scholarly journals Modeling Carbohydrate Counting Error in Type 1 Diabetes Management

2020 ◽  
Vol 22 (10) ◽  
pp. 749-759 ◽  
Author(s):  
Chiara Roversi ◽  
Martina Vettoretti ◽  
Simone Del Favero ◽  
Andrea Facchinetti ◽  
Giovanni Sparacino
Keyword(s):  
Type 1 Diabetes ◽  
Diabetes Management ◽  
Carbohydrate Counting ◽  
Counting Error

scholarly journals A Time-Friendly, Feasible Measure of Nutrition Knowledge in Type 1 Diabetes: The Electronic Nutrition and Carbohydrate Counting Quiz (eNCQ)

2018 ◽  
Vol 13 (1) ◽  
pp. 68-74
Author(s):  
Arwen M. Marker ◽  
Amy E. Noser ◽  
Nicole Knecht ◽  
Mark A. Clements ◽  
Susana R. Patton
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Nutrition Education ◽  
Diabetes Management ◽  
Clinical Care ◽  
Nutrition Knowledge ◽  
Diabetes Diagnosis ◽  
Carbohydrate Counting ◽  
One Year

Background: Greater knowledge about nutrition and carbohydrate counting are associated with improved glycemic control and quality of life in youth with type 1 diabetes (T1D). However, limited assessments of nutrition and carbohydrate knowledge have been developed, and existing measures can be time-consuming, overly broad, or not conducive to routine clinical use. To fill this gap, we developed and examined the feasibility of administering the electronic Nutrition and Carbohydrate Counting Quiz (eNCQ). Method: Ninety-two caregivers and 70 youth with T1D (mean age 12.5 years; mean time since diagnosis 5 years; English speaking) completed the 19-item eNCQ via tablet during a routine clinical visit. Completion time and item completion rates were used to assess feasibility. Relationships between eNCQ scores and patient demographics, diabetes management, and health outcomes were examined. Results: Participants took 10 minutes, on average, to complete the eNCQ. Total and Carbohydrate subscale scores (youth report) were negatively correlated with youth hemoglobin A1c (total r = –.38, carbohydrate r = –.38, Ps < .05), indicating that greater nutrition knowledge related to better glycemic control. Nutrition knowledge scores were generally high, but knowledge was negatively related to time since diabetes diagnosis ( r = –.276, P < .05). Conclusions: Findings support feasibility of the eNCQ to assess nutrition knowledge in routine clinical care. Following additional acceptability and validity testing, the eNCQ may identify families in need of further nutrition education. Nutrition assessment is particularly indicated for youth over one year since T1D diagnosis, as these families displayed lower nutrition knowledge and may need continuing education to maintain diabetes-specific nutrition knowledge over time.

scholarly journals Carbohydrate Counting App Using Image Recognition for Youth With Type 1 Diabetes: Pilot Randomized Control Trial

10.2196/22074 ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. e22074
Author(s):  
Jeffrey E Alfonsi ◽  
Elizabeth E Y Choi ◽  
Taha Arshad ◽  
Stacie-Ann S Sammott ◽  
Vanita Pais ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Diabetes Management ◽  
Digital Health ◽  
Controlled Trial ◽  
Qualitative Interviews ◽  
Mobile App ◽  
Thinking Aloud ◽  
Carbohydrate Counting ◽  
Scale Scores

Background Carbohydrate counting is an important component of diabetes management, but it is challenging, often performed inaccurately, and can be a barrier to optimal diabetes management. iSpy is a novel mobile app that leverages machine learning to allow food identification through images and that was designed to assist youth with type 1 diabetes in counting carbohydrates. Objective Our objective was to test the app's usability and potential impact on carbohydrate counting accuracy. Methods Iterative usability testing (3 cycles) was conducted involving a total of 16 individuals aged 8.5-17.0 years with type 1 diabetes. Participants were provided a mobile device and asked to complete tasks using iSpy app features while thinking aloud. Errors were noted, acceptability was assessed, and refinement and retesting were performed across cycles. Subsequently, iSpy was evaluated in a pilot randomized controlled trial with 22 iSpy users and 22 usual care controls aged 10-17 years. Primary outcome was change in carbohydrate counting ability over 3 months. Secondary outcomes included levels of engagement and acceptability. Change in HbA1c level was also assessed. Results Use of iSpy was associated with improved carbohydrate counting accuracy (total grams per meal, P=.008), reduced frequency of individual counting errors greater than 10 g (P=.047), and lower HbA1c levels (P=.03). Qualitative interviews and acceptability scale scores were positive. No major technical challenges were identified. Moreover, 43% (9/21) of iSpy participants were still engaged, with usage at least once every 2 weeks, at the end of the study. Conclusions Our results provide evidence of efficacy and high acceptability of a novel carbohydrate counting app, supporting the advancement of digital health apps for diabetes care among youth with type 1 diabetes. Further testing is needed, but iSpy may be a useful adjunct to traditional diabetes management. Trial Registration ClinicalTrials.gov NCT04354142; https://clinicaltrials.gov/ct2/show/NCT04354142

Evaluation of Meal Carbohydrate Counting Errors in Patients with Type 1 Diabetes

2021 ◽  
Author(s):  
Sina Buck ◽  
Collin Krauss ◽  
Delia Waldenmaier ◽  
Christina Liebing ◽  
Nina Jendrike ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Insulin Therapy ◽  
Standardized Test ◽  
Carbohydrate Content ◽  
Estimation Accuracy ◽  
Carbohydrate Counting ◽  
Counting Error ◽  
Patients With Diabetes ◽  
Correct Estimation

Abstract Aim Correct estimation of meal carbohydrate content is a prerequisite for successful intensified insulin therapy in patients with diabetes. In this survey, the counting error in adult patients with type 1 diabetes was investigated. Methods Seventy-four patients with type 1 diabetes estimated the carbohydrate content of 24 standardized test meals. The test meals were categorized into 1 of 3 groups with different carbohydrate content: low, medium, and high. Estimation results were compared with the meals’ actual carbohydrate content as determined by calculation based on weighing. A subgroup of the participants estimated the test meals for a second (n=35) and a third time (n=22) with a mean period of 11 months between the estimations. Results During the first estimation, the carbohydrate content was underestimated by −28% (−50, 0) of the actual carbohydrate content. Particularly meals with high mean carbohydrate content were underestimated by −34% (−56, −13). Median counting error improved significantly when estimations were performed for a second time (p<0.001). Conclusions Participants generally underestimated the carbohydrate content of the test meals, especially in meals with higher carbohydrate content. Repetition of estimation resulted in significant improvements in estimation accuracy and is important for the maintenance of correct carbohydrate estimations. The ability to estimate the carbohydrate content of a meal should be checked and trained regularly in patients with diabetes.

scholarly journals Carbohydrate Counting App Using Image Recognition for Youth With Type 1 Diabetes: Pilot Randomized Control Trial (Preprint)

2020 ◽  
Author(s):  
Jeffrey E Alfonsi ◽  
Elizabeth E Y Choi ◽  
Taha Arshad ◽  
Stacie-Ann S Sammott ◽  
Vanita Pais ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Diabetes Management ◽  
Digital Health ◽  
Controlled Trial ◽  
Qualitative Interviews ◽  
Mobile App ◽  
Thinking Aloud ◽  
Carbohydrate Counting ◽  
Scale Scores

BACKGROUND Carbohydrate counting is an important component of diabetes management, but it is challenging, often performed inaccurately, and can be a barrier to optimal diabetes management. iSpy is a novel mobile app that leverages machine learning to allow food identification through images and that was designed to assist youth with type 1 diabetes in counting carbohydrates. OBJECTIVE Our objective was to test the app's usability and potential impact on carbohydrate counting accuracy. METHODS Iterative usability testing (3 cycles) was conducted involving a total of 16 individuals aged 8.5-17.0 years with type 1 diabetes. Participants were provided a mobile device and asked to complete tasks using iSpy app features while thinking aloud. Errors were noted, acceptability was assessed, and refinement and retesting were performed across cycles. Subsequently, iSpy was evaluated in a pilot randomized controlled trial with 22 iSpy users and 22 usual care controls aged 10-17 years. Primary outcome was change in carbohydrate counting ability over 3 months. Secondary outcomes included levels of engagement and acceptability. Change in HbA<sub>1c</sub> level was also assessed. RESULTS Use of iSpy was associated with improved carbohydrate counting accuracy (total grams per meal, <i>P</i>=.008), reduced frequency of individual counting errors greater than 10 g (<i>P</i>=.047), and lower HbA<sub>1c</sub> levels (<i>P</i>=.03). Qualitative interviews and acceptability scale scores were positive. No major technical challenges were identified. Moreover, 43% (9/21) of iSpy participants were still engaged, with usage at least once every 2 weeks, at the end of the study. CONCLUSIONS Our results provide evidence of efficacy and high acceptability of a novel carbohydrate counting app, supporting the advancement of digital health apps for diabetes care among youth with type 1 diabetes. Further testing is needed, but iSpy may be a useful adjunct to traditional diabetes management. CLINICALTRIAL ClinicalTrials.gov NCT04354142; https://clinicaltrials.gov/ct2/show/NCT04354142

scholarly journals Impact of Carbohydrate Counting Error on Glycemic Control in Open-Loop Management of Type 1 Diabetes: Quantitative Assessment Through an in silico Trial

2021 ◽  
pp. 193229682110123
Author(s):  
Chiara Roversi ◽  
Martina Vettoretti ◽  
Simone Del Favero ◽  
Andrea Facchinetti ◽  
Pratik Choudhary ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
In Silico ◽  
Open Loop ◽  
Random Errors ◽  
Linear Regression Models ◽  
Reference Case ◽  
Counting Error ◽  
The Impact

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.

Can Innovative Technologies Overcome HbA1c Disparity for African-American Youth with Type 1 Diabetes?

2021 ◽  
pp. 193229682110213
Author(s):  
Stuart Chalew ◽  
Alan M. Delamater ◽  
Sonja Washington ◽  
Jayalakshmi Bhat ◽  
Diane Franz ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Racial Disparity ◽  
Diabetes Management ◽  
New Technology ◽  
African American Youth ◽  
Glucose Monitoring ◽  
Supportive Role

Achieving normal or near-normal glycemic control as reflected by HbA1c levels in patients with type 1 diabetes (T1D) is important for preventing the development and progression of chronic complications. Despite delineation and dissemination of HbA1c management targets and advances in insulin pharmacology, insulin delivery systems, and glucose monitoring, the majority of children with T1D do not achieve HbA1c goals. In particular, African Americans are more likely not to reach HbA1c goals and have persistently higher HbA1c than Non-Hispanic Whites. Availability of pumps and other technology has not eliminated the disparity in HbA1c. Multiple factors play a role in the persisting racial disparity in HbA1c outcome. The carefully designed application and deployment of new technology to help the patient/family and facilitate the supportive role of the diabetes management team may be able to overcome racial disparity in glycemic outcome and improve patient quality of life.

scholarly journals A global perspective on the issue of access to insulin

Diabetologia ◽  
2021 ◽  
Author(s):  
David Beran ◽  
Maria Lazo-Porras ◽  
Camille M. Mba ◽  
Jean Claude Mbanya
Keyword(s):  
Type 1 Diabetes ◽  
Diabetes Management ◽  
Multinational Companies ◽  
Global Perspective ◽  
Patient Access ◽  
Middle Income ◽  
Middle Income Countries ◽  
Wide Range ◽  
Pricing And Reimbursement

AbstractThe discovery of insulin in 1921 changed the prognosis for people with type 1 diabetes. A century later, availability and affordability of insulin remain a challenge in many parts of the globe. Using the WHO’s framework on understanding the life cycle of medicines, this review details the global and national challenges that affect patients’ abilities to access and afford insulin. Current research and development in diabetes has seen some innovations, but none of these have truly been game-changing. Currently, three multinational companies control over 95% of global insulin supply. The inclusion of insulin on the WHO’s Prequalification Programme is an opportunity to facilitate entry of new companies into the market. Many governments lack policies on the selection, procurement, supply, pricing and reimbursement of insulin. Moreover, mark-ups in the supply chain also affect the final price to the consumer. Whilst expenses related to diabetes are mostly covered by insurance in high-income countries, many patients from low- and middle-income countries have to pay out of their own pockets. The organisation of diabetes management within the healthcare system also affects patient access to insulin. The challenges affecting access to insulin are complex and require a wide range of solutions. Given that 2021 marks the centenary of the discovery of insulin, there is need for global advocacy to ensure that the benefits of insulin and innovations in diabetes care reach all individuals living with diabetes. Graphical abstract

Effects of advanced carbohydrate counting in patients with Type 1 diabetes: a systematic review

2014 ◽  
Vol 31 (8) ◽  
pp. 886-896 ◽  
Author(s):  
S. Schmidt ◽  
B. Schelde ◽  
K. Nørgaard
Keyword(s):  
Systematic Review ◽  
Type 1 Diabetes ◽  
Carbohydrate Counting
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