1044-P: The Impact of Basal Insulin Type, Prandial Dosing Plan, and Baseline Postprandial Glucose (PPG) on Glycemic Control after Treatment with Ultra-Rapid Lispro (URLi) or Humalog in Type 1 Diabetes: Planned Subgroup Analyses from PRONTO-T1D

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1044-P
Author(s):  
JULIANA M. BUE-VALLESKEY ◽  
JANG IK CHO ◽  
THOMAS HARDY
2021 ◽  
pp. 193229682110123
Author(s):  
Chiara Roversi ◽  
Martina Vettoretti ◽  
Simone Del Favero ◽  
Andrea Facchinetti ◽  
Pratik Choudhary ◽  
...  

Background: In the management of type 1 diabetes (T1D), systematic and random errors in carb-counting can have an adverse effect on glycemic control. In this study, we performed an in silico trial aiming at quantifying the impact of different levels of carb-counting error on glycemic control. Methods: The T1D patient decision simulator was used to simulate 7-day glycemic profiles of 100 adults using open-loop therapy. The simulation was repeated for different values of systematic and random carb-counting errors, generated with Gaussian distribution varying the error mean from -10% to +10% and standard deviation (SD) from 0% to 50%. The effect of the error was evaluated by computing the difference of time inside (∆TIR), above (∆TAR) and below (∆TBR) the target glycemic range (70-180mg/dl) compared to the reference case, that is, absence of error. Finally, 3 linear regression models were developed to mathematically describe how error mean and SD variations result in ∆TIR, ∆TAR, and ∆TBR changes. Results: Random errors globally deteriorate the glycemic control; systematic underestimations lead to, on average, up to 5.2% more TAR than the reference case, while systematic overestimation results in up to 0.8% more TBR. The different time in range metrics were linearly related with error mean and SD ( R2>0.95), with slopes of [Formula: see text], [Formula: see text] for ∆TIR, [Formula: see text], [Formula: see text] for ∆TAR, and [Formula: see text], [Formula: see text] for ∆TBR. Conclusions: The quantification of carb-counting error impact performed in this work may be useful understanding causes of glycemic variability and the impact of possible therapy adjustments or behavior changes in different glucose metrics.


Author(s):  
Maria Cusinato ◽  
Mariangela Martino ◽  
Alex Sartori ◽  
Claudia Gabrielli ◽  
Laura Tassara ◽  
...  

Abstract Objectives Our study aims to assess the impact of lockdown during the coronavirus disease 2019 pandemic on glycemic control and psychological well-being in youths with type 1 diabetes. Methods We compared glycemic metrics during lockdown with the same period of 2019. The psychological impact was evaluated with the Test of Anxiety and Depression. Results We analyzed metrics of 117 adolescents (87% on Multiple Daily Injections and 100% were flash glucose monitoring/continuous glucose monitoring users). During the lockdown, we observed an increase of the percentage of time in range (TIR) (p<0.001), with a significant reduction of time in moderate (p=0.002), and severe hypoglycemia (p=0.001), as well as the percentage of time in hyperglycemia (p<0.001). Glucose variability did not differ (p=0.863). The glucose management indicator was lower (p=0.001). 7% of youths reached the threshold-score (≥115) for anxiety and 16% for depression. A higher score was associated with lower TIR [p=0.028, p=0.012]. Conclusions Glycemic control improved during the first lockdown period with respect to the previous year. Symptoms of depression and anxiety were associated with worse glycemic control; future researches are necessary to establish if this improvement is transient and if psychological difficulties will increase during the prolonged pandemic situation.


2016 ◽  
Vol 11 (4) ◽  
pp. 753-758 ◽  
Author(s):  
Asma Deeb ◽  
Ahlam Al Hajeri ◽  
Iman Alhmoudi ◽  
Nico Nagelkerke

Background: Carbohydrate (CHO) counting is a key nutritional intervention utilized in the management of diabetes to optimize postprandial glycemia. The aim of the study was to examine the impact of accuracy of CHO counting on the postprandial glucose in children and adolescents with type 1 diabetes on insulin pump therapy. Methods: Children/adolescents with type 1 diabetes who were on insulin pump therapy for a minimum of 6 months are enrolled in the study. Patients were instructed to record details of meals consumed, estimated CHO count per meal, and 2-hour postprandial glucose readings over 3-5 days. Meals’ CHO contents were recounted by an experienced clinical dietician, and those within 20% of the dietician’s counting were considered accurate. Results: A total of 30 patients (21 females) were enrolled. Age range (median) was 8-18 (SD 13) years. Data of 247 meals were analyzed. A total of 165 (67%) meals’ CHO contents were accurately counted. Of those, 90 meals (55%) had in-target postprandial glucose ( P < .000). There was an inverse relationship between inaccurate CHO estimates and postprandial glucose. Of the 63 underestimated meals, 55 had above-target glucose, while 12 of the 19 overestimated meals were followed by low glucose. There was no association between accuracy and meal size (Spearman’s rho = .019). Conclusion: Accuracy of CHO counting is an important determining factor of postprandial glycemia. However, other factors should be considered when advising on prandial insulin calculation. Underestimation and overestimation of CHO result in postprandial hyperglycemia and hypoglycemia, respectively. Accuracy does not correlate with meal size.


2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A338-A338
Author(s):  
Jamie Calma ◽  
Sabrina Sangha ◽  
Marina Basina

Abstract Introduction: Data on the impact of the COVID-19 lockdown on glycemic control and psychological well-being in individuals with Type 1 Diabetes Mellitus (T1DM) showed mixed results. Some studies showed improvement in glycemic control attributed to more time for self-care and a more regular lifestyle schedule during the lockdown. However, most published data reflects a short duration of 3–5 months. The impact of long-term social isolation and transition to telemedicine on the health of T1DM patients remains unknown. Our study analyzes patient perception surrounding the impact of an 11-month lockdown on glycemic control, well-being, and self-reported depression symptoms. Methods: PHQ-9 was integrated into a 55-question survey created using RedCap, a secure portal for managing surveys. The survey was sent to 160 T1DM patients over the age of 18 to gauge their current diabetes management and overall well-being prior to, and during the pandemic. The survey also inquired about patients’ perceived effectiveness of telemedicine visits. PHQ9 scores were collected and analyzed along with survey responses. Results: Data collection is still ongoing. From the 47 responders, the PHQ9 screening showed 51% were in the minimal depression score, 34% in the range of mild depression, 11% in moderate depression, and 4% scored in moderate to severe depression. No patients scored within severe depression. In a regular week during the pandemic, 40% of patients experienced difficulty with their motivation and diabetes management and 60% reported no concern, as compared to 36% and 64% respectively before the pandemic. Among the 47 of patient respondents, 30 reported both A1c levels prior and during the pandemic of which 46% showed an improved A1c amid the pandemic, 10% had no change, and 44% reported a worsened A1c level. For the telehealth part of the survey, 90% of patients reported feeling “comfortable with the level of care” they receive via telemedicine, whereas the other 10% were not. Whilst 54% of patients preferred in-person visits and 46% indicated a preference for telehealth visits. Conclusion: T1DM management is challenging. The pandemic adds to the complexity and burden to both self-management and healthcare delivery. Staying locked down for a prolonged period of time imposes economical, psychological, and medical constraints to diabetes care, as nearly half of the patients reported worsening of glycemic control. Our comprehensive survey reports the longest duration reported up to date of how the COVID-19 lockdown impacts patient’s perceived changes in their mental health and diabetes management. It helps clinicians understand the connection between mental and physical health during the pandemic and improve time-restricted telehealth visits by understanding patient concerns. Additional larger scale studies are imperative to expand the knowledge in this field.


2022 ◽  
Vol 11 (2) ◽  
pp. 286
Author(s):  
Isabel Leiva-Gea ◽  
Maria F. Martos-Lirio ◽  
Ana Gómez-Perea ◽  
Ana-Belen Ariza-Jiménez ◽  
Leopoldo Tapia-Ceballos ◽  
...  

Aims: To evaluate the relationship between daily sensor scan rates and changes in HbA1c and hypoglycemia in children. Methods: We enrolled 145 paediatric T1D patients into a prospective, interventional study of the impact of the FreeStyle Libre 1 system on measures of glycemic control. Results: HbA1c was higher at lower scan rates, and decreased as the scan rate increased to 15–20 scans, after which it rose at higher scan rates. An analysis of the change in hypoglycemia, based on the number of daily sensor scans, showed there was a significant correlation between daily scan rates and hypoglycemia. Subjects with higher daily scan rates reduced all levels of hypoglycaemia. Conclusions: HbA1c is higher at lower scan rates, and decreases as scan rate increases. Reductions in hypoglycemia were evident in subjects with higher daily scan rates.


2020 ◽  
pp. 193229682095278
Author(s):  
Tara Kaushal ◽  
Lorraine E. Levitt Katz ◽  
Janet Joseph ◽  
Michelle Marowitz ◽  
Knashawn H. Morales ◽  
...  

Background: Adolescents with type 1 diabetes (T1D) have higher hemoglobin A1C (HbA1c) levels than others. In general, adolescents engage with text messaging (TM) and financial incentives, both associated with improved diabetes outcomes. This study aimed to assess the impact of a TM intervention with financial incentives on self-care behaviors and HbA1c. Methods: A six-month randomized controlled trial compared MyDiaText™, a TM education and support application, with standard care. The sample included 166 teens with T1D, 12-18 years old, attending a diabetes clinic. The intervention group received one daily TM and were instructed to respond. Participants who responded to TMs for the most consecutive days were eligible for a financial reward biweekly via lottery. All participants received prompts to complete the self-care inventory (SCI) at baseline, 90, and 180 days. HbA1c was collected at clinic visits. Changes in SCI and HbA1c were analyzed using a multilevel mixed-effects linear regression model. Intention-to-treat and per-protocol analyses were performed. Results: The median TM response rate was 59% (interquartile range 40.1%-85.2%) and decreased over time. After adjustment for baseline characteristics, in per-protocol analysis, there was a statistically significant difference in SCI score increase in those receiving one TM per day vs control ( P = .035). HbA1c decreased overall, without significant difference between groups ( P = .786). Conclusions: A TM intervention with financial incentives for adolescents with T1D in suboptimal control was associated with increasing self-care report; however, glycemic control did not differ from controls. Further research is needed to develop digital health interventions that will impact glycemic control.


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