Up to 50% of the people who have died from COVID-19 had metabolic and vascular disorders. Notably, there are many direct links between COVID-19 and the metabolic and endocrine systems. Thus, not only ...are patients with metabolic dysfunction (eg, obesity, hypertension, non-alcoholic fatty liver disease, and diabetes) at an increased risk of developing severe COVID-19 but also infection with SARS-CoV-2 might lead to new-onset diabetes or aggravation of pre-existing metabolic disorders. In this Review, we provide an update on the mechanisms of how metabolic and endocrine disorders might predispose patients to develop severe COVID-19. Additionally, we update the practical recommendations and management of patients with COVID-19 and post-pandemic. Furthermore, we summarise new treatment options for patients with both COVID-19 and diabetes, and highlight current challenges in clinical management.
Health systems and governments are increasingly required to implement measures that target at-risk populations to prevent noncommunicable diseases. In this review we lay out what governments should ...be doing to prevent diabetes throughout the life course. The following four target groups were used to structure the specific recommendations: (1) pregnant women and young families, (2) children and adolescents, (3) working age population, and (4) the elderly. The evidence to date supports the effectiveness of some known government policy measures, such as sugar taxes and regulatory measures in the (pre-)school setting for children and adolescents. Many of these appear to be more effective if they are part of a bundle of strategies and if they are supplemented by communication strategies. Although there is a current focus on strategies that target the individual, governments can make use of evidence-based population-level prevention strategies. More research and continuous evaluation of the overall and subgroup-specific effectiveness of policy strategies using high-quality longitudinal studies are needed.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Insbesondere interessant ist, dass sich die Insulinresistenz mit der App deutlich verbesserte, mit einer signifikanten Reduktion des Homeostasis-Model-Assessment(HOMA)-Index' um 2,5. Quelle: ...Moravcová K, Karbanová M, Bretschneider MP et al. Comparing Digital Therapeutic Intervention with an Intensive Obesity Management Program: Randomized Controlled Trial.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
17.
Non-use of telemedicine: A scoping review Reinhardt, Gesine; Schwarz, Peter EH; Harst, Lorenz
Health informatics journal,
10/2021, Volume:
27, Issue:
4
Journal Article
Peer reviewed
Open access
Many telemedicine interventions fail to be implemented in medical care with non-use and discontinued use by patients being among the major reasons. The aim of this scoping review was to provide an ...overview of barriers associated with non-use and discontinued use of telemedicine. An electronic search was conducted in Pubmed in October 2019 and updated in November 2020, followed by a hand search in the beginning of 2021. All potential articles were screened by two independent reviewers based on predefined inclusion and exclusion criteria. A qualitative content analysis according to Mayring was carried out. The topics ‘intervention’, ‘context of use’ and ‘user’ were chosen as overarching themes. Out of 1377 potentially relevant articles, 73 were included. User-related barriers were mentioned in most of the analysed studies, followed by barriers related to the intervention. The analysis provides the basis for overcoming non-use issues in telemedicine.
Lifestyle interventions in type 2 diabetes (DM2) prevention implementation studies can be effective and lasting. Long-term weight loss maintenance enhances the intervention effect through a ...significant decrease in diabetes incidence over time. Our objective was to identify factors predicting long-term successful weight reduction maintenance achieved during a DM2 prevention program in patients with high DM2 risk in primary health care. Study participants (n = 263), middle-aged, slightly obese with baseline increased DM2 risk (Finnish Diabetes Risk Score (FINDRISC)>14), but no diabetes were invited to receive 11 lifestyle counselling sessions, guided physical activity sessions and motivational support during 10-months. The study participants had three clinical examinations during the study (baseline, one and three years). Stepwise regression analysis was used to determine demographic, clinical, and lifestyle predictors of weight reduction maintenance two years after the discontinuation of the intervention. Out of 105 patients who completed all three examinations (baseline age 56.6 (standard deviation (SD) = 10.7), body mass index 31.1 kg/m2 (SD = 4.9), FINDRISC 18.6 (SD = 3.1)), 73 patients (70%) showed weight loss during the intervention (mean weight loss 4.2 kg, SD = 5.1). The total weight loss achieved in the maintainers (27 of 73 study participants) two years after the intervention had finished was 6.54 kg (4.47 kg+2.0 kg). The non-maintainers, on the other hand, returned to their initial weight at the start of the intervention (+0.21 kg). In multivariable analysis baseline history of increased glucose (odds ratio (OR) = 3.7; 95% confidence interval (CI) 1.0-13.6) and reduction of total fat in diet during follow-up (OR = 4.3; 95% CI 1.5-12.2) were independent predictors of successful weight loss. Further studies exploring predictors of weight loss maintenance in diabetes prevention are needed to help health care providers to redesign interventions and improve long-term outcomes of real life interventions.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
There are a number of arguments in support of early measures for the prevention of type 2 diabetes (T2D), as well as for concepts and strategies at later intervention stages. Diabetes prevention is ...achievable when implemented in a sustainable manner. Sustainability within a T2D prevention program is more important than the actual point in time or disease process at which prevention activities may start. The quality of intervention, as well as its intensity, should vary with the degree of the identified T2D risk. Nevertheless, preventive interventions should start as early as possible in order to allow a wide variety of relatively low- and moderate-intensity programs. The later the disease risk is identified, the more intensive the intervention should be. Public health interventions for diabetes prevention represent an optimal model for early intervention. Late interventions will be targeted at people who already have significant pathophysiological derangements that can be considered steps leading to the development of T2D. These derangements may be difficult to reverse, but the worsening of dysglycemia may be halted, and thus the clinical onset of T2D can be delayed.
Electric utilities are challenging net metering, which compensates owners of residential solar photovoltaic systems by crediting solar generation at the retail rate instead of reflecting the value of ...solar to the utility. In 2012, Austin Energy was the first US utility to replace net metering with Buy-All, Sell-All, where prosumers purchase all electricity at the retail rate and sell all electricity at the utility’s value of solar rate. Using Austin Energy customer data for hot weather months, a load curve comparison of comparably sized houses shows that prosumers have higher consumption than non-solar customers during system peak hours. Regression analysis finds that prosumers use more energy for air conditioning, with a rebound effect of 20%. A simulation shows that under net metering and net purchasing almost 7% of prosumer bills would be paid by non-solar customers while total subsidy would be 18% due to the inclusion of increasing block rates.
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CEKLJ, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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