scholarly journals Glycemic variability in patients with Wolfram syndrome is lower than in type 1 diabetes

2015 ◽  
Vol 52 (6) ◽  
pp. 1057-1062 ◽  
Author(s):  
A. Zmyslowska ◽  
W. Fendler ◽  
A. Szadkowska ◽  
M. Borowiec ◽  
M. Mysliwiec ◽  
...  
Author(s):  
Martín Borja Sanz ◽  
Gimeno Sergio Roman ◽  
Peteiro Miranda Carlos Miguel ◽  
Ortez Toro Jose Jorge ◽  
Ana Agudo ◽  
...  

2018 ◽  
Vol 14 (4) ◽  
pp. 395-403 ◽  
Author(s):  
Karem Mileo Felício ◽  
Ana Carolina Contente Braga de Souza ◽  
Joao Felicio Abrahao Neto ◽  
Franciane Trindade Cunha de Melo ◽  
Carolina Tavares Carvalho ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ziyang Shen ◽  
Hemin Jiang ◽  
Rong Huang ◽  
Yunting Zhou ◽  
Qian Li ◽  
...  

AbstractPrevious studies exploring the influence of glycemic variability (GV) on the pathogenesis of distal symmetrical polyneuropathy (DSPN) in type 1 diabetes (T1DM) produced conflicting results. The aim of this study was to assess the relationship between GV and DSPN in T1DM. Adults with T1DM were included in this cross-sectional study and asked to undergo 3-day CGM. GV quantified by coefficient of variation (CV) and mean amplitude of glucose excursions (MAGE) were obtained from CGM. Clinical characteristics and biochemical assessments were collected for analysis. The study comprised 152 T1DM patients (53.9% males) with mean age of 44.2 year. Higher levels of age and duration of diabetes and lower levels of total cholesterol, LDL, fasting C-peptide and postprandial C-peptide were observed in DSPN subjects. DSPN groups displayed a higher blood glucose between 00:00 and 12:59 according to the CGM profile. Higher MAGE and CV were associated with increased risk of DSPN in the fully adjusted model. Meanwhile, a significant association between measurements of hypoglycemia, especially nocturnal hypoglycemia, and DSPN was found after multiple tests. CGM parameters describing the glycemic variability and hypoglycemia were potential risk factors for DSPN in adults with T1DM.


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.


Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 96-OR
Author(s):  
RAFAL SIBIAK ◽  
BEATA MRZEWKA-ROGACZ ◽  
URSZULA MANTAJ ◽  
PAWEL GUTAJ ◽  
EWA WENDER-OZEGOWSKA

2019 ◽  
Vol 21 (8) ◽  
pp. 430-439 ◽  
Author(s):  
Ana María Gómez ◽  
Diana Cristina Henao ◽  
Angélica Imitola Madero ◽  
Lucía B. Taboada ◽  
Viviana Cruz ◽  
...  

2020 ◽  
pp. 193229682092225
Author(s):  
Morten Hasselstrøm Jensen ◽  
Simon Lebech Cichosz ◽  
Irl B. Hirsch ◽  
Peter Vestergaard ◽  
Ole Hejlesen ◽  
...  

Background: The prevalence of smoking and diabetes is increasing in many developing countries. The aim of this study was to investigate the association of smoking with inadequate glycemic control and glycemic variability with continuous glucose monitoring (CGM) data in people with type 1 diabetes. Methods: Forty-nine smokers and 320 nonsmokers were obtained from the Novo Nordisk Onset 5 trial. After 16 weeks of treatment with continuous subcutaneous insulin infusion, risk of not achieving glycemic target and glycemic variability from six CGM measures was investigated. Analyzes were carried out with logistic regression models (glycemic target) and general linear models (glycemic variability). Finally, CGM median profiles were examined for the identification of daily glucose excursions. Results: A 4.7-fold (95% confidence interval: 1.5-15.4) increased risk of not achieving glycemic target was observed for smokers compared with nonsmokers. Increased time in hyperglycemia, decreased time in range, increased time in hypoglycemia (very low interstitial glucose), and increased fluctuation were observed for smokers compared with nonsmokers from CGM measures. CGM measures of coefficient of variation and time in hypoglycemia were not statistically significantly different. Examination of CGM median profiles revealed that risk of morning hypoglycemia is increased for smokers. Conclusions: In conclusion, smoking is associated with inadequate glycemic control and increased glycemic variability for people with type 1 diabetes with especially risk of morning hypoglycemia. It is important for clinicians to know that if the patient has type 1 diabetes and is smoking, a preemptive action to treat high glycated hemoglobin levels should not necessarily be treatment intensification due to the risk of hypoglycemia.


Sign in / Sign up

Export Citation Format

Share Document