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.
Insulin resistance is the underlying mechanism for the metabolic syndrome and associated dyslipidaemia that theoretically implies a practical tool for identifying individuals at risk for ...cardiovascular disease and type-2-diabetes. Another screening tool is the hypertriglyceremic-waist phenotype (HTW). There is important impact of the ethnic background but a lack of studied European populations for the association of the triglyceride/high-density lipoprotein cholesterol (HDL-C) ratio and insulin resistance. This observational, retrospective study evaluated lipid ratios and the HTW for predicting the metabolic syndrome/insulin resistance in 1932 non-diabetic individuals from Germany in the fasting state and during a glucose tolerance test. The relations of triglyceride/HDL-C, total-cholesterol/HDL-C, and low-density lipoprotein cholesterol/HDL-C with 5 surrogate estimates of insulin resistance/sensitivity and metabolic syndrome were analysed by linear regression analysis and receiver operating characteristics (ROC) in participants with normal (n=1 333) or impaired fasting glucose (n=599), also for the impact of gender. Within the lipid ratios, triglyceride/HDL-C had the strongest associations with insulin resistance/sensitivity markers. In the prediction of metabolic syndrome, diagnostic accuracy was good for triglyceride/HDL-C (area under the ROC curve 0.817) with optimal cut-off points (in mg/dl units) of 2.8 for men (80% sensitivity, 71% specificity) and 1.9 for women (80% sensitivity, 75% specificity) and fair for HTW and HOMA-IR (area under the curve 0.773 and 0.761). These data suggest the triglyceride/HDL-C ratio as a physiologically relevant and practical index for predicting the concomitant presence of metabolic syndrome, insulin resistance and dyslipidaemia for therapeutic and preventive care in apparently healthy European populations.
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.
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.
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.
As physical inactivity is one of the four leading risk factors for mortality, it should be intensively treated. Therefore, this one-year follow-up study aimed to evaluate the long-term effects of a ...preventive app to increase physical activity in German adults under real-life circumstances. Data collection took place from July 2019 to July 2021 and included six online questionnaires. Physical activity was studied as the primary outcome based on MET-minutes per week (metabolic equivalent). Secondary outcomes included health-related quality of life based on a mental (MCS) and physical health component summary score (PCS). At the time of publication, 46/65 participants completed the study (median 52 years, 81.5% women). A significant increase of physical activity was observed in people with a low/moderate baseline activity during the first four months of follow-up (median increase by 490 MET-minutes per week,
< 0.001, r = 0.649). Both MCS (median increase by 2.8,
= 0.006, r = 0.344) and PCS (median increase by 2.6,
< 0.001, r = 0.521) significantly increased during the first two months and the BMI significantly decreased during the first six months after the intervention (median decrease by 0.96 kg/m
,
< 0.001, r = 0.465). Thus, this study provides evidence for the medium-term impact of the app, since the effects decreased over time. However, due to the chosen study design and a sizeable loss to follow-up, the validity of these findings is limited.
The aim of this study was to provide preliminary evidence on the impact of the digital health application Vitadio on improving glycemic control in patients with type 2 diabetes mellitus. This was a ...3-month, prospective, multicenter, open-label trial with an intraindividual control group. Participants received a digital lifestyle intervention. HbA1c levels were observed at 3 time points: retrospectively, at 3 months before app use; at baseline, at the start of usage; and 3 months after the start of use. In addition, changes in other metabolic parameters (fasting glucose, body weight, and waist circumference), patient reported outcomes (quality of life, self-efficacy, and depression), and data generated within the app (frequency of use, steps, and photos of meals) were evaluated. Repeated measures analysis of variance with the Bonferroni correction was used to assess the overall difference in HbA1c values between the intervention and the intraindividual control group, with p < 0.05 considered significant. Participants (n = 42) were 57 ± 7.4 years old, 55% male, and with a mean baseline HbA1c of 7.9 ± 1.0%. An average HbA1c reduction of −0.9 ± 1.1% (p < 0.001) was achieved. The digital health application was effective in significantly reducing body weight (−4.3 ± 4.5 kg), body mass index (−1.4 ± 1.5 kg/m2), waist circumference (−5.7 ± 15 cm), and fasting glucose (−0.6 ± 1.3 mmol/L). The digital therapy achieved a clinically meaningful and significant HbA1c reduction as well as a positive effect on metabolic parameters. These results provide preliminary evidence that Vitadio may be effective in supporting patient diabetes management by motivating patients to adopt healthier lifestyles and improving their self-management.
(1) Background: This study aimed at providing preliminary evidence for mebix, an app-based treatment program for patients with diabetes mellitus type II. The main target was to show a positive ...healthcare impact as defined by improved blood glucose control, i.e., reduced HbA1c values. (2) Methods: For this, a 3-month, prospective, open-label trial with an intraindividual control group was conducted. Participants received the mebix intervention for 3 months. HbA1c values were observed every 3 months: retrospectively, at baseline, and 3 months after the start of using the app. Additionally, weight and patients’ reported outcomes (well-being, diabetes-related distress, and self-management) were assessed. Data generated within the app were summarized and analyzed (steps, physical activity, fulfilled tasks, and food logs). (3) Results: After the usage of mebix for 3 months, participants significantly reduced their HbA1c levels (−1.0 ± 0.8%). Moreover, improvements in weight, well-being, and self-management as well as a reduction in diabetes-related distress were observed. App-generated data mainly supported the other main finding, that higher baseline HbA1c values lead to higher reductions. Overall, the study provided preliminary evidence that mebix can help patients improve metabolic and psychological health outcomes.
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