Carbohydrate Counting Research Articles

Insulin Therapy in Adults with Type 1 Diabetes Mellitus: a Narrative Review.

Here, we review insulin management options and strategies in nonpregnant adult patients with type 1 diabetes mellitus (T1DM). Most patients with T1DM should follow a regimen of multiple daily injections of basal/bolus insulin, but those not meeting individual glycemic targets or those with frequent or severe hypoglycemia or pronounced dawn phenomenon should consider continuous subcutaneous insulin infusion. The latter treatment modality could also be an alternative based on patient preferences and availability of reimbursement. Continuous glucose monitoring may improve glycemic control irrespective of treatment regimen. A glycemic target of glycated hemoglobin < 7% (53 mmol/mol) is appropriate for most nonpregnant adults. Basal insulin analogues with a reduced peak profile and an extended duration of action with lower intraindividual variability relative to neutral protamine Hagedorn insulin are preferred. The clinical advantages of basal analogues compared with older basal insulins include reduced injection burden, better efficacy, lower risk of hypoglycemic episodes (especially nocturnal), and reduced weight gain. For prandial glycemic control, any rapid-acting prandial analogue (aspart, glulisine, lispro) is preferred over regular human insulin. Faster-acting insulin aspart is a relatively new option with the advantage of better postprandial glucose coverage. Frequent blood glucose measurements along with patient education on insulin dosing based on carbohydrate counting, premeal blood glucose, and anticipated physical activity is paramount, as is education on the management of blood glucose under different circumstances.Plain Language Summary: Plain language summary is available for this article.

Dietary recommendation in diabetes care: Carbohydrate counting and caloric content of Nigerian foods

The prevalence of diabetes mellitus is rising globally and even more in low- and middle-income countries such as Nigeria. Optimal management of the disease is important to improve survival and prevent or delay its complications. Lifestyle management is a standard universal approach in optimizing the care given to diabetic patients. Dietary management is the central link in lifestyle modifications of individuals living with diabetes. Medical nutrition therapy (MNT) is a systematic therapeutic approach of assessing the nutritional needs of an individual, determining nutritional goals, counseling the clients on how to achieve the goals, prescribing and monitoring meal plans to achieve the goals. It is evidence-based, effective, and highly recommended. All carers of the diabetes patient, including the health workers and the family members of the patients need to have basic understanding of MNT but the efforts should be coordinated by licensed dietitians. There are evidences that adherence to prescribed calories is effective in the control of cardiovascular risk factors such as blood glucose, weight, lipid profile, and blood pressure. However, prescription of calories should be based on thoughtful consideration of the nutritional needs, weight goal, personal preferences and tastes and cultural practices of individuals living with diabetes mellitus. Food pyramids give a graphical illustration on the recommended classes and servings of food. Six to eleven servings per day of carbohydrates, 3–5 servings per day of vegetables, 2–4 servings per day of fruit, 2–3 servings per day of dairy products, and 2–3 servings per day of fish are the recommended proportions of the different classes of foods for an adult on an average of 2000 calories. Carbohydrate counting, taken with appropriate insulin dosing and physical activity, has been demonstrated to be effective in optimizing the glycemic control of patients on multiple daily insulin injections. There are challenges in doing this in Nigeria due to lack of food labels. The caloric contents of common Nigerian foods are highlighted so as to help in achieving dietary goals.

Influence of food consumption in the glycemic profile of children and adolescents with type 1 diabetes Mellitus

ABSTRACT Objective To review the dietary intake of children and adolescents with type 1 diabetes Mellitus and its association with the glycemic profile. Methods Longitudinal observational study. Dietary intake was measured using a three-day dietary record and the glycemic profile with a continuous glucose monitoring (range between 70 and 180mg/dL) and serum glycated hemoglobin levels (ideal &lt;7.5%). Anthropometric data, insulin therapy, and carbohydrate counting were collected. Results The sample included 34 individuals with type 1 diabetes Mellitus aged 13.6±2.1 years. The majority of the population was eutrophic (76.4%). The entire sample used the basal-bolus insulin regimen, with mean insulin dose of 1.0±0.2U/kg/day; for 44.1% of the sample the carbohydrate counting method was used. Macronutrients intake was adequate in only 8.8% of the individuals, the highest frequency of inadequacy was related to carbohydrates (p=0.07). Inadequate glycemic control with hyperglycemia episodes and high mean glycated hemoglobin (9.7%) was observed in all individuals (61.3±18.5%). Carbohydrate counting was responsible for maintaining the percentage of time that the patient had interstitial blood glucose values within the range &gt;40% (p&lt;0.001) and maintaining the percentage of time in hyperglycemia &lt;50% (p&lt;0.001). Conclusion The majority of individuals were eutrophic, but presented inadequate dietary intake and glycemic control. The method of counting carbohydrates positively influenced the glycemic profile.

Contribution for Validation of a Questionnaire about Carbohydrate Count and Insulin Dosage in Youth with Type 1 Diabetes Intensive Insulin Therapy

Contribution for Validation of a Questionnaire about Carbohydrate Count and Insulin Dosage in Youth with Type 1 Diabetes Intensive Insulin Therapy

Reliability and validity of an Arabic version of a questionnaire to assess carbohydrate counting skills, knowledge of heart-healthy foods, and nutrition label-reading skills in adults with diabetes

Reliability and validity of an Arabic version of a questionnaire to assess carbohydrate counting skills, knowledge of heart-healthy foods, and nutrition label-reading skills in adults with diabetes

STRATEGIES TO EDUCATE YOUNG PEOPLE WITH TYPE 1 DIABETES MELLITUS ON INSULIN THERAPY: SYSTEMATIC REVIEW

ABSTRACT Objective: to identify evidence available in the literature on educational strategies used in the teaching of insulin therapy to children and adolescents with Type 1 diabetes mellitus. Method: systematic review undertaken in five databases, using the descriptors Insulin/therapeutic use, Patient education as topic, Diabetes mellitus type 1, Child, Infant, Adolescent and keywords, without any time limit. Primary studies on insulin therapy teaching were included, while research on insulin pumps was excluded. Results: 243 studies were identified, 13 of which were included. The results present educational strategies focused on children, adolescents and young people of up to 24 years of age, applied individually or in groups; by telephone contact or text messages by mobile phone; dramatization and educational camps; by a single professional or a multidisciplinary team. The strategies described in the analyzed studies addressed the adjustment of insulin dosages in everyday situations and education for insulin management, associated with the nutritional strategy of carbohydrate counting, diabetes education with a specific module on insulin therapy and intensive insulin use. The studies analyzed the effect of the educational intervention on several clinical and behavioral outcomes, such as glycated hemoglobin and self-efficacy. Conclusion: this review could not identify a single educational strategy able to improve metabolic and psychosocial outcomes. In most cases, nurses are the professionals responsible for the development of educational strategies focused on insulin therapy in children and adolescents with diabetes, regardless of the context in which they will be deployed. This confirms their role as educators.

Prevalence of Dyslipidemia in Patients with Type 1 Diabetes

Introduction: Patients with Type 1 Diabetes tend to present premature cardiovascular disease and dyslipidemia is a relevant risk factor in this cases. Objective: To determine the prevalence of dyslipidemia and its association with glycemic control, insulin therapy, nutritional therapy of carbohydrate counting, body mass index and physical activity level in children, adolescents and adults with Type 1 diabetes. Methodology: Cross-sectional study with 87 children, adolescents and adults with Type 1 Diabetes assisted in a public hospital in Brazil. The variables studied were: age, sex, education level, blood lipid levels, glycated hemoglobin, fasting glucose, body mass index, physical activity level, insulin therapy, and the nutrition therapy of carbohydrate counting. Data were collected from medical records and analyzed in their distribution, frequency, and association with the Person’s exct chi-squared test and Fisher’s exact test (p&lt;0,05). Results: The patients of the study were mostly adults (54%), females (64%) and, 40% concluded high school. The predominant insulin therapy was based in multiple daily injections with basal and rapid-acting analogs of insulin. The minority followed the nutrition therapy of carbohydrate counting. The prevalence of elevated glycated hemoglobin and fasting glucose was high (80,5% and 73,3%, respectively). Obesity was observed in 4,6% of adults. Regarding the blood lipid levels, hypercholesterolemia and low levels of HDL-c were observed in all age categories. Dyslipidemia was not associated with the variables of the study. Conclusion: There was observed dyslipidemia in all age categories of the patients of the study. Most of them were not following the nutrition therapy of carbohydrate counting and presented poor glycemic control. These two last caracteristics are modifiable and more educational activities should be developed to encourage self-care and prevent premature diabetes complications like cardiovascular diseases.

Assessment of Carbohydrate Count Method Knowledge Levels and Insulin Types of Individuals with Type 1 DM

Objectives: The purpose of this research is to evaluate the knowledge status of carbohydrate (CHO) counting method and to examine the insulin types and doses of adult individuals with Type 1 diabetes mellitus (T1DM) who applied CHO count.Methods: This is a descriptive study. The working group of this study consisted of 118 patients with T1DM who applied CHO counting, aged 18-65 using outpatient treatment in the endocrine outpatient clinics of Antakya Academy Hospital, Private Eastern Mediterranean Hospital and Private Laurel Hospitals in Hatay. In the study, a questionnaire consisting of questions about the participants’ introductory information (such as age, gender, weight, height, body mass index (BMI), feeding habits (main meals, snacks, fluid consumption), insulin type and doses and CHO counting information level was applied to the participants.Results: The mean age of the participants was 35 years, the mean BMI was 24.5 kg /m2 the mean duration of diabetes was 13.6 months and the duration of CHO counting was 22 months. The most frequently used insulin type was rapid-acting insulin with 49.2%. Participants administered the highest amount of insulin overnight and an average of 14.83 units. The most preferred CHO counting level of the participants was second level with 40.7%. 57.6% of the participants thought that they had information about CHO counting. Participants have the highest information on CHO counts from dietitians (51.7%). Participants’ most preferred method when performing CHO counting; The portion estimation method with 50.8%. In addition, 68.6% of the participants stated that they had no difficulty in adjusting insulin dosage by CHO counting method. 67.8% of the participants thought that CHO amount was more important than CHO types. In addition, 44.1% of the participants who used CHO counting method had information about CHO containing foods, but they hadn’t enough information, and 16.9% of the participants said that they have no idea.Conclusions: Participants were most likely to use overnight and rapid-long-acting insulin, and their preferred method of CHO counting was second level. The majority of participants had knowledge of CHO counting, but their knowledge were insufficient. In addition, the majority of participants didn’t have difficulty adjusting insulin dosage by CHO counting method.

Carbohydrate counting accuracy in adults with cystic fibrosis related diabetes.

Poorly controlled Cystic Fibrosis-Related Diabetes (CFRD) is associated with adverse impacts on lung function and nutritional status. Insulin therapy is the only recommended medical treatment. Carbohydrate Counting (CC) is used to guide insulin doses and can assist in achieving optimal postprandial blood glucose levels. This study aimed to determine the prevalence of individuals with CFRD who carbohydrate count, explore barriers to its use and assess the accuracy of CC in hospitalised patients. A cross-sectional, mixed-methods, descriptive study recruited individuals with CFRD hospitalised at an Australian tertiary hospital. Consenting patients completed a questionnaire. Patients were asked to estimate the carbohydrate content of their ordered meals provided by hospital foodservices. The study dietitian assessed each meal's estimation against the actual content. 17 individuals were recruited to this study and five declined. Seven had a fixed insulin regimen, and ten had a flexible insulin regimen and used CC. Patients in the fixed insulin group reported lower levels of confidence in their ability to carbohydrate count (P < .001) and placed less importance on CC (P < .001). 53% of the fixed insulin group's and 41.7% of the flexible insulin group's estimations of the carbohydrate content of the hospital food items were accurate. Of those patients recruited to this study, 59% used CC as a tool to guide insulin dosing, and patients estimated accurate carbohydrate values in only 46% of meals. Further research is warranted to investigate the most suitable method to assist accurate carbohydrate content estimations in a hospital setting.

Insulin Dosing for Fat and Protein: Is it Time?

The impact of dietary fat and protein on postprandial glycemia in type 1 diabetes (T1D) and the need to adjust for them in the mealtime insulin dose have been controversial (1,2). Recently, carefully designed randomized trials in individuals living with T1D have shown protein and fat consumed in meals with carbohydrate reduce the early postprandial rise (1–2 h) and contribute to postprandial hyperglycemia in the late (3–6 h) postprandial period (3–5). In clinical practice, continuous glucose monitoring highlights the glycemic effects of different meal types demonstrating that mealtime insulin dosing strategies based on carbohydrate counting alone have limitations. There is a need for an evidence-based, safe, and practical method to guide insulin adjustments for high-fat, high-protein meals. In this issue of Diabetes Care , Bell et al. (6) address the pressing clinical question of optimal insulin adjustments for meals containing differing amounts of dietary fat. This is important because postprandial hyperglycemia has been identified as a risk factor for the development of long-term complications of diabetes (7), and higher fat diets have increased in popularity in recent years. The mechanisms by which all three macronutrients impact blood glucose levels in people with T1D is shown in Fig. 1. Dietary carbohydrate is absorbed and rapidly increases the blood glucose concentration (8). Dietary protein results in a delayed and more prolonged increase in blood glucose levels by conversion of amino acids to glucose through gluconeogenesis, as well as an influence on multiple hormones including glucagon, cortisol, growth hormone, insulin-like growth factor 1, and ghrelin, thus increasing insulin resistance (9). Dietary fat also results in a delayed glycemic response by a number of mechanisms. Free fatty acids act via peroxisome proliferator–activated receptors and free fatty acid receptors to impact …

Human Visual System vs Convolution Neural Networks in food recognition task: An empirical comparison

Automated food recognition from food plate is useful for smartphone-based applications promoting healthy lifestyles and for automated carbohydrate counting, e.g. targeted at type I diabetic patients, but the variation of appearance of food items makes it a difficult task. Convolution Neural Networks (CNNs) raised to prominence in recent years, and they will enable those applications if they are able to match HVS accuracy at least in meal classification. In this work we run an experimental comparison of accuracy between CNNs and HVS based on a simple meal recognition task. We set up a survey for humans with two phases, training and testing, and also give the food dataset to state-of-the-art CNNs. The results, considering some relevant variations in the setup, allow us to reach conclusions regarding the comparison, characteristics and limitations of CNNs, which are relevant for future improvements.

Patient directed carbohydrate counting from diagnosis - the Torbay experience

Patient directed carbohydrate counting from diagnosis - the Torbay experience

Review of compliance and methods of carbohydrate counting in paediatric diabetic patients at District General Hospital

Review of compliance and methods of carbohydrate counting in paediatric diabetic patients at District General Hospital

Effects of basic carbohydrate counting versus standard outpatient nutritional education (The BCC Study): study protocol for a randomised, parallel open-label, intervention study focusing on HbA1c and glucose variability in patients with type 2 diabetes

IntroductionRecommendations on energy intake are key in body weight management to improve glycaemic control in people with type 2 diabetes (T2D). International clinical guidelines recommend a variety of eating patterns...

Does meal-time insulin dosing based on fat-protein counting give positive results in postprandial glycaemic profile after a high protein-fat meal in adolescents with type 1 diabetes: a randomised controlled trial.

The present study investigated the effects of fat-protein (CFP) counting in addition to carbohydrate (CARB) counting for calculating prandial insulin dosage on blood glucose profile in patients with type 1 diabetes (T1D) on basal-bolus insulin therapy. In this single centre, cross-over, randomised, controlled study, control meal (SM: standard meal using a carbohydrate counting method) and three test meals (HPM: high protein meal using a carbohydrate counting method; HPFM-a: high protein-fat meal using a carbohydrate counting method; HPFM-b: high protein-fat meal using a carbohydrate and fat-protein counting method) were compared on postprandial early (0-120min), late (120-240min) and total (0-240min) glucose response in 30 patients with T1D, aged 16-18years. The glucose levels of 0-90min did not change after different meal consumptions (P>0.05), whereas 120-240min glucose levels were higher after HPFM-a consumption compared to HPFM-b consumption (P<0.05). There were no significant differences between meals with respect to the early postprandial glucose response (0-120min) (P=0.405). In late response (120-240min), HPFM-b [area under the curve (AUC)=20609 (582)mg dL-1 ×dk] was significantly lower than SM [AUC=24092 (9015)mg dL-1 ×dk], HPM [AUC=24072(5853)mg dL-1 ×dk] and HPFM-a [AUC=25986(6979)mg dL-1 ×dk] (P=0.032). Meal-related insulin dosing based on carbohydrate plus fat/protein counting has given positive results in the postprandial glycaemic profile as a result of lower postprandial glycaemic levels compared to conventional carbohydrate counting in patients with T1D after a high protein-fat meal.

19 - A Fully-Automated Artificial Pancreas to Alleviate the Burden of Carbohydrate Counting in Type 1 Diabetes

Most current artificial pancreas systems still require carbohydrate counting of each meal, which is a burdensome task. Therefore, we have designed a fully automated artificial pancreas system that is being tested in phase II clinical trial. First, we hypothesized that the delivery of insulin, pramlintide and glucagon will alleviate this burden and control glucose levels without any user input. The system was tested against insulin-alone artificial pancreas with carbohydrate counting on 9 test patients. While optimizing the dosing algorithm, results showed that glucagon wasn’t needed to control participants’ sugar levels. Since glucagon is an additional hormone carrying additional burdens for patients, glucagon was removed to make the system applicable in the real world. Preliminary results from the final algorithm showed that for 3 test patients, time spent in the target range was 78% in the insulin-plus-pramlintide arm with 12% of the time in hyperglycemia compared to 75% time in range for the insulin-alone control arm with 25% of time spent in hyperglycemia. We are currently running a randomized controlled crossover noninferiority trial on 25 participants to compare insulin-plus-pramlintide artificial pancreas without carbohydrate counting to insulin-alone artificial pancreas with carbohydrate counting. The primary outcome is a time in the target range (3.9-10.0 mmol/L). This is important because the system acts like a healthy pancreas resulting in improved quality of life and fewer diabetes complications.

Cystic fibrosis related diabetes: Nutrition and growth considerations

Nutritional considerations are crucial to the optimal management of cystic fibrosis related diabetes (CFRD). The development of abnormal glucose tolerance and CFRD can have negative effects on CF nutritional status. Treatment of CFRD with insulin replacement is essential; however, medical nutrition therapy is important to maintain nutritional status while normalizing blood glucose levels. CF Foundation Nutritional Guidelines are recommended for the nutritional management of CFRD; specifically, the diet should be high in calories, protein, fat, and salt. Carbohydrate intake is not limited, but carbohydrate counting can be used to guide insulin dosing and maintain consistent blood glucose levels. CFTR modulator therapy shows early promise for the improvement of growth and nutritional parameters in CF.

One potato, two potato,… assessing carbohydrate counting accuracy in adolescents with type 1 diabetes

Diabetes education includes nutritional education and the provision of practical guidelines as to the interrelation between insulin requirements and carbohydrate intake. Carbohydrate (CHO) counting has therefore been a recommended daily practice to help patients to manage blood glucose levels in type 1 diabetes (T1D). Evidence suggests that CHO estimates should be within 10–15 g of the actual meal for optimal postprandial blood glucose control.

The dietary education trial in carbohydrate counting (DIET-CARB Study): study protocol for a randomised, parallel, open-label, intervention study comparing different approaches to dietary self-management in patients with type 1 diabetes

IntroductionClinical guidelines recommend that patients with type 1 diabetes (T1D) learn carbohydrate counting or similar methods to improve glycaemic control. Although systematic educating in carbohydrate counting is still not offered...

Prospective evaluation of insulin‐to‐carbohydrate ratio in children and adolescents with type 1 diabetes using multiple daily injection therapy

Assessment of insulin-to-carbohydrate ratio (ICR) in children and adolescents with type 1 diabetes mellitus (T1DM) using multiple daily injection (MDI) therapy. This prospective observational study was conducted over a 2-year period at Sohag University Hospital, Egypt. Children and adolescents aged 4 to 17 years, diagnosed with T1DM for at least 1 year, with fasting serum C-peptide levels <0.24 ng/dL and whose parents accepted to shift their management to flexible MDI using carbohydrate counting, were included. Participants were initially hospitalized for estimation of ICR and insulin doses, then followed-up monthly for further adjustments. Insulin doses, ICR, and glycemic control parameters were assessed after 3 months. The study included 201 participants, 110 (54.7%) of them were males. The median age was 9.5 years (interquartile range: 7-12.5 years). Bolus insulin requirements estimated by the 500 rule were significantly lower than the actual doses used by the study participants for all meals (P < .001). Bolus insulin requirement for morning meal was significantly higher compared to other meals (P < .001). Linear regression analyses between ICR for different meals and the reciprocal of total daily dose (TDD) in 96 participants with optimum glycemic control revealed that ICR could be calculated as 301 to 309/TDD for morning meal (R2 = 0.97, P < .001), 317 to 331/TDD for afternoon meal (R2 = 0.96, P < .001), and 362 to 376/TDD for evening meal (R2 = 0.98, P < .001). Bolus insulin requirements showed diurnal variation. Using 301 to 309/TDD, 317 to 331/TDD, and 362 to 376/TDD formulas would be more appropriate than the 500 rule for initial estimation of ICR for morning, afternoon, and evening meals, respectively.