Can trajectories of glycemic control be predicted by depression, anxiety, or diabetes-related distress in a prospective cohort of adults with newly diagnosed type 1 diabetes? Results of a five-year follow-up from the German multicenter diabetes cohort study (GMDC-Study)

2018 ◽  
Vol 141 ◽  
pp. 106-117 ◽  
Author(s):  
Hanna Kampling ◽  
Oskar Mittag ◽  
Stephan Herpertz ◽  
Harald Baumeister ◽  
Bernd Kulzer ◽  
...  
2017 ◽  
Vol 5 (11) ◽  
pp. e170 ◽  
Author(s):  
Concetta Irace ◽  
Matthias Axel Schweitzer ◽  
Cesare Tripolino ◽  
Faustina Barbara Scavelli ◽  
Agostino Gnasso

2017 ◽  
Vol 18 (8) ◽  
pp. 808-816 ◽  
Author(s):  
Anna Stahl-Pehe ◽  
Sandra Landwehr ◽  
Karin S. Lange ◽  
Christina Bächle ◽  
Katty Castillo ◽  
...  

2020 ◽  
Author(s):  
Martina Parise ◽  
Linda Tartaglione ◽  
Antonio Cutruzzolà ◽  
Maria Ida Maiorino ◽  
Katherine Esposito ◽  
...  

BACKGROUND Telemedicine use in chronic disease management has markedly increased during health emergencies due to COVID-19. Diabetes and technologies supporting diabetes care, including glucose monitoring devices, software analyzing glucose data, and insulin delivering systems, would facilitate remote and structured disease management. Indeed, most of the currently available technologies to store and transfer web-based data to be shared with health care providers. OBJECTIVE During the COVID-19 pandemic, we provided our patients the opportunity to manage their diabetes remotely by implementing technology. Therefore, this study aimed to evaluate the effectiveness of 2 virtual visits on glycemic control parameters among patients with type 1 diabetes (T1D) during the lockdown period. METHODS This prospective observational study included T1D patients who completed 2 virtual visits during the lockdown period. The glucose outcomes that reflected the benefits of the virtual consultation were time in range (TIR), time above range, time below range, mean daily glucose, glucose management indicator (GMI), and glycemic variability. This metric was generated using specific computer programs that automatically upload data from the devices used to monitor blood or interstitial glucose levels. If needed, we changed the ongoing treatment at the first virtual visit. RESULTS Among 209 eligible patients with T1D, 166 completed 2 virtual visits, 35 failed to download glucose data, and 8 declined the visit. Among the patients not included in the study, we observed a significantly lower proportion of continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII) users (n=7/43, 16% vs n=155/166, 93.4% and n=9/43, 21% vs n=128/166, 77.1%, respectively; <i>P</i>&lt;.001) compared to patients who completed the study. TIR significantly increased from the first (62%, SD 18%) to the second (65%, SD 16%) virtual visit (<i>P</i>=.02); this increase was more marked among patients using the traditional meter (n=11; baseline TIR=55%, SD 17% and follow-up TIR=66%, SD 13%; <i>P</i>=.01) than among those using CGM, and in those with a baseline GMI of ≥7.5% (n=46; baseline TIR=45%, SD 15% and follow-up TIR=53%, SD 18%; <i>P</i>&lt;.001) than in those with a GMI of &lt;7.5% (n=120; baseline TIR=68%, SD 15% and follow-up TIR=69%, SD 15%; <i>P</i>=.98). The only variable independently associated with TIR was the change of ongoing therapy. The unstandardized beta coefficient (B) and 95% CI were 5 (95% CI 0.7-8.0) (<i>P</i>=.02). The type of glucose monitoring device and insulin delivery systems did not influence glucometric parameters. CONCLUSIONS These findings indicate that the structured virtual visits help maintain and improve glycemic control in situations where in-person visits are not feasible.


BMJ ◽  
2018 ◽  
pp. k3547 ◽  
Author(s):  
Julie C Antvorskov ◽  
Thorhallur I Halldorsson ◽  
Knud Josefsen ◽  
Jannet Svensson ◽  
Charlotta Granström ◽  
...  

Abstract Objective To examine the association between prenatal gluten exposure and offspring risk of type 1 diabetes in humans. Design National prospective cohort study. Setting National health information registries in Denmark. Participants Pregnant Danish women enrolled into the Danish National Birth Cohort, between January 1996 and October 2002, Main outcome measures Maternal gluten intake, based on maternal consumption of gluten containing foods, was reported in a 360 item food frequency questionnaire at week 25 of pregnancy. Information on type 1 diabetes occurrence in the participants’ children, from 1 January 1996 to 31 May 2016, were obtained through registry linkage to the Danish Registry of Childhood and Adolescent Diabetes. Results The study comprised 101 042 pregnancies in 91 745 women, of whom 70 188 filled out the food frequency questionnaire. After correcting for multiple pregnancies, pregnancies ending in abortions, stillbirths, lack of information regarding the pregnancy, and pregnancies with implausibly high or low energy intake, 67 565 pregnancies (63 529 women) were included. The average gluten intake was 13.0 g/day, ranging from less than 7 g/day to more than 20 g/day. The incidence of type 1 diabetes among children in the cohort was 0.37% (n=247) with a mean follow-up period of 15.6 years (standard deviation 1.4). Risk of type 1 diabetes in offspring increased proportionally with maternal gluten intake during pregnancy (adjusted hazard ratio 1.31 (95% confidence interval 1.001 to 1.72) per 10 g/day increase of gluten). Women with the highest gluten intake versus those with the lowest gluten intake (≥20 v <7 g/day) had double the risk of type 1 diabetes development in their offspring (adjusted hazard ratio 2.00 (95% confidence interval 1.02 to 4.00)). Conclusions High gluten intake by mothers during pregnancy could increase the risk of their children developing type 1 diabetes. However, confirmation of these findings are warranted, preferably in an intervention setting.


2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Caroline A. Brorsson ◽  
Lotte B. Nielsen ◽  
Marie Louise Andersen ◽  
Simranjeet Kaur ◽  
Regine Bergholdt ◽  
...  

Genome-wide association studies (GWAS) have identified over 40 type 1 diabetes risk loci. The clinical impact of these loci onβ-cell function during disease progression is unknown. We aimed at testing whether a genetic risk score could predict glycemic control and residualβ-cell function in type 1 diabetes (T1D). As gene expression may represent an intermediate phenotype between genetic variation and disease, we hypothesized that genes within T1D loci which are expressed in islets and transcriptionally regulated by proinflammatory cytokines would be the best predictors of disease progression. Two-thirds of 46 GWAS candidate genes examined were expressed in human islets, and 11 of these significantly changed expression levels following exposure to proinflammatory cytokines (IL-1β+ IFNγ+ TNFα) for 48 h. Using the GWAS single nucleotide polymorphisms (SNPs) from each locus, we constructed a genetic risk score based on the cumulative number of risk alleles carried in children with newly diagnosed T1D. With each additional risk allele carried, HbA1c levels increased significantly within first year after diagnosis. Network and gene ontology (GO) analyses revealed that several of the 11 candidate genes have overlapping biological functions and interact in a common network. Our results may help predict disease progression in newly diagnosed children with T1D which can be exploited for optimizing treatment.


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