Background And Aims: Type 2 diabetes mellitus is one of the major public health concerns. The current lifestyle and advances in technology resulted in the development of a virtual mode of professional healthcare, which is an effective alternative method of management of patients. This study aimed to assess the feasibility of implementation of a virtual comprehensive care programme during the COVID-19 pandemic, patients' acceptance and the changes in self-care behaviours, metabolic parameters and emotional factors.
Methods: The programme employed in this study included nine health interventions in 1 day. Due to the COVID-19 pandemic, the mode of interventions, including questionnaires, patient evaluations and a satisfaction survey, was modified to the virtual form in 2020. This study assessed the changes in self-care behaviours, metabolic parameters and emotional factors and compared the data pertaining to patients who received virtual healthcare in 2020 with those who received face-to-face modality of medical care in 2019.
Results: During June to November 2020, 130 patients received healthcare by means of the virtual modality. The change in modality of healthcare was feasible and 75% of the patients displayed good acceptance of the same. The evaluation of self-care behaviours included self-monitoring blood glucose (SMBG) levels, foot care and regular exercise. The duration of exercise decreased from 120 to 0 min/week ( < 0.001). However, there was no change in metabolic parameters. Regarding the mental health parameters, we observed an increase in the proportion of patients with anxiety (21.5% 11.1%), depressive symptoms (10.8% 4.3%), diabetes distress (18.5% 11.1%) and prescription of psychotropic drugs (32.8% 18.2%) ( < 0.05) in virtual face-to-face, respectively.
Conclusion: The virtual comprehensive care programme for the management of patients with diabetes is a feasible approach that allows healthcare professionals to provide an adequate care during the COVID-19 pandemic.
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http://dx.doi.org/10.1177/20420188211059882 | DOI Listing |
Sci Rep
December 2024
College of Mechanical and Electronic Engineering, Dalian Minzu University, Dalian, 116650, Liaoning, China.
The novel coronavirus (COVID-19) has affected more than two million people of the world, and far social distancing and segregated lifestyle have to be adopted as a common solution in recent years. To solve the problem of sanitation control and epidemic prevention in public places, in this paper, an intelligent disinfection control system based on the STM32 single-chip microprocessor was designed to realize intelligent closed-loop disinfection in local public places such as public toilets. The proposed system comprises seven modules: image acquisition, spraying control, disinfectant liquid level control, access control, voice broadcast, system display, and data storage.
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December 2024
Department of Mathematics, GC University, Lahore, Pakistan.
In this article, a nonlinear fractional bi-susceptible [Formula: see text] model is developed to mathematically study the deadly Coronavirus disease (Covid-19), employing the Atangana-Baleanu derivative in Caputo sense (ABC). A more profound comprehension of the system's intricate dynamics using fractional-order derivative is explored as the primary focus of constructing this model. The fundamental properties such as positivity and boundedness, of an epidemic model have been proven, ensuring that the model accurately reflects the realistic behavior of disease spread within a population.
View Article and Find Full Text PDFNat Commun
December 2024
Division of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Antibody-mediated protection against pathogens is crucial to a healthy life. However, the recent SARS-CoV-2 pandemic has shown that pre-existing comorbid conditions including kidney disease account for compromised humoral immunity to infections. Individuals with kidney disease are not only susceptible to infections but also exhibit poor vaccine-induced antibody response.
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December 2024
State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China.
Lipid nanoparticles (LNPs) have proven effective in mRNA delivery, as evidenced by COVID-19 vaccines. Its key ingredient, ionizable lipids, is traditionally optimized by inefficient and costly experimental screening. This study leverages artificial intelligence (AI) and virtual screening to facilitate the rational design of ionizable lipids by predicting two key properties of LNPs, apparent pKa and mRNA delivery efficiency.
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December 2024
Laboratory of Aging Research and Cancer Drug Target, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China.
The immune escape capacities of XBB variants necessitate the authorization of vaccines with these antigens. In this study, we produce three recombinant trimeric proteins from the RBD sequences of Delta, BA.5, and XBB.
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