How to Keep Home Healthcare on Target

Home visits have the power to ease the clinical trial process for patients, but complex study design, tight timelines, busy clinical operations teams, and overburdened sites can sometimes make home health feel like yet another moving piece to manage. Individual variables that play a large role in establishing timelines can include factors like: * Amount of protocol-specific training required. * Level of engagement during a visit. * On-site processing requirements. * Drug or sample stability. * Recruitment goals. [...]all training should be to the full satisfaction of the principal investigator overseeing the study. Since sites are still responsible for the conduct of home visits from a regulatory perspective, there is often a concern about how they can remain in control of the progress without overwhelming the already busy study team and staff.

Long Term, Pre, and Post Impacts of SARS-CoV-2 Pandemic on Road Traffic Crashes in the Case of Budapest, Hungary

SARS-CoV-2 is a pandemic that affects road traffic flaw and crashes globally. This study attempted to compare the situation of road traffic crashes in the city of Budapest before and after the SARS-CoV-2 pandemic to better understand its long-term percussive effects. The study considers 12208 road traffic crashes that registered between 20 May 2018 – 31 December 2021. The rate and severity of road traffic crashes during the SARS-CoV-2 pandemic examined by using a percentage frequency distribution and a severity index. This study depicted that most crashes reported during the normal daytime between15:01-18:00 (peak hour). The study indicated that during the SARS-CoV-2 pandemic the road traffic crashes were reduced by 20.15%. A rear-end collision was one of the most common type of catastrophes highly registered. Road users, particularly drivers, heavily endorsed crashes. Even though the proportion of road traffic crashes caused by alcohol consumption was modest (6%), the rate of alcohol consumption and its concentration increased slightly during the SARS-CoV-2 pandemic. At the same time the number of crashes caused by high-speed traffic maneuvers reduced. Improper interpretation of road traffic signs, road pavement condition and failure to respect proper sight distance were influential reasons of road traffic crashes among the top. Meanwhile, the distributional impact of careless driving in the aftermath of the SARS-CoV-2 pandemic causes a shift in rank. Therefore, this study proved that during SARS-CoV-2 pandemics road traffic crashes reduced, the rate and concentration of alcohol consumption increased, and careless driving was encouraged.

AI and Dynamic Prediction of Deterioration in Covid-19

During the COVID-19 pandemic it became evident that outcome prediction of patients is crucial for triaging, when resources are limited and enable early start or increase of available therapeutic support. COVID-19 demographic risk factors for severe disease and death were rapidly established, including age and sex. Common Clinical Decision Support Systems (CDSS) and Early Warning Systems (EWS) have been used to triage based on demographics, vital signs and laboratory results. However, all of these have limitations, such as dependency of laboratory investigations or set threshold values, were derived from more or less specific cohort studies. Instead, individual illness dynamics and patterns of recovery might be essential characteristics in understanding the critical course of illness.The pandemic has been a game changer for data, and the concept of real-time massive health data has emerged as one of the important tools in battling the pandemic. We here describe the advantages and limitations of established risk scoring systems and show how artificial intelligence applied on dynamic vital parameter changes, may help to predict critical illness, adverse events and death in patients hospitalized with COVID-19.Machine learning assisted dynamic analysis can improve and give patient-specific prediction in Clinical Decision Support systems that have the potential of reducing both morbidity and mortality. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Work context and clinical manifestations of COVID-19 in health professionals

To analyze associations between work context and clinical manifestations of COVID-19 in health professionals. Methods: This is a cross-sectional study, with health professionals from the northeast of Brazil, from the medical, nursing and physiotherapy categories from different areas of expertise. A Google Forms questionnaire was sent through social networks, gathering demographic, academic, work context, clinical manifestations and data related to testing for COVID-19 (the test performed was not specified) and whether the result confirmed infection active or presence of antibodies (categorized as positive). Pearson's chi-square test and multivariate binary logistic regression analysis were performed, with Wald's chi-square test, considering p-value <0.05, Odds Ratio and 95% confidence interval. Results: A total of 1,354 professionals agreed to participate in the study. Of these, 324 reported a positive test for COVID-19, with a prevalence of 23.9% (324/1,354). There was a statistical association between symptom onset and positive result (p=0.000). The work context characteristics related to the number of jobs, practice setting, contact with critically ill patients and employment in the capital were the independent variables associated with a positive result for COVID-19 (p<0.05). It was identified that 54.8% of the dependent variable can be related to the work sector, number of jobs, fever, loss of smell and taste. Conclusion: Health professionals from urban centers, hospitals, critical care units and those with more than one job are more affected by COVID-19, with the positive test result being closely related to the symptoms of fever, loss of smell and taste that are characteristic of the illness. © 2022 Departamento de Enfermagem/Universidade Federal de Sao Paulo. All rights reserved.

Effects of oral of administration of monoglycide laurate on virus load and inflammation in PEDV infected porcine.

To investigate the effect of monoglyceryl laurate (GML) against PEDV in vivo, the clinical signs, pathological changes, tissue viral load and cytokine levels of piglets were compared in different GML treatment groups and PEDV infected group. The diets of experimental groups were supplemented with different doses of GML (5g for A1, 10g for A2, 20g for A3) on day 1, 2, and 3 after PEDV challenge, and the virus challenge group (group C) and blank group (group B) were set as control. The results showed that compared with group C, groups As could reduce the mortality rate of piglets, among which the protection rates of groups A2 and A3 could reach 100%. The trend of weight loss of piglets was effectively slowed down and growth performance recovered in GML treated groups. GML reduced the pathological damage of intestinal tract and the viral load in intestine and mesenteric lymph nodes. The levels of IL-8 and TNF-α in the blood of group As were inhibited by GML in a dose-dependent manner when compared with group C. Our study suggests that GML has potential anti-PEDV effects in vivo.

The long-term effects of the Covid-19 infection on cardiac symptoms.

BACKGROUND: Besides the lungs, coronavirus disease 2019 (COVID-19) can affect the cardiovascular, digestive, urinary, hepatic, and central nervous systems. Other than its short-term effects, COVID-19 may also cause long-term complications. In this study, we assessed long-term COVID-19 cardiovascular symptoms among patients in a cardiovascular clinic. METHOD: A retrospective cohort was conducted between October 2020 to May 2021 on patients at an outpatient cardiovascular clinic in Shiraz, Iran. Patients with a history of COVID-19 at least one year before their referral were included. Baseline information was extracted from the clinic's database. Data were collected regarding symptoms like dyspnea, chest pain, fatigue, and palpitations after a year of COVID-19. We also noted any major adverse cardiac events (MACE). RESULTS: Most common symptoms after a year of COVID-19 were exertional dyspnea (51.2%), dyspnea at rest (41.6%), fatigue (39%), and chest pain (27.1%). The symptoms were more prevalent in hospitalized patients than in non-hospitalized patients. The prevalence of MACE was about 6.1% during the 12-month follow-up, with this rate being higher in those with a history of hospitalization or comorbid diseases. CONCLUSION: The prevalence of cardiovascular symptoms was fairly high in patients at our clinic a year after COVID-19, and the most common symptom was dyspnea. Hospitalized patients had more MACE. (Clinicaltrial.gov number: NCT05715879)(04/02/2023).

Etiological factors of chronic pain syndrome in young adults with post-coronavirus disease 2019 condition.

PURPOSE: The coronavirus disease 2019 (COVID-19) generates long-term sequelae, but studies investigating patients with chronic pain syndrome (CPS) are limited. This study aimed to establish the etiological factors of CPS in patients with post-COVID-19 conditions. METHODS: This was a case-control retrospective study. The predictor variables were sex, diabetes mellitus, obesity (predisposing factors), unfavorable socioeconomic conditions, impaired rehabilitation (disabling factors), repeated exposure to COVID-19 (precipitating factor), home isolation, stress overload, fear of dying, admission to intensive care unit, prone positioning, and use of medications (reinforcing factors). The outcome variable was the presence of CPS. FINDINGS: This study included 120 individuals. Prolonged days of isolation (p = 0.005), fear (p < 0.001), stress overload (p < 0.001), and impaired rehabilitation (p = 0.003) were significantly associated with CPS. CONCLUSIONS: A significant relationship was found between prolonged days of isolation, fear, stress overload, impaired rehabilitation, and CPS. IMPLICATIONS FOR NURSING PRACTICE: The study findings can assist nurses by promoting their knowledge of the causes of CPS and supporting the care planning needs of patients with post-COVID-19 conditions, in addition to promoting the use of the NANDA-International taxonomy.

The Pi-CON Methodology Applied: Operator Errors and Preference Tracking of a Novel Ubiquitous Vital Signs Sensor and Its User Interface

Remote Patient Monitoring has enjoyed strong growth to new heights driven by several factors, such as the COVID-19 pandemic or advances in technology, allowing consumers and patients to continuously record health data by themselves. This does not come without its challenges, however. A literature review was completed and highlights usability gaps when using wearables or home use medical devices in a virtual environment. Based on these findings, the Pi-CON methodology was applied to close these gaps by utilizing a novel sensor that allows the acquisition of vital signs at a distance, without any sensors touching the patient. Pi-CON stands for passive, continuous and non-contact, and describes the ability to acquire vital signs continuously and passively, with limited user interaction. The preference of vital sign acquisition with a newly developed sensor was tested and compared to vital sign tests taken with patient generated health-data devices (ear thermometer, pulse oximeter) measuring heart rate, respiratory rate and body temperature. In addition, the amount of operator errors and the user interfaces were tested and compared. Results show that participants preferred vital signs acquisition with the novel sensor and the developed user interface of the sensor. Results also revealed that participants had a mean error of .85 per vital sign measurement with the patient-generated health data devices and .33 with the developed sensor, confirming the beneficial impact available when using the developed sensor based on the Pi-CON methodology.

Affective Immediately: Reading the Semiotic Landscape of COVID-19 in Lincoln, Nebraska

For this chapter, I raise social psychologist Margaret Wetherell's metaphorical sledgehammer, breaking down the affective-discursive practices which come freighted with emotions, politics, as well as the promise of dignity and a renascent sense of community as we transition into, through and eventually out of, coronacrisis. I examine how we make meaning during COVID, across thresholds of physical distance, observing the ad hoc signage which mark interventions into public space through queueing stickers, yard signs, and window decals which help us navigate through the everyday spaces of the pandemic. Here, I conduct multimodal discourse analysis of the semiotic landscapes of Lincoln, Nebraska and Sioux Falls, South Dakota during the height of the first wave of the pandemic (Spring into Summer 2020) in the Great Plains region of the United States. I argue that these semiotic landscapes form a diverse, polysemic affective regime spatialized across a patchwork of bodies. By analyzing the affective regimes and practices instantiated by ad hoc signage in public spaces, I aim to understand the discursive and embodied (and discursively embodied) forces which quicken common things and common landscapes with theoretical importance in these exceptional times. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Bioinformatic Screening of Compounds from Iranian Lamiaceae Family Members against SARS-CoV-2 Spike Protein

Background: COVID-19 (coronavirus disease 2019) is still a major challenge worldwide. The disease is caused by binding the coronavirus to ACE2 receptors on lung cells, infecting the cells and triggering the onset of symptoms. The prevention of such a binding in which the virus is eventually unable to enter the cell could be a promising therapeutic approach.Methods: In this in silico study, 306 compounds of Lamiaceae family native in Iran (native Mints) were retrieved from several databases as 3D structures, and after that molecular docking and virtual screening, the compounds with inhibitory potential were selected in terms of free energy binding against the spike protein of the virus. The pharmacokinetic profile of selected compounds was evaluated, and by molecular dynamic simulation and MM/PBSA, four compounds were further assessed for binding affinities against the receptor-binding domain of the spike.Results: The results showed the Catechin gallate and Perovskone B from Stachys and Salvia genus generated a stronger binding affinity, and therefore could act as potential inhibitory compounds of RBD of the SARS-CoV-2 spike protein.Conclusion: This study revealed that some members of the Lamiaceae family could be employed to inhibit SARS-CoV-2 activity through interaction with spike protein and therefore could be used for further investigation in vitro and in vivo.

IOT based Temperature and Oxygen level monitoring and Data visualization

The Covid-19 pandemic that hit us in 2020 changed our lifestyle in every way. There was tremendous damage to people's lives. It is now predicted that other variants of Coronavirus are affecting people's health throughout the world. We must remain vigilant against upcoming dangers. The Indian health ministry has also advised people to take the necessary precautions. In this paper, we will focus on automating temperature and oxygen monitoring using the Internet of Things. According to our proposed model, data generated by the temperature sensor (MLX90614) and oxygen saturation sensor (MAX30102) will be stored in a relational database. Using this data, future data analyses can be conducted. We are also going to visualize the data by building an interactive dashboard using Power BI. Overall, health monitoring will become much more convenient and speedier. © 2023 IEEE.

‘No Face Mask, No Entry!': Dissecting Multilingual COVID-19 Related Public Health Signs in Penang, Malaysia

Penang is often known as a multilingual and multiethnic city in Malaysia. Its diversity of growing population based on its pre-colonial history and evidence of different ethnic groups living together has resulted in an emergence of a variety of languages today. Henceforth, this chapter embarks on an examination of languages that appear on public health signs in Penang. Conceptualising the study within the framework of language planning and policy, it dissects the languages observed on COVID-19 related signs that were designed by the multiple layers of agency in Penang. The findings are hierarchically organised as follows: (a) state government, (b) district government, (c) large enterprise, and (d) small enterprise. Although a trend of dynamism is reflected in the findings, they still mark social inequality for people's access to public advice related to the COVID-19 outbreak in Penang. The chapter concludes that the linguistic landscape of Penang is a mosaic closely connected to the social and political processes and urges for an increased use of community languages to safeguard vulnerable groups in Penang and across the globe. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Prolonged inflammation in patients hospitalized for coronavirus disease 2019 (COVID-19) resolves 2 years after infection.

Long-term complications from coronavirus disease 2019 (COVID-19) are concerning, as survivors can develop subclinical multiorgan dysfunction. It is unknown if such complications are due to prolonged inflammation, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination may reduce sequela. We conducted a prospective longitudinal study on hospitalized patients over 24 months. Clinical symptoms were collected by self-reporting during follow-up, along with blood samples for quantification of inflammatory markers and immune cell frequencies. All patients were given one dose of mRNA vaccine at 12-16 months. Their immune profiles at 12 and 24 months were compared. Approximately 37% and 39% of our patients reported post-COVID-19 symptoms at 12 and 24 months, respectively. The proportion of symptomatic patients with more than one symptom decreased from 69% at 12 months to 56% at 24 months. Longitudinal cytokine profiling revealed a cluster of individuals with persistently high inflammatory cytokine levels 12 months after infection. Patients with prolonged inflammation showed elevated terminally differentiated memory T cells in their blood; 54% had symptoms at 12 months. The majority of inflammatory markers and dysregulated immune cells in vaccinated patients recovered to a healthy baseline at 24 months, even though symptoms persisted. Post-COVID-19 symptoms can linger for 2 years after the initial infection and are associated with prolonged inflammation. Prolonged inflammation in hospitalized patients resolves after 2 years. We define a set of analytes associated with persistent inflammation and presence of symptoms, which could be useful biomarkers for identifying and monitoring high-risk survivors.

Isolation and Characterization of Porcine Sapelovirus from the PDCoV-Positive Sample and Its Molecular Epidemiology in Henan Province, China

Porcine sapelovirus (PSV) is an emerging swine enteric virus that can cause various disorders including acute diarrhea, respiratory distress, reproductive failure, and polioencephalomyelitis in pigs. In this study, we isolated a PSV strain HNHB-01 from a clinical porcine deltacoronavirus- (PDCoV-) positive intestinal content of a diarrheic piglet. PSV was first identified using the small RNA deep sequencing and assembly, and further identified by the electron microscopic observation and the immunofluorescence assay. Subsequently, this virus was serially passaged in swine testis (ST) cells, and the complete genomics of PSV HNHB-01 passage 5 (P5), P30, P60, and P100 were sequenced and analyzed. 9 nucleotide mutations and 7 amino acid changes occurred in the PSV HNHB-01 P100 strain when compared with the PSV HNHB-01 P5. Pathogenicity investigation showed that orally inoculation of PSV HNHB-01 P30 could cause obvious clinical symptoms and had broad tissue tropism in 5-day-old piglets. Epidemiological investigation revealed that PSV infections and the coinfections of diarrhea coronaviruses were highly prevalent in swine herds. The complete genomes of 8 representative PSV epidemic strains were sequenced and analyzed. Phylogenetic analysis revealed that the PSV epidemic strains were closely related to other PSV reference strains that located in the Chinese clade. Furthermore, recombination analysis revealed that the recombination events were occurred in downstream of the 2C region in our sequenced PSV HNNY-02/CHN/2018 strain. Our results provided theoretical basis for future research studies of the pathogenic mechanism, evolutionary characteristics, and the development of vaccines against PSV.

Mitigating the impact of COVID-19 on quality and value

The impact of the COVID-19 pandemic on hospital care quality operations and reporting is substantial. The authors experienced it as members of the care and leadership teams directly managing large "surges" of COVID-19 patients in one of the United States' early COVID "hotspots, " the Greater New Orleans area. Leadership, structural, operational, clinical, documentation, and regulatory impacts are described. We also share the mitigation efforts our teams were able to mount to counteract the impact of the COVID surges on patient safety, care team safety, documentation accuracy, and the health of our community. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Clinical and occupational characteristics of university hospital workers with COVID-19 signs and symptoms during the pandemic

Objective: to understand the sociodemographic and occupational characteristics and risk exposure among workers of a university hospital who presented COVID-19 symptoms during the first wave of the pandemic. Methods: a cross-sectional study (July to September 2020), on staff from the Hospital Puerta de Hierro Majadahonda (Madrid, Spain) who were working during the first wave of the pandemic. An ad hoc survey was designed, which included the worker profile, COVID-19 symptoms, exposure, clinical course, and healthcare, among others. Descriptive analysis was conducted, and Chi-square and Student's t-test were used for statistical hypothesis testing. Results: the study included 992 subjects;34.3% (n= 340) presented COVID-19 symptoms;283 (84.0%) were female;82.9% (n= 282) of them were healthcare staff;36.8% (n= 125) were nurses;63.5% (n= 216) worked at high risk units;36.2% (n= 123) had a previous medical condition. Of the participants, 83.3% (n= 194) admitted having worked previously at high risk units;84.5% (n= 229) stated that they have felt exposed to the infection during work;49.7% (n= 98) had some incidence of risk;and 73.7% (n= 202) presented asthenia. There was a higher prevalence of healthcare staff with COVID symptoms vs. non-healthcare staff, based on care activities (92.9% vs. 50.0%;p< 0.001), work at COVID areas (74.2% vs. 48.1%;p< 0.001), and activity in high risk Units (73.4% vs. 15.5%;p< 0.001). Conclusions: among the workers with COVID symptoms, there was a higher proportion of healthcare staff, women, nurses, workers at COVID areas, risk units, and previous exposure to patients with confirmed or suspected infection. Differences between healthcare and non-healthcare staff were determined by their place of work during the pandemic and their risk of exposure to COVID-19. © 2023 DAE Editorial, Grupo Paradigma. All rights reserved.

Investigation of COVID-19 symptoms using deep learning based image enhancement scheme for x-ray medical images

Image enhancement is the inevitable technique for investigating various biological features. The biological image data can be obtained from computer tomography (CT), magnetic resonance imaging (MRI), and X-ray imaging. X-ray imaging is useful for getting the information from lungs and respiratory system. COVID-19 is a life-threatening contiguous disease for the past two years in the world. Patient's chest images playing an important role in the diagnosis of early detection of disease intensity. We propose a generative adversarial network (GAN) method that identifies COVID-19 from medical images and improves diagnostic sensitivity. Here we used virtual colouring methods and a platform for training the images by using a deep parental training method. Similarly, it gives optimal classification results with the help of well-defined image enhancement techniques and image extraction approaches. In our method, the accuracy level lies between 87.8% and 89.6% correspondingly for the dataset and synthetic dataset.

INSIGHT OF PANDEMIC COVID-19: DEVELOPMENTS AND CHALLENGES

This review focuses on the characteristics of coronavirus disease-19 (COVID-19) including virus structure, ecoepidemiology and pathophysiology, signs and symptoms in infected people, and data on virus pathogenicity, severity, and survivability in COVID-19 infected patients. The emphasis is on immunological reactions, diagnosis, prophylactic methods, and the zoonotic significance of COVID-19. The authors feel that the review's contents will be valuable to epidemiologists, virologists, public health officials, diagnosticians, laboratory workers, environmentalists, and socioeconomic experts. It has information on the many types of coronavirus variants, the disease situation in Pakistan and the WHO criteria for COVID-19 prevention is given. Moreover, lessons learned from the COVID-19 pandemic are also outlined.

Knowledge, perceptions and preventive practices towards COVID-19 early in the outbreak among Jimma university medical center visitors, Southwest Ethiopia

Background Novel-coronavirus disease-2019 (COVID-19) is currently a pandemic and public health emergency of international concern, as avowed by the World Health Organization (WHO). Ethiopia has become one of the affected countries as of March 15, 2020. Objective This study aimed to assess the knowledge, perceptions, and practices among the Jimma University medical center (JUMC) visitors in Jimma town. Methods A cross-sectional study was conducted on 247 sampled visitors, from 20–24 March 2020. Consecutive sampling was used to recruit the participants. The study tools were adapted from WHO resources. The data were analyzed using the Statistical Package for Social Sciences (SPSS) version 20.0. Descriptive statistics were used to describe the status of knowledge, perception, and practices. Logistic regression was executed to assess the predictors of dominant preventive practices. Results Of the 247 respondents, 205 (83.0%) knew the main clinical symptoms of COVID-19. 72.0% knew that older people who have chronic illnesses are at high risk of developing a severe form of COVID-19. About 95.1% knew that the COVID-19 virus spreads via respiratory droplets of infected people, while 77 (31.2%) of the respondents knew about the possibility of asymptomatic transmission. Only 15 (6.1%) knew that children and young adults had to involve preventive measures. Overall, 41.3% of the visitors had high knowledge. The majority, 170(68.8%), felt self-efficacious to controlling COVID-19. 207(83.3%) believed that COVID-19 is a stigmatized disease. Frequent hand washing (77.3%) and avoidance of shaking hands (53.8%) were the dominant practices. Knowledge status and self-efficacy (positively), older age, and unemployment (negatively) predicted hand washing and avoidance of handshaking. Conclusions The status of knowledge and desirable practices were not sufficient enough to combat this rapidly spreading virus. COVID-19 risk communication and public education efforts should focus on building an appropriate level of knowledge while enhancing the adoption of recommended self-care practices with special emphasis on high-risk audience segments.

Physical activity and mental health in Brazilian university students: An analysis in different sexes during the COVID-19 pandemic

Study aim: To identify symptoms of depression, anxiety, and stress in Brazilian university students of both sexes and the association of physical activity parameters during the COVID-19 pandemic.Material and methods: An online cross-sectional study was conducted from March to April 2021. Data on occupational and social variables and mental health symptoms were investigated using the Beck Anxiety Inventory, Hamilton depression rating scale, and Perceived Stress Scale questionnaires. Physical activity levels were assessed using the International Physical Activity Questionnaire.Results: In total, 277 college students over eighteen years old participated in the study (66% female;46.7% brown race). Higher scores and symptoms of anxiety and depression were observed in women (p < 0.0001). Anxiety symptoms were negatively associated with physical activity levels in women. Sedentary time, including sitting correlated with depression scores in women (r = 0.171;p < 0.05).Conclusions: University students are a risk group for the appearance of symptoms related to mental health. In addition, these disorders occur more frequently in females, and sedentary habits, such as more time sitting, were related to higher scores in depression and anxiety.