CNOs), and carbon black (CB), are being utilized in recent years in the development of advanced technologies for sensing applications., Although sensors based on CNMs are promising, they have nevertheless faced many practical challenges to be used in different fields of applications. For instance, their processing is not cost-effective for large-scale manufacturing of high-purity nanomaterials, which is the key reason why the existing market prices for CNMs in the fabrication of sensors are costly, thereby limiting their commercial applications in this sector. In terms of value and volume, this chapter identifies, explains, and forecasts the global demands of sensors based on CNMs and it provides detailed information regarding the emerging trends, concerns, and factors influencing the growth of the market. © 2022 Elsevier Inc. All rights reserved.
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BACKGROUND: Vaccine hesitancy leads to an increase in morbidity, mortality, and health-care burden. Reasons for vaccine hesitancy include anti-vax group statements, misinformation about vaccine side effects, speed of vaccine development, and general disbelief in the existence of viruses like COVID-19. Medical students are future physicians and are key influencers in the uptake of vaccines. Hence, investigating vaccine hesitancy in this population can help to overcome any barrier in vaccine acceptance. METHODS: In this paper, we review five articles on COVID-19 vaccine hesitancy in medical students and consider potential future research. All published papers relevant to the topic were obtained through extensive search using major databases. Inclusion criteria included studies that specifically investigated COVID-19 vaccine hesitancy in medical students published between 2020 and 2021. Exclusion criteria included studies that investigated vaccine hesitancy in health-care professionals, allied health, and viruses apart from COVID-19. A total of 10 studies were found from our search. RESULTS: Based on our exclusion criteria, only five studies were included in our review. The sample size ranged from 168 to 2133 medical students. The percentage of vaccine hesitancy in medical students ranged from 10.6 to 65.1%. Reasons for vaccine hesitancy included concern about serious side effects, vaccine efficacy, misinformation and insufficient information, disbelief in public health experts, financial costs, and belief that they had acquired immunity. CONCLUSION: These results suggest that vaccine hesitancy is an important cause of the incidence and prevalence of COVID-19 cases. Identifying the barriers of vaccine hesitancy in prospective physicians can help increase vaccination uptake in the general public. Further research is necessary to identify the root cause of these barriers. © Shahad A. Hafez et al., 2022;Published by Mary Ann Liebert, Inc. 2022.
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RATIONALE: Around 4.6 million people in the United Kingdom (UK) have asthma, with an estimated 5.7% treated for severe asthma. Benralizumab is indicated for the treatment of severe eosinophilic asthma (SEA) in adults inadequately controlled despite appropriate maintenance therapy. The Connect 360 Patient Support Programme (PSP) for patients on benralizumab includes options for home-based drug administration, education and adherence support by trained nurses - of particular relevance during the COVID-19 pandemic. Limited evidence exists on the benefit of PSPs for asthma patients or those administering biological therapies at home. This study aims to describe patient characteristics, key outcomes and experience with the PSP using UK data from Connect 360. METHODS: A non-interventional, retrospective cohort study of patients, enrolled in the PSP (Oct-2019 onwards) and consenting to the use of personal data for research purposes (“study cohort”). Patients opting for additional support services with at least one nurse interaction within described study timeframes formed the clinical cohort. Patients were observed up to 48 weeks post-PSP enrolment (interim data taken on 31-Mar-2021;data collection ongoing) with study endpoints assessed at baseline (0-4 weeks), 24 (±4) weeks and 48 (±8) weeks post-PSP enrolment. Characteristics at enrolment are described for the study cohort. Patient-reported clinical outcomes (hospitalisations, maintenance oral corticosteroid [mOCS] use, Asthma Control Questionnaire [ACQ-6] scores) and service satisfaction (1-5 point scale, 5 being most satisfied) were analysed where available from routine PSP nurse calls/visits. Analysis was descriptive;Kaplan-Meier estimators were used to estimate PSP discontinuation rates. RESULTS: The study cohort was 611 patients (mean enrolment age: 54.1 years, 63.2% female [N=323]). Most (98.9%) were benralizumab users on maintenance dosing (8-weekly) at enrolment. The clinical cohort consisted of 149 (baseline), 175 (24 weeks) and 195 (48 weeks) patients. PSP discontinuation rates were 4.4% and 11.6% at 24 and 48 weeks. Proportion of patients reporting mOCS use was 49.7%, 44.0% and 32.8% at each timepoint and hospitalizations were 10.9% and 4.1% at 24 and 48 weeks. Mean ACQ-6 scores decreased over time. Mean (SD) satisfaction scores were 4.6 (0.7) and 4.8 (0.5) at 24 and 48 weeks, respectively. (Table 1). CONCLUSIONS: Overall patients' experience with the PSP was positive, evidenced by high satisfaction with and persistence to the PSP. Where data were available, proportion of patients reporting mOCS and hospitalizations at 48 weeks were numerically lower than previous timepoints and mean ACQ-6 scores improved, suggesting a positive impact of benralizumab treatment within the PSP.
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Background: Globally Covid 19 has leased almost all domains of human life in and around;business, education, tourism and so on are not an exception. Medical professionals are group which actively got involved in this disaster management arena. Training of medical and nursing professionals has also got into stake or it got narrowed into online mode of education. Methods: A phenomenological qualitative study was conducted to identify perceived benefits and challenges confronted by nursing students of a selected nursing college in Northern India. Data was collected from thirty nursing students with the help of a validated focus group discussion guide. Five FGD were conducted to collect data until availing data saturation. Data was transcribed, coded and developed themes, sub-themes based on codes keeping participant verbatim in support. Results: The thematic content analysis of Data revealed four core themes 1) academic usefulness, 2) Time effectiveness, 3) Challenges faced, 4) attitude and perception of students and couple of sub themes along with it. Overall impression of the study shows nursing students were less favorable to online mode of learning. Conclusion:This study portrays out all aspects pertaining to online education mode considering ill effects and benefits as perceived by nursing students from their nearly one year of experience. © 2022 Author(s).
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Background: The occurrence of invasive fungal infections in COVID-19 patients is on surge in countries like India. Several reports related to rhino-nasal-sinus mucormycosis in COVID patients have been published in recent times;however, very less has been reported about invasive pulmonary fungal infections caused mainly by mucor, aspergillus or invasive candida species. We aimed to present 6 sputum culture proved cases of invasive pulmonary fungal infection (four mucormycosis and two invasive candidiasis) in COVID patients, the clues for the diagnosis of fungal invasion as well as difficulties in diagnosing it due to superimposed COVID imaging features. Case presentation: The HRCT imaging features of the all 6 patients showed signs of fungal invasion in the form of cavities formation in the pre-existing reverse halo lesions or development of new irregular margined soft tissue attenuating growth within the pre-existing or in newly formed cavities. Five out of six patients were diabetics. Cavities in cases 1, 2, 3 and 4 of mucormycosis were aggressive and relatively larger and showed relatively faster progression into cavities in comparison with cases 5 and 6 of invasive candidiasis. Conclusion: In poorly managed diabetics or with other immunosuppressed conditions, invasive fungal infection (mucormycosis, invasive aspergillosis and invasive candidiasis) should be considered in the differential diagnosis of cavitary lung lesions.
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Purpose The purpose of this study is two-fold. First, to identify and encapsulate the enablers that can facilitate technology integration in higher education and second, to understand and analyze the interplay between technology agility enablers. Design/methodology/approach The study used the Total Interpretive Structural Modeling (TISM) approach to construct a theoretical model of the technology agility enablers in higher education and MICMAC analysis for ranking and segregating the enablers based on their dependence power into four categories: Autonomous, Dependent, Linkage and Independent. Findings The study helped identify eight technology agility enablers, with the Covid-19 pandemic as the most significant enabler. The Covid-19 pandemic has catalyzed the diffusion of technology across the education sector in India, including tertiary higher education. The study revealed government initiatives and institutional commitment as other enablers that can promote technology agility in higher education. Practical implications The results of this study would assist the policymakers and management of universities and colleges in understanding the important enablers that can facilitate technology integration in higher education. Originality/value Research in the past on technology adoption in higher education has looked into each enabler in isolation. This research provides a comprehensive view of the enablers and has attempted to establish a multidirectional interplay between the enablers.
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The demographic dividend is an essential measure of the growth and development of a country. It refers to the economy’s growth due to a shift in the age structure in the country’s population. In India, around 90% of the population is under the age of 60, which is a stark contrast compared to the world, where more than 20% of the population lies above 60. Such a young population ensures that the working-age group will be vibrant in the coming years, adding to the country’s overall productivity. Today, COVID has caused much damage to an already vibrant economy, because of which millions of people have lost their jobs and have had to migrate back to their hometowns. To recover from this severe damage and take stock of the existing and incoming workforce, it is necessary to identify and analyze the current population that lies in suitable age ranges and understand how to use them optimally. Therefore, analyzing the demographic dividend to identify the workforce of the country becomes an essential task. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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COVID-19 is an air-borne viral infection, which infects the respiratory system in the human body, and it became a global pandemic in early March 2020. The damage caused by the COVID-19 disease in a human lung region can be identified using Computed Tomography (CT) scans. We present a novel approach in classifying COVID-19 infection and normal patients using a Random Forest (RF) model to train on a combination of Deep Learning (DL) features and Radiomic texture features extracted from CT scans of patient's lungs. We developed and trained DL models using CNN architectures for extracting DL features. The Radiomic texture features are calculated using CT scans and its associated infection masks. In this work, we claim that the RFs classification using the DL features in conjunction with Radiomic texture features enhances prediction performance. The experiment results show that our proposed models achieve a higher True Positive rate with the average Area Under the Receiver Curve (AUC) of 0.9768, 95% Confidence Interval (CI) [0.9757, 0.9780]. © 2021 IEEE.
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Introduction: The Coronavirus Virus Disease 2019 (COVID-19) pandemic has affected many social organisations with the workplace being amongst those most affected. Organisation faced the challenge of continued productivity during a global health crisis. Employees have shown signs of fatigue caused by living with the persistent fear and anxiety of falling sick and this which can consequently resulted in a reduction in productivity and frequently reduced income. Measures that were introduced to keep people safe such as social distancing, lockdowns, new working styles together with necessary lifestyle changes such as social isolation have reinforced feelings of uncertainty and fear amongst the workforce. These factors have influenced the mental health of workers and will continue to do so as society reorganise and make the changes necessary to accommodate new systems. Purpose: The purpose of this literature review is to conceptualize the psychological aspects linked to workplace factors following the rise of COVID-19 to epidemic proportions and in order to address upcoming psychological critical issues in the workplaces. Method: This literature study proceeded a search engine using Google Scholar, PubMed, and Scopus, using keywords SARS-CoV-2, COVID-19 pandemic, occupational health and safety, mental health, psychological disorders, COVID 19 and working people, workplace organization and selected 30 articles out of thirty 20 articles were analyzed corroding to researchers need. The literature information is further narrated and draws on insights of the researcher. Conclusion: The review study conceptualizes the pandemic spread of COVID-19 and reviews its effect in the workplace as companies reorganize and establish new patterns of operations in response the COVID-19 virus and to ensure precautionary measure against further spread of the disease. The adaptations necessary in the wake of this disease have novel reorganization in both structural and functional areas. The workforce at the workplace underwent loss of its psychological homeostasis. The mitigation which ensured has led to multiple organizational and work-related interventions intended to be instrumental in defending health-related safety in the workplaces. © RJPT All right reserved.
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Network (cGAN) architecture that is capable of generating 3D Computed Tomography scans in voxels from noisy and/or pixelated approximations and with the potential to generate full synthetic 3D scan volumes. We believe conditional cGAN to be a tractable approach to generate 3D CT volumes, even though the problem of generating full resolution deep fakes is presently impractical due to GPU memory limitations. We present results for autoencoder, denoising, and depixelating tasks which are trained and tested on two novel COVID19 CT datasets. Our evaluation metrics, Peak Signal to Noise ratio (PSNR) range from 12.53 - 46.46 dB, and range from 0.89 to 1. © 2020 IEEE.
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Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, a plethora of ultraviolet-C (UV-C) disinfection products have come to market, especially in emerging economies. UV-C-based disinfection products for mobile phones, food packaging, face masks and personal protective equipment (PPE), and other everyday objects are available in popular electronic-commerce platforms as consumer products. Product designers from multinational to startup companies began to design UV-C disinfection products but had no prior-art reference, user feedback, or validation of product efficacy, which are important stages in product design. A UV-C disinfection product cannot be assessed by most consumers for its viricidal efficacy. Many firms entered the domain of UV-C products and were unaware of the necessary validation requirements. Lack of availability and access to virology laboratories, due to lockdowns in countries, and lack of standards and certification for UV-C disinfection products limited product designers and firms in benchmarking their UV-C-based devices before market release. This work evaluates two UV-C disinfection devices for viricidal efficacy on PPE fabric and National Institute for Occupational Safety and Health (NIOSH)-certified N95 respirators through controlled experiments using the H1N1 virus, which is enveloped and is transmitted via the respiratory route similar to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of COVID-19. The experiment also evaluated the effectiveness of chemical disinfectants along with and versus UV-C disinfection. Experiments for material selection, UV dose calculation, and UV endurance of PPE samples to be disinfected are also discussed. The outcome of this work establishes a systematic method to validate the efficacy of UV-C disinfection products. The design guidelines would benefit product designers in designing UV-C-based disinfection products.
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COVID-19 is a novel infectious disease responsible for over 1.2 million deaths worldwide as of November 2020. The need for rapid testing is a high priority and alternative testing strategies including x-ray image classification are a promising area of research. However, at present, public datasets for COVID-19 x-ray images have low data volumes, making it challenging to develop accurate image classifiers. Several recent papers have made use of Generative Adversarial Networks (GANs) in order to increase the training data volumes. But realistic synthetic COVID-19 x-rays remain challenging to generate. We present a novel Mean Teacher + Transfer GAN (MTT-GAN) that generates COVID-19 chest x-ray images of high quality. In order to create a more accurate GAN, we employ transfer learning from the Kaggle pneumonia x-ray dataset, a highly relevant data source orders of magnitude larger than public COVID-19 datasets. Furthermore, we employ the Mean Teacher algorithm as a constraint to improve stability of training. Our qualitative analysis shows that the MTT-GAN generates x-ray images that are greatly superior to a baseline GAN and visually comparable to real x-rays. Although board-certified radiologists can distinguish MTT-GAN fakes from real COVID-19 x-rays, quantitative analysis shows that MTT-GAN greatly improves the accuracy of both a binary COVID-19 classifier as well as a multi-class pneumonia classifier as compared to a baseline GAN. Our classification accuracy is favorable as compared to recently reported results in the literature for similar binary and multi-class COVID-19 screening tasks.