The effect of the modified fat-protein unit algorithm compared with that of carbohydrate counting on postprandial glucose in adults with type-1 diabetes when consuming meals with differing macronutrient compositions: a randomized crossover trial

BACKGROUND

The optimization of glucose control in type-1 diabetes is challenged by postprandial glycemic variability. This study aimed to compare the postprandial glycemic effects of carbohydrate counting and the modified fat-protein unit (FPU) algorithms following meals with different protein and fat emphases in adults with type-1 diabetes.

METHODS

Thirty adults with type-1 diabetes aged 18 to 45 years participated in a randomized crossover trial. In a random order, participants consumed four test meals with equivalent energy and different macronutrient emphases on four separate mornings. The modified FPU algorithms and carbohydrate counting were used to determine the insulin dose for the test meals. A continuous glucose monitoring system was used to measured postprandial glycemia.

RESULTS

Compared with carbohydrate counting, the modified FPU algorithm significantly decreased the late postprandial mean glucose levels (p = 0.026) in high protein-fat meals. The number of hypoglycemia episodes was similar between insulin dosing algorithms for the high protein-fat meals; hypoglycemic events were considerably higher for the modified FPU in the normal protein-fat meal (p = 0.042).

CONCLUSIONS

The modified FPU algorithm may improve postprandial glycemic control after consuming high protein-fat meals in adults with type-1 diabetes but may result in increased hypoglycemia risk when used with a normal protein-fat meal.

Carbohydrate counting implementation on pediatric type 1 diabetes mellitus: systematic review and meta-analysis

PURPOSE

Type 1 diabetes mellitus, which is the most common type of diabetes among children, is not curable but can be managed well without a negative effect on quality of life. One of the treatments of type 1 diabetes mellitus is carbohydrate counting. This systematic review and meta-analysis sought to evaluate the efficacy of carbohydrate counting with regard to hemoglobin A1c (HbA1c) reduction in children with type 1 diabetes mellitus.

METHODS

Nine studies were assessed, with the primary outcome being glycemic control (HbA1c changes). We searched the following electronic databases: ProQuest, PubMed, Scopus, and ScienceDirect. The quality of studies included was assessed using the risk of bias for randomized control trials and the JBI Critical Appraisal Checklist for observational and cross-sectional studies. Quantitative analyses were made and extrapolated into a forest plot.

RESULTS

A total of 1,693 articles were identified. Four reviewers independently screened titles and abstracts. Of the 36 articles screened, 34 articles were found to be eligible. Of these, 25 studies were excluded because of unsuitable outcomes and study designs. Nine articles were included in the final analysis. Meta-analysis showed that there was a reduction in HbA1c in the carbohydrate counting group as compared to the control group. The cumulative effect of carbohydrate counting on HbA1c was a mean difference of -0.55 (95% confidence interval, -0.81 to -0.28, P<0.001). All of the studies exhibited similar results with the mean difference reduction favoring the interventional group. However, the heterogeneity analysis revealed an I2 value of 88%, implying high heterogeneity in the meta-analysis.

CONCLUSION

The meta-analysis showed evidence favoring the use of carbohydrate counting in the management of type 1 diabetes mellitus.

Carbohydrate counting as a strategy to optimize glycemic control in type 1 diabetes mellitus

Objective

The objective of this study was to verify the impact of carbohydrate counting (CC) on glycemic control and body weight variation (primary and secondary outcomes, respectively) between consultations in patients with diabetes mellitus (T1D) followed at a tertiary hospital in southern Brazil in a public health system environment. We also sought to investigate CC adherence.

Materials and methods

This retrospective cohort study included 232 patients with T1D who underwent nutritional monitoring at a referral hospital for diabetes care between 2014 and 2018. To assess primary and secondary outcomes, data from 229 patients, 49 of whom underwent CC during this period and 180 individuals who used fixed doses of insulin, were analyzed. The impact of CC on glycemic control was assessed with the mean glycated hemoglobin (HbA1c) level at all consultations during the follow-up period.

Results

In the model adjusted for the most confounders (except pregnancy), the mean HbA1c was better in the CC group (8.66 ± 0.4% vs. 9.36 ± 0.39%; p = 0.016), and body weight variation was lower (0.13 ± 0.28 kg vs. 0.53 ± 0.24 kg; p = 0.024). Adherence to CC was reported in 69.2% of consultations.

Conclusion

CC optimized the glycemic control of individuals with T1D, resulting in less weight variation than in the fixed insulin dose group, which indicates that CC is an important care strategy for these patients.

Empowering Patients with Type 1 Diabetes through a Multidisciplinary Team-assisted, Technology-Enabled Education Program

BACKGROUND

Carbohydrate counting is a tool that helps patients with type 1 diabetes (T1D) to control their blood glucose. It calculates the bolus insulin dose needed from the total amount of carbohydrates consumed at each meal. However, carbohydrate counting can be quite challenging. The Diabetes Tele Management System® (DTMS®) is a telemedicine-based program that enables the patient to interact directly with a professionally trained, multidisciplinary team (MDT) of experts. This, along with technology-enabled education programs, could allow people with T1D to achieve glycemic control.

METHODS

Fifty patients with T1D between 5 and 35 years with a diabetes duration of at least 6 months, baseline HbA1c of 7 or above, using SCII or MDI and willing to take part in the study were invited to participate in an MDT-assisted technology-enabled program and trained trimonthly on carbohydrate counting. The control group went on to perform carbohydrate counting independently and used technologies at their convenience. The test group additionally received continuous individual assistance from the MDT.

RESULTS

The MDT-assisted patients had significantly decreased HbA1c, blood glucose levels, decreased episodes of hyperglycemia and hypoglycemia, and reported a more positive outlook on life.

CONCLUSION

Carbohydrate counting remains a challenge for youth with T1D, and errors in counting can have a clinical impact. Our data suggested that the assistance from an MDT of experts was associated with improved carbohydrate counting, which led to improved glycemic control and reduced complications.

Efficacy and safety of carbohydrate counting versus other forms of dietary advice in patients with type 1 diabetes mellitus: A systematic review and meta-analysis of randomized clinical trials

BACKGROUND AND AIMS

Diabetes mellitus (DM) is one of the most prevalent chronic non-communicable diseases globally, and the only way to reduce its complications is good glycemic control. Insulin remains the only approved treatment for type 1 DM (T1DM) and is used by many with Type 2 DM (T2DM). Carbohydrate counting is considered the ideal way to calculate meal-related insulin doses since it allows greater flexibility in diet and could, in some people, reduce the burden of the disease. This systematic review's primary objective was to assess carbohydrate counting efficacy in reducing glycated hemoglobin (HbA_1c ) and safety by not increasing hypoglycemia risk, inducing an increase in body weight or blood lipids, and reducing the quality of life of people with T1DM.

METHODS

We included randomized controlled clinical trials with a parallel-group design comparing any carbohydrate counting forms with standard care or other forms of dietary advice or insulin dose calculation in people with T1DM with a follow up period of at least three months and with no restrictions in language, age, or settings. As a primary outcome, we consider the change of HbA_1c within at least three months. Secondary outcomes were hypoglycemia events, body weight changes, blood lipids levels, and the total daily insulin dose. We also evaluated health-related quality of life changes and diabetes treatment satisfaction questionnaires.

RESULTS

Data from 11 studies with 899 patients were retrieved with a mean follow of 52 ± 35.5 weeks. Carbohydrate counting is not better in reducing HbA_1c , SMD - 0.24% (95%CI -0.68 to 0.21) than all dietary advice forms. However, this finding was highly heterogeneous. We identified three studies that account for most of the heterogeneity using clustering algorithms. A second analysis excluding these studies shows a meaningful HbA_1c reduction, SMD - 0.52% (95%CI -0.82 to -0.23) with low heterogeneity. In the subgroup analysis, carbohydrate counting significantly reduces HbA_1c compared to usual diabetes education. Carbohydrate counting doesn't relate to any substantial change in blood lipids, body weight, hypoglycemia risk, or daily insulin dose. Finally, we analyzed the effect of trial duration with HbA_1c reduction and found no significant change related to time.

CONCLUSIONS

Carbohydrate counting is an efficacious technique to safely reduce HbA_1c in adults and children compared to standard diabetes education. And its effect doesn't seem to change with prolonged time. Standardization in reporting important outcomes like hypoglycemia and quality of life is vital to produce comparable evidence in carbohydrate counting clinical trials. This SR was registered in PROSPERO under code: CRD42020218499. This article is protected by copyright. All rights reserved.

Effectiveness of carbohydrate counting and Dietary Approach to Stop Hypertension dietary intervention on managing Gestational Diabetes Mellitus among pregnant women who used metformin: A randomized controlled clinical trial

BACKGROUND

Gestational diabetes mellitus (GDM) is one of the most common complication of pregnancy that has significant impacts on both mother and her offspring health. The present study aimed to examine the effect of carbohydrate counting, carbohydrate counting combined with DASH, and control dietary interventions on glycemic control, and maternal and neonatal outcomes.

METHODS

A total of 75 pregnant women with GDM at 24th - 30th week of gestation were enrolled and randomized to follow one of the three diets: control or carbohydrate counting, or carbohydrate counting combined with Dietary Approach to Stop Hypertension (DASH). Only 70 of them completed the study until delivery. Fasting blood samples were taken at baseline and the end of the study to measure fasting blood glucose (FBG), fasting insulin, glycated hemoglobin (HbA1c), and fructosamine. Homeostatic model assessment-insulin resistance (HOMA-IR) score was calculated using HOMA2 calculator program. The participants recorded at least four blood glucose readings per day. Maternal and neonatal outcomes were collected from medical records. Dietary intake was assessed by three-day food records at the baseline and the end of the study.

RESULTS

Adherence to the three dietary interventions, resulted in decreased FBG levels significantly among all the participants (P < 0.05). Consumption of the carbohydrate counting combined with the DASH diet showed significant reduction in serum insulin levels and HOMA-IR score compared to carbohydrate counting group and control group. Means of fructosamine and HbA1c did not differ significantly among the three intervention diet groups. Overall mean of 1-h postprandial glucose (1 h PG) level was significantly lower in the carbohydrate counting combined with DASH group compared with that in the carbohydrate counting group and the control group (P < 0.001). The number of women who were required to commence insulin therapy after dietary intervention was significantly lower in carbohydrate counting group and carbohydrate counting combined with DASH group (P = 0.026). There were no significant differences in other maternal and neonatal outcomes among the three dietary intervention groups.

CONCLUSIONS

The carbohydrate counting and the carbohydrate counting combined with DASH dietary interventions resulted in beneficial effects on FBG and 1 h PG compared with the control diet. The three dietary interventions produced similar maternal and neonatal outcomes in women with GDM.

TRIAL REGISTRATION

This trial was registered on ClinicalTrials.gov under the identification code: NCT03244579. https://clinicaltrials.gov/ct2/show/NCT03244579.

Formative research to develop diabetes self-management education and support (DSMES) program for adults with Type 1 Diabetes

BACKGROUND AND AIM

There is a lack of data on effectiveness of diabetes self-management education and support (DSMES) programs for South Asian adults with type 1 diabetes mellitus (T1DM). This formative research was conducted to explore existing practices on the said subject and gather information for planning an intervention program.

METHODS AND MATERIALS

We conducted in-depth semi-structured interviews with endocrinologists, dieticians, diabetes educators and adults with T1DM. The participants were selected from a mix of public and private health facilities. Thematic analysis using inductive and deductive approach was undertaken. The intervention was developed and refined using the principles of FUSED and COM-B models.

RESULTS

In total, 28 in-depth interviews were conducted, 18 with health care professionals and 10 with adult individuals with T1DM. The results demonstrated deficiencies in the implementation of a structured self-management program for diabetes owing to several patient and healthcare system-related factors. A detailed nutritional counseling was provided at all sites by a qualified dietitian, however, carbohydrate counting was not routinely practiced. The interviews of this formative research revolved around: (a) evaluation of the existing usual care and gaps in implementation of a structured DSMES program, and (b) development of themes that will help in formulation of an intervention package and its effective delivery to the participants.

CONCLUSION

This research study comprehensively investigated the existing practices among diabetes-health care professionals caring for persons living with T1DM and rendered insights towards development of a scientific DSMES program.

Prospective Independent Evaluation of the Carbohydrate Counting Accuracy of Two Smartphone Applications

INTRODUCTION

Smartphone applications (apps) have been designed that help patients to accurately count their carbohydrate intake in order to optimize prandial insulin dose matching. Our aim was to evaluate the accuracy of two carbohydrate (carb) counting apps.

METHODS

Medical students, in the role of mock patients, evaluated meals using two smartphone apps: Foodvisor^® (which uses automatic food photo recognition technology) and Glucicheck^® (which requires the manual entry of carbohydrates with the help of a photo gallery). The macronutrient quantifications obtained with these two apps were compared to a reference quantification.

RESULTS

The carbohydrate content of the entire meal was underestimated with Foodvisor^® (Foodvisor^® quantification minus gold standard quantification = - 7.2 ± 17.3 g; p < 0.05) but reasonably accurately estimated with Glucicheck^® (Glucicheck^® quantification minus gold standard quantification = 1.4 ± 13.4 g; ns). The percentage of meals with an absolute error in carbohydrate quantification above 20 g was greater for Foodvisor^® compared to Glucicheck^® (30% vs 14%; p < 0.01).

CONCLUSION

The carb counting accuracy was slightly better when using Glucicheck^® compared to Foodvisor^®. However, both apps provided a lower mean absolute carb counting error than that usually made by T1D patients in everyday life, suggesting that such apps may be a useful adjunct for estimating carbohydrate content.

Efficacy of Bolus Calculation and Advanced Carbohydrate Counting in Type 2 Diabetes: A Randomized Clinical Trial

Background: Carbohydrate counting and use of automated bolus calculators (ABCs) can help reduce HbA_1c in type 1 diabetes but only limited evidence exists in type 2 diabetes. We evaluated the efficacy of advanced carbohydrate counting (ACC) and use of an ABC compared with manual insulin bolus calculation (MC) in persons with type 2 diabetes. Materials and Methods: A 24-week open-label, randomized clinical study was conducted in 79 persons with type 2 diabetes treated with basal-bolus insulin (mean age 62.5 ± 9.6 years, HbA_1c 8.7% ± 1.0% [72 ± 11 mmol/mol], diabetes duration 18.7 ± 7.6 years). Participants were randomized 1:1 into two groups: ABC group received training in ACC and use of an ABC; MC group received training in ACC and manual calculation of insulin bolus. Participants wore blinded continuous glucose monitors for 6 days at baseline and at study end. Primary endpoint was change in HbA_1c. Results: After 24 weeks, HbA_1c decreased 0.8% (8.8 mmol/mol) in ABC group and 0.8% (9.0 mmol/mol) in MC group with no between-group difference (P = 0.96) and without increase in time in hypoglycemic range (sensor glucose <3.9 mmol/L). Glycemic variability decreased significantly in both groups, whereas the total insulin dose and body mass index (BMI) remained unchanged during the study. Treatment satisfaction increased significantly in both groups after 24 weeks. Conclusion: ACC is an effective, low-cost tool to reduce HbA_1c and glycemic variability in persons with basal-bolus insulin-treated type 2 diabetes without increase in hypoglycemia or BMI. Similar effects were seen with use of an ABC and with use of manual bolus calculation. Trial registration: ClinicalTrials.gov NCT02887898.

The role of carbohydrate counting in glycemic control and oxidative stress in patients with type 1 diabetes mellitus (T1DM)

PURPOSE

Oxidative stress is closely related to type 1 diabetes mellitus (T1DM), playing a key role in the pathogenesis of the disease and progression of complications. It is characterized by loss of equilibrium between oxidative factors and antioxidant protective mechanisms. Several markers have been used to assess both components of oxidative status; two of which are malondialdehyde (MDA) and ferric reducing antioxidant power (FRAP).

METHODS

We investigated glycated hemoglobin (HbA1c), lipid profile, MDA, and FRAP in 35 patients with T1DM, aged 2-23 years, at the end of two 4-month observational periods: period A: standard insulin dosing per meal, and period B: proper prandial insulin dosing based on the amount of carbohydrates contained in each meal.

RESULTS

At the end of period B, (i) glucose control (HbA1c) was improved; (ii) oxidative stress, estimated by MDA, showed a tendency to decrease; and (iii) antioxidant capacity, estimated by FRAP, was significantly increased compared with that of period A. No significant differences were observed in the lipid profile of the patients between the two periods.

CONCLUSION

Proper insulin dosing based on carbohydrate counting (CC) may have an impact on the antioxidant defensive mechanisms of patients with T1DM through the attainment of a better glycemic profile. There are also indications that it may reduce MDA, an important biomarker of oxidative stress and a significant mediator of complications in T1DM. Therefore, prompt dietetic intervention using CC as early as possible after the diagnosis of T1DM is important for achieving optimal glycemic control and improved oxidative status.

Effect of adherence to carbohydrate counting on metabolic control in children and adolescents with type 1 diabetes mellitus

PURPOSE

Carbohydrate counting provides better glycemic control and flexibility than other food planning methods. Consistent adherence to such a complex method is difficult, especially for youth. However, studies that determine adherence to this method and whether it alters metabolic control are limited. The aim of the current study was to determine adherence to this method and investigate its effect on metabolic control, anthropometric measurements, insulin dose, and energy intake.

METHODS

In this prospective cross-sectional study, 53 children and adolescents with type 1 diabetes mellitus aged 2 to18 years and receiving intensive insulin therapy were trained and followed for 6 months. Demographics, anthropometrics, insulin requirements, hemoglobin A1c (HbA1c), fasting lipids, and food records at baseline and study conclusion were evaluated. At the end of the study patients were divided into adherer and nonadherer groups according to carbohydrate estimate deviations from standardized daily sample menus and calculations for accurate insulin doses. More than 10-g variation in daily consumed carbohydrate amount or failure to decide bolus insulin dose was defined as a nonadherer.

RESULTS

The mean HbA1c, low-density lipoprotein cholesterol, and body mass index standard deviation score changed after the carbohydrate counting training while the mean HbA1c between groups was significant (P<0.05). Total daily insulin doses increased, and the mean high-density lipoprotein cholesterol levels decreased in both groups. There were significant correlations between HbA1c and carbohydrate deviation scores as well as HbA1c and caregiver's education level.

CONCLUSION

Since adherence to carbohydrate counting may affect metabolic control, health professionals should evaluate and monitor carbohydrate counting skills of caregivers and patients in order to improve efficiency.

Insulin Pump Settings During Breastfeeding in Women with Type 1 Diabetes

Background: We aimed to explore insulin pump settings in breastfeeding women with type 1 diabetes. Methods: Thirteen unselected breastfeeding women with type 1 diabetes on insulin pump therapy were included consecutively from April 2016 to October 2017. Blinded continuous glucose monitoring (CGM) for 6 days was applied at 1, 2, and 6 months after delivery. Recommendations were intake of 210 g carbohydrate daily while aiming for glucose target range 4.0-10.0 mmol/L and avoiding hypoglycemia. Immediately after delivery a reduction of total insulin dose by 30% of the prepregnancy dose was recommended. Insulin pump target glucose was 5.8 mmol/L. Results: Median diabetes duration was 22 (range 13-36) years. At 1, 2, and 6 months, 13, 11, and 8 women, respectively, were breastfeeding and spent ≥70.8% (25%-99%) of time in the glucose target range and ≤3.8% (0%-15.5%) of time with CGM <4.0 mmol/L at night-time and for 24 h. None of the women experienced severe hypoglycemia. HbA1c was 58 (47-72) mmol/mol and 52 (44-60) at 6 months and prepregnancy, respectively, P = 0.18. At 1, 2, and 6 months, the insulin pump settings remained almost stable with basal insulin rates (at 03.00, 08.00, 12.00, and 18.00) 14% lower and the carbohydrate-to-insulin ratios 10% higher than the prepregnancy settings. Conclusions: In breastfeeding women with type 1 diabetes who consumed sufficient amounts of carbohydrates and obtained appropriate glycemic control, the basal insulin rates were 14% lower and carbohydrate-to-insulin ratios 10% higher than before pregnancy. These data are useful when recommending insulin pump settings after delivery.

Predictor factors of glycemic control in children and adolescents with type 1 diabetes mellitus treated at a referral service in Rio de Janeiro, Brazil

AIM

To evaluate the predictive factors of glycemic control in children and adolescents with type 1 diabetes mellitus (T1DM).

METHODS

Cross-sectional study at a referral service in Rio de Janeiro, Brazil. Sociodemographic, anthropometric, clinical, and dietary factors were evaluated. Food consumption was evaluated by 24 h dietary recall and the NOVA system was adopted for classifying the foods according to the extent and purpose of industrial processing. The predictive factors were evaluated by multivariate linear regression, adopting p < 0.05.

RESULTS

One hundred and twenty children and adolescents participated, with a mean age of 11.74 years (±2.88) and HbA1c of 8.13% (±1.26). The mean diabetes duration was 6.68 years (±3.33) and the insulin used was 1.05 units per kilogram of ideal weight (IU/kg of ideal weight; ±0.46) About 80% (n = 96) used carbohydrate counting and it was verified that 24.27% (±17.89) of the participants' total calories came from ultraprocessed foods. For each year of diagnosis with T1DM and for each IU/kg of weight used, HbA1c increased by 0.087% (β = 0.087, p = 0.007) and 0.651%, respectively (β = 0.651; p = <0.001). Use of carbohydrate counting was associated with a 1.058% reduction in HbA1c (β = -1.058; p = 0.001).

CONCLUSION

Disease duration and insulin dose were directly reflected in HbA1c concentrations, while carbohydrate counting showed an inverse association.

Efficacy and Safety of Fast-Acting Insulin Aspart in People with Type 1 Diabetes Using Carbohydrate Counting: A Post Hoc Analysis of Two Randomised Controlled Trials

INTRODUCTION

Insulin dosing based on carbohydrate counting is the gold standard for improving glycaemic control in type 1 diabetes (T1D). This post hoc analysis aimed to explore the efficacy and safety of fast-acting insulin aspart (faster aspart) according to bolus dose adjustment method in people with T1D.

METHODS

Post hoc analysis of two 26-week, treat-to-target, randomised trials investigating treatment with double-blind mealtime faster aspart, insulin aspart (IAsp), or open-label post-meal faster aspart (onset 1, n = 1143; onset 8, n = 1025). Participants with previous experience continued carbohydrate counting (onset 1, n = 669 [58.5%]; onset 8, n = 428 [41.8%]), while remaining participants used a bolus algorithm.

RESULTS

In onset 1, HbA1c reduction was statistically significantly in favour of mealtime faster aspart versus IAsp with carbohydrate counting (estimated treatment difference [ETD 95% CI] - 0.19% [- 0.30; - 0.09]; - 2.08 mmol/mol [- 3.23; - 0.93]). In onset 8, there was no statistically significant difference in HbA1c reduction with either dose adjustment method, although a trend towards improved HbA1c was observed for mealtime faster aspart with carbohydrate counting (ETD - 0.14% [- 0.28; 0.003]; - 1.53 mmol/mol [- 3.10; 0.04]). In both trials, bolus insulin doses and overall rates of severe or blood glucose-confirmed hypoglycaemia were similar between treatments across dose adjustment methods.

CONCLUSION

For people with T1D using carbohydrate counting, mealtime faster aspart may offer improved glycaemic control versus IAsp, with similar insulin dose and weight gain and no increased risk of hypoglycaemia.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT01831765 (onset 1) and NCT02500706 (onset 8).

FUNDING

Novo Nordisk.

Variation of carbohydrate intake in diabetic children on carbohydrate counting

AIMS

Carbohydrate counting (CC) is a technique for managing diabetes particularly based on the counting of carbohydrates. It allows diabetic patients to vary their amount of carbohydrates from one meal to another by adjusting their insulin dose. The primary objective was to determine the variation of carbohydrate intake (CI) in children on CC.

METHOD

This was a prospective study conducted between 2014 and 2016. We collected the amount of carbohydrates eaten at each meal by 77 diabetic over a period of 28 days (i.e. 8068 data). We analyzed the number and percentage of significant CI variation rates from one day to another, both for the whole day and for each meal. The CI variation rate was deemed significant if it was greater than or equal to 30%.

RESULTS

The percentage of significant CI variation rates was 30% at the daily level, 34% for breakfast, 44% for lunch and dinner, and 53% for snack. The percentage of significant variation rates varied according to age, treatment and occurrence of events.

CONCLUSION

Children varied their CI significantly from one meal to another more than one in three times. CC offers flexibility and a better quality of life for children using this method.

Breastfeeding at night is rarely followed by hypoglycaemia in women with type 1 diabetes using carbohydrate counting and flexible insulin therapy

AIMS/HYPOTHESIS

Hypoglycaemia in association with breastfeeding is a feared condition in mothers with type 1 diabetes. Thus, routine carbohydrate intake at each breastfeed, particularly at night, is often recommended despite lack of evidence. We aimed to evaluate glucose levels during breastfeeding, focusing on whether night-time breastfeeding induced hypoglycaemia in mothers with type 1 diabetes.

METHODS

Of 43 consecutive mothers with type 1 diabetes, 33 (77%) were included prospectively 1 month after a singleton delivery. Twenty-six mothers (mean [SD] age 30.7 [5.8] years, mean [SD] duration of diabetes 18.6 [10.3] years) were breastfeeding and seven mothers (mean [SD] age 31.7 [5.6] years, mean [SD] duration of diabetes 20.4 [6.2] years) were bottle-feeding their infants with formula. All were experienced in carbohydrate counting using individually tailored insulin therapy with insulin analogues (45% on insulin pump, 55% on multiple daily injections). Thirty-two women with type 1 diabetes, matched for age ±1 year and BMI ±1 kg/m², who had not given birth or breastfed in the previous year, served as a control group. Blinded continuous glucose monitoring (CGM) for 6 days was applied at 1, 2 and 6 months postpartum in the breastfeeding mothers who recorded breastfeeds and carbohydrate intake at each CGM period. CGM was applied at 1 month postpartum in the formula-feeding mothers and once in the control women. The insulin dose was individually tailored after each CGM period.

RESULTS

The percentage of night-time spent with CGM <4.0 mmol/l was low (4.6%, 3.1% and 2.7% at each CGM period in the breastfeeding mothers vs 1.6% in the control women, p = 0.77), and the breastfeeding mothers spent a greater proportion of the night-time in the target range of 4.0-10.0 mmol/l (p = 0.01). Symptomatic hypoglycaemia occurred two or three times per week at 1, 2 and 6 months postpartum in both breastfeeding mothers and the control women. Severe hypoglycaemia was reported by one mother (3%) during the 6 month postpartum period and by one control woman (3%) in the previous year (p = 0.74). In breastfeeding mothers at 1 month, the insulin dose was 18% (-67% to +48%) lower than before pregnancy (p = 0.04). In total, carbohydrate was not consumed in relation to 438 recorded night-time breastfeeds, and CGM <4.0 mmol/l within 3 h occurred after 20 (4.6%) of these breastfeeds.

CONCLUSIONS/INTERPRETATION

The percentage of night-time spent in hypoglycaemia was low in the breastfeeding mothers with type 1 diabetes and was similar in the control women. Breastfeeding at night-time rarely induced hypoglycaemia. The historical recommendation of routine carbohydrate intake at night-time breastfeeding may be obsolete in mothers with type 1 diabetes who have properly reduced insulin dose with sufficient carbohydrate intake.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02898428.

Influence of Flexible Insulin Dosing with Carbohydrate Counting Method on Metabolic and Clinical Parameters in Type 1 Diabetes Patients

OBJECTIVE:

The purpose of providing and maintaining a proper metabolic control is to prevent the development of chronic complications. In this study, we aimed to determine the influence of flexible insulin dosing with carbohydrate counting method on metabolic and clinical parameters in type 1 diabetes patients.

MATERIAL AND METHODS:

This study was conducted with patients following up at the Endocrinology Clinic with a diagnosis of type 1 diabetes mellitus between 2012 and 2015. Metabolic and clinical parameters before and after carbohydrate counting were compared.

RESULTS:

Forty patients were included in the study. Of the patients, 40% (n = 16) were female, and 60% (n = 24) were male, and mean age was 21.5 ± 7 year at the time of diagnosis. Statistically significant differences were not detected when haemoglobin A1c, fasting plasma glucose, post-prandial glucose, LDL-cholesterol, and HDL-cholesterol levels were compared at standard dose insulin use and after carbohydrate counting (P < 0.005). Among the parameters measured when the patients received standard dose of insulin without counting carbohydrate and flexible insulin dosing by counting carbohydrate, statistically, significant differences were not detected for baseline insulin dose, bolus insulin dose, triglyceride level, body mass index, or monthly hypoglycemia episodes (P > 0.05).

CONCLUSION:

Flexible insulin dosing with carbohydrate counting provides significant improvements in clinical and metabolic control. We detected improvements in lipid profiles and glycemic control. Additionally, patients generally did not gain weight despite flexible nutrition, and frequency of hypoglycemia remained unchanged despite strict glycemic control.

The influence of carbohydrate consumption on glycemic control in pregnant women with type 1 diabetes

AIMS

To study the influence of the quantity and the quality of carbohydrate consumption on glycemic control in early pregnancy among women with type 1 diabetes.

METHODS

A retrospective study of 107 women with type 1 diabetes who completed 1-3days of diet recording before first antenatal visit, as a part of routine care. The total daily carbohydrate consumption from the major sources (e.g. bread, potatoes, rice, pasta, dairy products, fruits, candy) was calculated. A dietician estimated the overall glycemic index score (scale 0-7).

RESULTS

At least two days of diet recording were available in 75% of the 107 women at mean 64 (SD±14) gestational days. The quantity of carbohydrate consumption from major sources was 180 (±51)g/day. HbA1c was positively associated with the quantity of carbohydrate consumption (β=0.41; 95% CI 0.13-0.70, P=0.005), corresponding to an increase of 0.4% in HbA1c per 100g carbohydrates consumed daily, when adjusted for insulin dose/bodyweight and use of insulin pump treatment. The median (IQR) glycemic index score was 2 (0-3). An adjusted association between HbA1c and glycemic index score was not demonstrated. The women using carbohydrate counting daily (45%) had lower HbA1c compared to the remaining women (6.4 (±0.5) vs. 6.8 (±0.9)% (47±6 vs. 51±10mmol/mol), P=0.01).

CONCLUSIONS

HbA1c in early pregnancy was positively associated with the quantity of carbohydrate consumption regardless of insulin treatment. Carbohydrate counting is probably important for glycemic control in pregnant women with type 1 diabetes.

Carbohydrate Counting during Pregnancy in Women with Type 1 Diabetes: Are There Predictable Changes That We Should Know?

BACKGROUND/AIMS

Carbohydrate counting (CC) is a helpful strategy for the treatment of type 1 diabetes mellitus (T1DM) and the main parameters used in this method are the insulin to carbohydrate ratio (ICR) and the sensitivity factor (SF). Throughout pregnancy, a state of insulin resistance develops. Therefore, we hypothesized that ICR and SF change and our aim was to describe the pattern of modification of these parameters in pregnant women with T1DM on CC.

METHODS

This study followed 21 women with T1DM throughout pregnancy. Starting ICR was 1:15 and SF was calculated using the formula: 1,500/total daily insulin dose (TDID; for regular insulin) or 1,800/TDID (for ultra-rapid analogs). ICR was adjusted every 1-2 weeks according to self-monitoring of blood glucose. SF was recalculated every 1-2 weeks.

RESULTS

Throughout gestation there was a mean decrease in the ICR in breakfast, lunch and dinner of 8.2 (p < 0.0001), 7.7 (p = 0.003) and 7 (p = 0.005) grams per international units (g/IU), respectively. Mean SF reduction from first to third trimester was 10 mg/dL per IU (mg/dL/IU; p < 0.0001).

CONCLUSIONS

Women with T1DM in CC during pregnancy evolve with a progressive reduction in the ICR at every meal (mean of 8.2 g/IU for breakfast, 7.7 g/IU for lunch and 7 g/IU for dinner) and also in the SF (10 mg/dL/IU).

Practices, perceptions and expectations for carbohydrate counting in patients with type 1 diabetes - Results from an online survey

AIMS

Characterize adult patients with diabetes on intensive insulin therapy in terms of: (a) practices and perceived difficulties relative to carbohydrate counting (CC) and diabetes treatment, and (b) their perceptions and expectations relative to CC.

METHODS

Participants completed a 30-question web-based questionnaire.

RESULTS

Participants with type 1 diabetes (T1D) and using CC as part of their treatment plan (n=180) were included in this analysis. Participants were predominantly women (64%), aged 42±13years old and had diabetes for 22±13years. A large proportion of participants reported being confident in applying CC (78%) and considered precise CC as being important for glycemic control (91%), while only 17% reported finding CC difficult. Despite the low perceived difficulty associated with CC, many specific difficulties were encountered by patients such as the perception that glycemia fluctuates even with appropriate CC and that CC complicates the management of diabetes. A larger proportion of participants with a lower level of education (<university degree) and current or history of depression reported not feeling confident in applying CC. Most respondents believed that new technologies could facilitate CC (57%) and would be interested in such technology (62%).

CONCLUSIONS

Although a majority of participant reported being confident in applying CC, many difficulties and constraints associated with CC have been identified. These results highlight that patients with a lower level of education and with a history or current depression could benefit from specific CC education strategies. Future studies should examine the efficacy of technology tools to facilitate CC.

Mitigating Reductions in Glucose During Exercise on Closed-Loop Insulin Delivery: The Ex-Snacks Study

OBJECTIVE

To assess whether snacking could be used with closed-loop (CL) insulin delivery to avoid exercise-induced reductions in plasma glucose (PG), as well as elevations in PG at the end of exercise.

RESEARCH DESIGN AND METHODS

Twelve type 1 diabetes (T1D) subjects (age 13-36 years, duration 10.7 ± 8.4 years, A1c 7.4% ± 0.8% [57 ± 8.7 mmol/mol]) underwent two 105-min exercise studies while under CL control: CL alone and CL+snack. Exercise, commenced at 3 PM, consisted of four 15-min periods of brisk treadmill walking to 65%-70% HR_max (separated by three 5-min rest periods), followed by a 30-min recovery period. Fifteen to 30 g carbohydrate (Gatorade) was provided on snacking visits just before and midway through the exercise period. PG and insulin were measured every 15-20 min during the exercise studies.

RESULTS

Baseline PG levels were similar for CL alone (164 ± 16 mg/dL) versus CL+snack (172 ± 11 mg/dL). During exercise, PG levels fell by 53 ± 10 mg/dL without snacking versus a modest 10 ± 13 mg/dL increase in PG with snacking (P = 0.0005); similar differences in the change in PG levels were observed at the end of recovery period. Hypoglycemia requiring rescue treatment (PG ≤60 mg/dL) during exercise occurred in three nonsnacking visits versus none with snacking. During the 75-min exercise period, insulin delivered was 1.8 ± 0.4 U for the CL+snack admission compared to 0.7 ± 0.1 U during CL alone (P = 0.002).

CONCLUSION

These results support the use of a simple snacking strategy to avoid exercise-induced lowering of PG while on CL insulin delivery. Persistent insulin infusion during exercise with snacking also appears to be effective in limiting increases in PG at the end of exercise.

Knowledge of carbohydrate counting and insulin dose calculations in paediatric patients with type 1 diabetes mellitus

Background

Patients with type 1 diabetes mellitus (T1DM) who are able to adjust their insulin doses according to the carbohydrate content of a meal, as well as their blood glucose, are likely to have improved glycaemic control (Silverstein et al., 2005). With improved glycaemic control, patients have a lower risk of developing long-term microvascular complications associated with T1DM (Diabetes Control and Complications Trial Research Group, 1993).

To assess the carbohydrate and insulin knowledge of patients attending our paediatric diabetes clinic at the University Hospital Limerick (UHL), the validated PedCarbQuiz (PCQ) was applied to our clinic population.

Methods

This study was completed by applying a questionnaire called the PedCarbQuiz (PCQ) to children exclusively attending our paediatric diabetes clinic at UHL. Of the clinic's 220 patients, 81 participated in the study.

Results

The average total PCQ score (%) was higher in the continuous subcutaneous insulin infusion (CSII) group compared with the multiple daily insulin (MDI) injection user group (79.1 ± 12.1 versus 65.9 ± 6.6 p = 0.005). The CSII group also had a higher average carbohydrate score (%) compared with the MDI group (79.4 ± 12.4 versus 66.3 ± 16.2, p = 0.004).

Conclusions

This study demonstrates that in a representative Irish regional paediatric T1DM clinic, knowledge of carbohydrates and insulin is better among patients treated with CSII compared with MDI. However, knowledge in both groups is poorer than in the original US sample.

General significance

This study demonstrates that in a representative Irish regional paediatric T1DM clinic, knowledge of carbohydrates and insulin is poorer than in a US based sample, although this knowledge is better among patients treated with CSII compared with MDI. This highlights the need for improved resources for diabetes and carbohydrate counting education for patients with T1DM.

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All children with Type 1 diabetes mellitus, require dietetic input to optimize diabetes outcomes.

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In a unit without a dedicated paediatric diabetes dietitian, the knowledge of carbohydrate counting and insulin dosing is poor.

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In this study, this did not correlate statistically with HbA1c but this may be due to low patient numbers.

Glycaemic load versus carbohydrate counting for insulin bolus calculation in patients with type 1 diabetes on insulin pump

AIMS

To evaluate feasibility and effectiveness on short-term blood glucose control of using glycaemic load counting (GLC) versus carbohydrate counting (CC) for prandial insulin dosing in patients with type 1 diabetes (T1D).

METHODS

Nine T1D patients on insulin pump, aged 26-58 years, HbA1c 7.7 ± 0.8 % (61 ± 8.7 mmol/mol), participated in this real-life setting study. By a crossover design, patients were randomised to calculate their pre-meal insulin dose based on the insulin/glycaemic load ratio (GLC period) or the insulin/carbohydrate ratio (CC period) for 1 week, shifting to the alternate method for the next week, when participants duplicated their first week food plan. Over either week, a blind subcutaneous continuous glucose monitoring was performed, and a 7-day food record was filled in.

RESULTS

Total daily insulin doses (45 ± 10 vs. 44 ± 9 I.U.; M ± SD, p = 0.386) and basal infusion (26 ± 7 vs. 26 ± 8 I.U., p = 0.516) were not different during GLC and CC periods, respectively. However, the range of insulin doses (difference between highest and lowest insulin dose) was wider during GLC, with statistical significance at dinner (8.4 ± 6.2 vs. 6.0 ± 3.9 I.U., p = 0.041). Blood glucose iAUC after lunch was lower, albeit not significantly, during GLC than CC period (0.6 ± 8.6 vs. 3.4 ± 8.2 mmol/l∙3 h, p = 0.059). Postprandial glucose variability, evaluated as the maximal amplitude after meal (highest minus lowest glucose value), was significantly lower during GLC than CC period at lunch (4.22 ± 0.28 vs. 5.47 ± 0.39 mmol/l, p = 0.002) and dinner (3.89 ± 0.33 vs. 4.89 ± 0.33, p = 0.026).

CONCLUSIONS

Calculating prandial insulin bolus based on glycaemic load counting is feasible in a real-life setting and may improve postprandial glucose control in people with T1D.

Insulin therapy in type 1 diabetes

Although not curable, type 1 diabetes is eminently controllable. IIT, as guided by the results of landmark studies such as the DCCT, provides primary care providers with a blueprint for reducing the frequency of the devastating complications of diabetes that were all too common in the recent past. Considering the remarkable advances in contemporary therapy, including MDI and CSII, the likelihood of even greater future improvements in quality of life and survivability can be anticipated. Success requires patient engagement and education, an informed primary care provider, and an interdisciplinary team to maximize the benefits of insulin therapy and avoid the risks of hypoglycemia.

Assessment guidance of carbohydrate counting method in patients with type 2 diabetes mellitus

AIMS

We evaluated the application of the method of carbohydrate counting performed by 21 patients with type 2 diabetes, 1 year later attending a guidance course.

METHODS

Participants answered a questionnaire to assess patients' adhesion to carbohydrate counting as well as to identify habit changes and the method's applicability, and values of glycated hemoglobin were also analyzed.

RESULTS

Most participants (76%) were females, and 25% of them had obesity degree III. There was a statistically significant decrease in glycated hemoglobin from 8.42±0.02% to 7.66±0.01% comparing values before and after counseling. We observed that although patients stated that the method was difficult they understood that carbohydrate counting could allow them make choices and have more freedom in their meals; we also verified if they understood accurately how to replace some foods used regularly in their diets and most patients correctly chose replacements for the groups of bread (76%), beans (67%) and noodles (67%).

CONCLUSIONS

We concluded that participation in the course led to improved blood glucose control with a significant reduction of glycated hemoglobin, better understanding of food groups and the adoption of healthier eating habits.

Carbohydrate counting with an automated bolus calculator helps to improve glycaemic control in children with type 1 diabetes using multiple daily injection therapy: an 18-month observational study

AIMS

This study aimed to investigate the effect of carbohydrate counting (carbC), with or without an automated bolus calculator (ABC), in children with type 1 diabetes treated with multiple daily insulin injections.

METHODS

We evaluated 85 children, aged 9-16 years, with type 1 diabetes, divided into four groups: controls (n=23), experienced carbC (n=19), experienced carbC+ABC (n=18) and non-experienced carbC+ABC (n=25). Glycated haemoglobin (HbA1c), insulin use, and glycaemic variability - evaluated as high blood glucose index (HBGI) and low blood glucose index (LBGI) - were assessed at baseline and after 6 and 18 months.

RESULTS

At baseline, age, disease duration, BMI, HbA1c, insulin use, and HBGI (but not LBGI; p=0.020) were similar for all groups. After 6 months, HbA1c improved from baseline, although not significantly - patients using ABC (according to manufacturer's recommendations) HbA1c 7.14 ± 0.41% at 6 months vs. 7.35 ± 0.53% at baseline, (p=0.136) or without carbC experience HbA1c 7.61±0.62% vs. 7.95 ± 0.99% (p=0.063). Patients using ABC had a better HBGI (p=0.001) and a slightly worse LBGI (p=0.010) than those not using ABC. ABC settings were then personalised. At 18 months, further improvements in HbA1c were seen in children using the ABC, especially in the non-experienced carbC group (-0.42% from baseline; p=0.018).

CONCLUSIONS

CarbC helped to improve glycaemic control in children with type 1 diabetes using multiple daily injections. ABC use led to greater improvements in HbA1c, HBGI and LBGI compared with patients using only carbC, regardless of experience with carbC.