Background In 2019, a new virus known as severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) has emerged. Coronavirus disease 2019 (COVID-19) was classified as a pandemic in a short period of time. In order to reduce the spread of COVID-19, many countries have imposed a lockdown with movement restrictions, social distancing and home confinement, which has affected routine healthcare activities and everyday life. The aim of this systematic review was to examine the impact of the COVID-19 lockdown on glycemic control in patients with type 1 diabetes (T1D) and type 2 diabetes (T2D). Methods We systematically identified studies by searching the databases Cochrane Library, MEDLINE via PubMed, Web of Science Core Collection, EMBASE, and CINAHL until April 2021. We included n = 33 observational studies of which n = 25 investigated T1D and n = 8 T2D. Results Overall, we analyzed n = 2881 T1D patients and n = 1823 T2D patients. Glycemic values in patients with T1D improved significantly during lockdown. Overall, n = 18 (72%) T1D studies indicated significant improvements in glycemic outcomes. Meta-analysis revealed a mean difference in HbA1c of − 0.05% (95% CI − 0.31 to 0.21) due to lockdown, and in time in range (TIR) of + 3.75% (95% CI 2.56 to 4.92). Lockdown determined a short-term worsening in glycemic values in patients with T2D. Overall, n = 4 (50%) publications observed deteriorations in glycemic control. Meta-analysis demonstrated a mean difference in HbA1c of + 0.14 (95% CI − 0.13 to 0.40) through the lockdown. Moreover, n = 3 (75%) studies reported a not significant deterioration in body weight. Conclusions Glycemic values in people with T1D significantly improved during COVID-19 lockdown, which may be associated with positive changes in self-care and digital diabetes management. In contrast, lockdown rather determined a short-term worsening in glycemic parameters in patients with T2D. Further research is required, particularly into the causes and effective T2D management during lockdown.

Background According to the World Health Organization, the worldwide prevalence of diabetes mellitus (DM) is increasing dramatically and DM comprises a large part of the global burden of disease. At the same time, the ongoing digitalization that is occurring in society today offers novel possibilities to deal with this challenge, such as the creation of mobile health (mHealth) apps. However, while a great variety of DM-specific mHealth apps exist, the evidence in terms of their clinical effectiveness is still limited. Objective The objective of this review was to evaluate the clinical effectiveness of mHealth apps in DM management by analyzing health-related outcomes in patients diagnosed with type 1 DM (T1DM), type 2 DM (T2DM), and gestational DM. Methods A scoping review was performed. A systematic literature search was conducted in MEDLINE (PubMed), Cochrane Library, EMBASE, CINAHL, and Web of Science Core Collection databases for studies published between January 2008 and October 2020. The studies were categorized by outcomes and type of DM. In addition, we carried out a meta-analysis to determine the impact of DM-specific mHealth apps on the management of glycated hemoglobin (HbA1c). Results In total, 27 studies comprising 2887 patients were included. We analyzed 19 randomized controlled trials, 1 randomized crossover trial, 1 exploratory study, 1 observational study, and 5 pre-post design studies. Overall, there was a clear improvement in HbA1c values in patients diagnosed with T1DM and T2DM. In addition, positive tendencies toward improved self-care and self-efficacy as a result of mHealth app use were found. The meta-analysis revealed an effect size, compared with usual care, of a mean difference of –0.54% (95% CI –0.8 to –0.28) for T2DM and –0.63% (95% CI –0.93 to –0.32) for T1DM. Conclusions DM-specific mHealth apps improved the glycemic control by significantly reducing HbA1c values in patients with T1DM and T2DM patients. In general, mHealth apps effectively enhanced DM management. However, further research in terms of clinical effectiveness needs to be done in greater detail.

Background Diabetes mellitus (DM) is one of the world’s greatest health threats with rising prevalence. Global digitalization leads to new digital approaches in diabetes management, such as telemedical interventions. Telemedicine, which is the use of information and communication technologies, may provide medical services over spatial distances to improve clinical patient outcomes by increasing access to diabetes care and medical information. Objective This study aims to examine whether telemedical interventions effectively improve diabetes control using studies that pooled patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM), and whether the benefits are greater in patients diagnosed with T2DM than in those diagnosed with T1DM. We analyzed the primary outcome glycated hemoglobin A1c (HbA1c) and the secondary outcomes fasting blood glucose (FBG), blood pressure (BP), body weight, BMI, quality of life (QoL), cost, and time saving. Methods Publications were systematically identified by searching Cochrane Library, MEDLINE via PubMed, Web of Science Core Collection, Embase, and CINAHL databases for studies published between January 2008 and April 2020, considering systematic reviews (SRs), meta-analyses (MAs), randomized controlled trials (RCTs), and clinical trials (CTs). Study quality was assessed using the A Measurement Tool to Assess Systematic Reviews, Effective Public Health Practice Project, and National Institute for Health and Care Excellence qualitative checklist. We organized the trials by communication technologies in real-time video or audio interventions, asynchronous interventions, and combined interventions (synchronous and asynchronous communication). Results From 1116 unique citations, we identified 31 eligible studies (n=15 high, n=14 moderate, n=1 weak, and n=1 critically low quality). We selected 21 SRs and MAs, 8 RCTs, 1 non-RCT, and 1 qualitative study. Of the 10 trials, 3 were categorized as real-time video, 1 as real-time video and audio, 4 as asynchronous, and 2 as combined intervention. Significant decline in HbA1c levels based on pooled T1DM and T2DM patients data ranged from −0.22% weighted mean difference (WMD; 95% CI −0.28 to −0.15; P<.001) to −0.64% mean difference (95% CI −1.01 to −0.26; P<.001). The intervention effect on lowering HbA1c values might be significantly smaller for patients with T1DM than for patients with T2DM. Evidence on the impact on BP, body weight, FBG, cost effectiveness, and time saving was smaller compared with HbA1c but indicated potential in some publications. Conclusions Telemedical interventions might be clinically effective in improving diabetes control overall, and they might significantly improve HbA1c concentrations. Patients with T2DM could benefit more than patients with T1DM regarding lowering HbA1c levels. Further studies with longer duration and larger cohorts are necessary.

Background There is lots of evidence that maternal peri-gestational metabolic, genomic and environmental conditions are closely linked to metabolic and cardiovascular outcomes in their offspring later in life. Moreover, there is also lotsof evidence that underlining mechanisms, such as molecular as well as epigenetic changes may alter the intrauterine environment leading to cardio-metabolic diseases in their offspring postnatal. But, there is also increasing evidence that cardio-metabolic diseases may be closely linked to their paternal metabolic risk factors, such as obesity, Type 2 Diabetes and other risk factors. Objective To analyse the evidence as well as specific risk factors of paternal trans-generational programming of cardio-metabolic diseases in their offspring. Methods Within a systematic scoping review, we performed a literature search in MEDLINE (PubMed) and EMBASE databases in August 2020 considering original research articles (2000–2020) that examined the impact of paternal programming on metabolic and cardiovascular offspring health. Epidemiological, clinical and experimental studies as well as human and animal model studies were included. Results From n = 3.199 citations, n = 66 eligible studies were included. We selected n = 45 epidemiological as well as clinical studies and n = 21 experimental studies. In brief, pre-conceptional paternal risk factors, such as obesity, own birth weight, high-fat and low-protein diet, undernutrition, diabetes mellitus, hyperglycaemia, advanced age, smoking as well as environmental chemical exposure affect clearly metabolic and cardiovascular health of their offspring later in life. Conclusions There is emerging evidence that paternal risk factors, such as paternal obesity, diabetes mellitus, nutritional habits, advanced age and exposure to environmental chemicals or cigarette smoke, are clearly associated with adverse effects in metabolic and cardiovascular health in their offspring. Compared to maternal programming, pre-conceptional paternal factors might also have also a substantial effect in the sense of trans-generational programming of their offspring and need further research.

Background Gestational diabetes mellitus (GDM) emerges worldwide and is closely associated with short- and long-term health issues in women and their offspring, such as pregnancy and birth complications respectively comorbidities, Type 2 Diabetes (T2D), metabolic syndrome as well as cardiovascular diseases. Against this background, mobile health applications (mHealth-Apps) do open up new possibilities to improve the management of GDM. Therefore, we analyzed the clinical effectiveness of specific mHealth-Apps on clinical health-related short and long-term outcomes in mother and child. Methods A systematic literature search in Medline (PubMed), Cochrane Library, Embase, CINAHL and Web of Science Core Collection databases as well as Google Scholar was performed. We selected studies published 2008 to 2020 analyzing women diagnosed with GDM using specific mHealth-Apps. Controlled clinical trials (CCT) and randomized controlled trials (RCT) were included. Study quality was assessed using the Effective Public Health Practice Project (EPHPP) tool. Results In total, n = 6 publications (n = 5 RCTs, n = 1 CCT; and n = 4 moderate, n = 2 weak quality), analyzing n = 408 GDM patients in the intervention and n = 405 in the control groups, were included. Compared to control groups, fasting blood glucose, 2-h postprandial blood glucose, off target blood glucose measurements, delivery mode (more vaginal deliveries and fewer (emergency) caesarean sections) and patient compliance showed improving trends. Conclusion mHealth-Apps might improve health-related outcomes, particularly glycemic control, in the management of GDM. Further studies need to be done in more detail.