Correlation between amount of carbohydrate in mixed meals and insulin delivery by artificial pancreas in seven IDDM subjects

Postprandial glucose metabolism in children and adolescents with type 1 diabetes mellitus: potential targets for improvement

The main goal of therapeutic management of type 1 Diabetes Mellitus (T1DM) is to maintain optimal glycemic control to prevent acute and long-term diabetes complications and to enable a good quality of life. Postprandial glycemia makes a substantial contribution to overall glycemic control and variability in diabetes and, despite technological advancements in insulin treatments, optimal postprandial glycemia is difficult to achieve. Several factors influence postprandial blood glucose levels in children and adolescents with T1DM, including nutritional habits and adjustment of insulin doses according to meal composition. Additionally, hormone secretion, enteroendocrine axis dysfunction, altered gastrointestinal digestion and absorption, and physical activity play important roles. Meal-time routines, intake of appropriate ratios of macronutrients, and correct adjustment of the insulin dose for the meal composition have positive impacts on postprandial glycemic variability and long-term cardiometabolic health of the individual with T1DM. Further knowledge in the field is necessary for management of all these factors to be part of routine pediatric diabetes education and clinical practice. Thus, the aim of this report is to review the main factors that influence postprandial blood glucose levels and metabolism, focusing on macronutrients and other nutritional and lifestyle factors, to suggest potential targets for improving postprandial glycemia in the management of children and adolescents with T1DM.

The relationship between meal carbohydrate quantity and the insulin to carbohydrate ratio required to maintain glycaemia is non-linear in young people with type 1 diabetes: A randomized crossover trial

OBJECTIVE

To determine if the relationship between meal carbohydrate quantity and the insulin to carbohydrate ratio (ICR) required to maintain glycaemia is linear in people with type 1 diabetes.

METHODS

We used an open labelled randomized four-arm cross-over study design. Participants (N = 31) aged 12-27 years, HbA1c ≤ 64 mmol/mol (8.0%) received insulin doses based on the individual's ICR and the study breakfast carbohydrate quantity and then consumed four breakfasts containing 20, 50, 100 and 150 g of carbohydrate over four consecutive days in randomized order. The breakfast fat and protein percentages were standardized. Postprandial glycaemia was assessed by 5 h continuous glucose monitoring. The primary outcome was percent time in range (TIR) and secondary outcomes included hypoglycaemia, glucose excursion and incremental area under the curve. Statistical analysis included linear mixed modelling and Wilcoxon signed rank tests.

RESULTS

The 20 g carbohydrate breakfast had the largest proportion of TIR (0.74 ± 0.29 p < 0.04). Hypoglycaemia was more frequent in the 50 g (n = 13, 42%) and 100 g (n = 15, 50%) breakfasts compared to the 20 g (n = 6, 20%) and 150 g (n = 7, 26%) breakfasts (p < 0.029). The 150 g breakfast glucose excursion pattern was different from the smaller breakfasts with the lowest glucose excursion 0-2 h and the highest excursion from 3.5 to 5 h.

CONCLUSIONS

A non-linear relationship between insulin requirement and breakfast carbohydrate content was observed, suggesting that strengthened ICRs are needed for meals with ≤20 and ≥150 g of carbohydrate. Meals with ≥150 g of carbohydrate may benefit from dual wave bolusing.

Carbohydrate restriction for diabetes: rediscovering centuries-old wisdom

Carbohydrate restriction, used since the 1700s to prolong survival in people with diabetes, fell out of favor after the discovery of insulin. Despite costly pharmacological and technological developments in the last few decades, current therapies do not achieve optimal outcomes, and most people with diabetes remain at high risk for micro- and macrovascular complications. Recently, low-carbohydrate diets have regained popularity, with preliminary evidence of benefit for body weight, postprandial hyperglycemia, hyperinsulinemia, and other cardiometabolic risk factors in type 2 diabetes and, with more limited data, in type 1 diabetes. High-quality, long-term trials are needed to assess safety concerns and determine whether this old dietary approach might help people with diabetes attain clinical targets more effectively, and at a lower cost, than conventional treatment.

Factors Beyond Carbohydrate to Consider When Determining Meantime Insulin Doses: Protein, Fat, Timing, and Technology

For many years, carbohydrate counting has been a popular strategy for determining mealtime insulin doses for people with diabetes who are on a multiple daily injection regimen or continuous subcutaneous insulin infusion. This approach assumes that only carbohydrate-containing foods and beverages affect postprandial glucose levels. However, many studies have indicated that the fat and protein content of a meal can play an important role in delaying postprandial hyperglycemia and should be considered when trying to optimize postprandial glucose levels. This article reviews research on making insulin dose adjustments for high-fat and high-protein meals, as well as the timing of mealtime insulin doses.

Analyzing the Potential of Advanced Insulin Dosing Strategies in Patients With Type 2 Diabetes: Results From a Hybrid In Silico Study

BACKGROUND

The ongoing improvement of continuous glucose monitoring (CGM) sensors and of insulin pumps are paving the way for a fast implementation of artificial pancreas (AP) for type 1 diabetes (T1D) patients. The case for type 2 diabetes (T2D) patients is less obvious since usually some residual beta cell function allows for simpler therapy approaches, and even multiple daily injections (MDI) therapy is not very widespread. However, the number of insulin dependent T2D patients is vastly increasing and therefore a need for understanding chances and challenges of an automated insulin therapy arises. Based on this background, this article analyzes conditions under which the use of more advanced therapeutic approaches, particularly AP, could bring a substantial improvement and should be considered as a viable therapy option.

METHOD

Data of 14 insulin-treated T2D patients on MDI wearing a CGM device and deviation analysis methods were used to estimate the expected improvements in the clinical outcome by using self-monitoring of blood glucose (SMBG) with advanced carbohydrate counting, a full AP or intermediate approaches, either CGM measurements with MDI therapy or SMBG with insulin pump. HbA1C and time in range (70-140 mg/dl, 70-180 mg/dl, respectively) were used as a performance measure. Outcome measures beyond glycemic control (eg, compliance, patient acceptance) have not been analyzed in this study.

RESULTS

AP has the potential to improve the condition of many poorly controlled insulin-treated T2D patients. However, as the interpatient variability is much higher than in T1D, a prescreening is recommended to select suitable patients.

CONCLUSIONS

Clinical criteria need to be developed for inclusion/exclusion of T2D patients for AP related therapies.

Carbohydrate Counting in Children and Adolescents with Type 1 Diabetes

Carbohydrate counting (CC) is a meal-planning tool for patients with type 1 diabetes (T1D) treated with a basal bolus insulin regimen by means of multiple daily injections or continuous subcutaneous insulin infusion. It is based on an awareness of foods that contain carbohydrates and their effect on blood glucose. The bolus insulin dose needed is obtained from the total amount of carbohydrates consumed at each meal and the insulin-to-carbohydrate ratio. Evidence suggests that CC may have positive effects on metabolic control and on reducing glycosylated haemoglobin concentration (HbA1c). Moreover, CC might reduce the frequency of hypoglycaemia. In addition, with CC the flexibility of meals and snacks allows children and teenagers to manage their T1D more effectively within their own lifestyles. CC and the bolus calculator can have possible beneficial effects in improving post-meal glucose, with a higher percentage of values within the target. Moreover, CC might be integrated with the counting of fat and protein to more accurately calculate the insulin bolus. In conclusion, in children and adolescents with T1D, CC may have a positive effect on metabolic control, might reduce hypoglycaemia events, improves quality of life, and seems to do so without influencing body mass index; however, more high-quality clinical trials are needed to confirm this positive impact.

The relationship between carbohydrate and the mealtime insulin dose in type 1 diabetes

A primary focus of the nutritional management of type 1 diabetes has been on matching prandial insulin therapy with carbohydrate amount consumed. Different methods exist to quantify carbohydrate including counting in one gram increments, 10g portions or 15g exchanges. Clinicians have assumed that counting in one gram increments is necessary to precisely dose insulin and optimize postprandial control. Carbohydrate estimations in portions or exchanges have been thought of as inadequate because they may result in less precise matching of insulin dose to carbohydrate amount. However, studies examining the impact of errors in carbohydrate quantification on postprandial glycemia challenge this commonly held view. In addition it has been found that a single mealtime bolus of insulin can cover a range of carbohydrate intake without deterioration in postprandial control. Furthermore, limitations exist in the accuracy of the nutrition information panel on a food label. This article reviews the relationship between carbohydrate quantity and insulin dose, highlighting limitations in the evidence for a linear association. These insights have significant implications for patient education and mealtime insulin dose calculations.

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.

The Role of Dietary Protein and Fat in Glycaemic Control in Type 1 Diabetes: Implications for Intensive Diabetes Management

A primary focus of the management of type 1 diabetes has been on matching prandial insulin therapy with carbohydrate amount consumed. However, even with the introduction of more flexible intensive insulin regimes, people with type 1 diabetes still struggle to achieve optimal glycaemic control. More recently, dietary fat and protein have been recognised as having a significant impact on postprandial blood glucose levels. Fat and protein independently increase the postprandial glucose excursions and together their effect is additive. This article reviews how the fat and protein in a meal impact the postprandial glycaemic response and discusses practical approaches to managing this in clinical practice. These insights have significant implications for patient education, mealtime insulin dose calculations and dosing strategies.

Toward a more standardised and accurate evaluation of glycemic response to foods: recommendations for portion size calculation

This study aimed at evaluating the adequacy of calculation methods for portions to be provided to subjects in clinical trials evaluating glycemic response to foods. Portion sizes were calculated for 140 food samples, based on Nutrition Facts labels (current practice) and actual available carbohydrate content (current recommendation), and compared against the amount of monosaccharides yielded by the digestive breakdown of their actual available carbohydrate content (basis for glycemic response to food). The current practice can result in significant under- or over-feeding of carbohydrates in 10% of tested cases, as compared to the targeted reference dosage. The method currently recommended can result in significantly inadequate yields of monosaccharides in 24% of tested cases. The current and recommended calculation methods do not seem adequate for a standardised evaluation of glycemic response to foods. It is thus recommended to account for the amount of absorbable monosaccharides of foods for portion size calculation.

Efficacy of carbohydrate counting in type 1 diabetes: a systematic review and meta-analysis

BACKGROUND

Although carbohydrate counting is the recommended dietary strategy for achieving glycaemic control in people with type 1 diabetes, the advice is based on narrative review and grading of the available evidence. We aimed to assess by systematic review and meta-analysis the efficacy of carbohydrate counting on glycaemic control in adults and children with type 1 diabetes.

METHODS

We screened and assessed randomised controlled trials of interventions longer than 3 months that compared carbohydrate counting with general or alternate dietary advice in adults and children with type 1 diabetes. Change in glycated haemoglobin (HbA1c) concentration was the primary outcome. The results of clinically and statistically homogenous studies were pooled and meta-analysed using the random-effects model to provide estimates of the efficacy of carbohydrate counting.

FINDINGS

We identified seven eligible trials, of 311 potentially relevant studies, comprising 599 adults and 104 children with type 1 diabetes. Study quality score averaged 7·6 out of 13. Overall there was no significant improvement in HbA1c concentration with carbohydrate counting versus the control or usual care (-0·35% [-3·9 mmol/mol], 95% CI -0·75 to 0·06; p=0·096). We identified significant heterogeneity between studies, which was potentially related to differences in study design. In the five studies in adults with a parallel design, there was a 0·64% point (7·0 mmol/mol) reduction in HbA1c with carbohydrate counting versus control (95% CI -0·91 to -0·37; p<0·0001).

INTERPRETATION

There is some evidence to support the recommendation of carbohydrate counting over alternate advice or usual care in adults with type 1 diabetes. Additional studies are needed to support promotion of carbohydrate counting over other methods of matching insulin dose to food intake.

FUNDING

None.

Continuous glucose monitoring-guided insulin dosing in pump-treated patients with type 1 diabetes: a clinical guide

This article describes our methods for structured continuous glucose monitoring (CGM)-guided insulin dosing in pump-treated type 1 diabetes. Some of the methods have been reported and some are based on clinical experience. It is expected that this guide will help those involved in the care of such patients and who have experience with CGM to achieve better glucose control in their patients. More research needs to be done on insulin dosing and we hope that this article will also encourage others to pursue this field. This is a guide and, as such, is not meant to replace clinical judgment. Also, these dosing approaches apply only to those patients on pump therapy. They do not necessarily carry over to those patients treated with basal analog insulin.

Effects of carbohydrate counting on glucose control and quality of life over 24 weeks in adult patients with type 1 diabetes on continuous subcutaneous insulin infusion: a randomized, prospective clinical trial (GIOCAR)

OBJECTIVE

Few studies have assessed the efficacy of carbohydrate counting in type 1 diabetes, and none have validated its efficacy in patients who are treated with continuous subcutaneous insulin infusion (CSII). The aim of our study was to test the effect of carbohydrate counting on glycemic control and quality of life in adult patients with type 1 diabetes who are receiving CSII.

RESEARCH DESIGN AND METHODS

Sixty-one adult patients with type 1 diabetes treated with CSII were randomly assigned to either learning carbohydrate counting (intervention) or estimating pre-meal insulin dose in the usual empirical way (control). At baseline and 12 and 24 weeks, we measured HbA(1c), fasting plasma glucose, BMI, waist circumference, recorded daily insulin dose, and capillary glucose data, and administered the Diabetes-Specific Quality-of-Life Scale (DSQOLS) questionnaire.

RESULTS

Intention-to-treat analysis showed improvement of the DSQOLS score related to diet restrictions (week 24 - baseline difference, P = 0.008) and reduction of BMI (P = 0.003) and waist circumference (P = 0.002) in the intervention group compared with control subjects. No changes in HbA(1c), fasting plasma glucose, daily insulin dose, and hypoglycemic episodes (<2.8 mmol/L) were observed. Per-protocol analysis, including only patients who continuously used carbohydrate counting and CSII during the study, confirmed improvement of the DSQOLS score and reduction of BMI and waist circumference, and showed a significant reduction of HbA(1c) (-0.35% vs. control subjects, P = 0.05).

CONCLUSIONS

Among adult patients with type 1 diabetes treated with CSII, carbohydrate counting is safe and improves quality of life, reduces BMI and waist circumference, and, in per-protocol analysis, reduces HbA(1c).

Contemporary management of patients with type 1 diabetes

The current standard of care for patients with type 1 diabetes (T1D) employs a system of intensive diabetes management aimed at near-normal glycemia, which reduces the risk of micro- and macrovascular complications. Optimal management is an ongoing process based on a patient-centered collaboration with a primary care clinician and a multidisciplinary diabetes team that provides diabetes management, including education and psychosocial support. Intensive diabetes therapy attempts to mimic physiologic insulin replacement. Over the past 15 years, there has been widespread use of multiple-dose insulin regimens using a variety of insulin analogs, administered either by injection or insulin pump therapy, together with medical nutrition therapy, frequent self-monitoring of blood glucose and, more recently, continuous logo glucose monitoring. It is now possible to achieve previously unattainable levels of glycemic control with less risk of severe hypoglycemia, and yet only a minority of patients achieves target hemoglobin A1c values. This review discusses contemporary management of T1D with a focus on health outcomes.

Real-life application and validation of flexible intensive insulin-therapy algorithms in type 1 diabetes patients

AIMS

Flexible intensive insulin therapy (FIT) has become the reference standard in type 1 diabetes. Besides carbohydrate counting (CHO), it requires the use of algorithms to adjust prandial insulin doses to the number of CHO portions. As recourse to standard algorithms is usual when initiating FIT, the use of personalized algorithms would also allow more precise adjustments to be made. The aim of the present study was to validate personalized prandial algorithms for FIT as proposed by Howorka et al. in 1990.

METHODS

We conducted a 4-month observational study of 35 patients with type 1 diabetes, treated with FIT for at least 6 months, who were already using Howorka's prandial algorithms (meal-related and correctional insulin doses for blood glucose increases induced by CHO). These patients were asked to use a personal digital assistant (PDA) phone with an electronic diary (instead of a paper one) to take advantage of the computerized data-collection system to assess the quality of postprandial metabolic control.

RESULTS

Whatever the number of CHO portions, mean postprandial blood glucose values remained close to the target of 7.8mmol/L, and the compensatory algorithm allowed precise correction of preprandial hyperglycaemia. In fact, the algorithms for meal-related and correctional insulin doses at the end of the study did not differ significantly from those initially calculated, but they generally differed from one patient to another.

CONCLUSION

In type 1 diabetic patients treated with FIT, the use of individualized parameters permits fast and accurate adjustment of mealtime insulin doses, leading to good control of the postprandial state.

Children and adolescents on intensive insulin therapy maintain postprandial glycaemic control without precise carbohydrate counting

AIMS

Carbohydrate (CHO) quantification is used to adjust pre-meal insulin in intensive insulin regimens. However, the precision in CHO quantification required to maintain postprandial glycaemic control is unknown. We determined the effect of a +/-10-g variation in CHO amount, with an individually calculated insulin dose for 60 g CHO, on postprandial glycaemic control.

METHODS

Thirty-one children and adolescents (age range 9.5-16.8 years), 17 using continuous subcutaneous insulin infusion (CSII) and 14 using multiple daily injections (MDI), participated. Each subject consumed test lunches of equal macronutrient content, differing only in carbohydrate quantity (50, 60, 70 g CHO), in random order on three consecutive days. For each participant, the insulin dose was the same for each meal, based on their usual insulin : CHO ratio for 60 g CHO. Activity was standardized. Continuous glucose monitoring was used.

RESULTS

The CSII and MDI subjects demonstrated no difference in postprandial blood glucose levels (BGLs) for comparable carbohydrate loads (P > 0.05). The 10-g variations in CHO quantity resulted in no differences in BGLs or area under the glucose curves for 2.5 h (P > 0.05). Hypoglycaemic episodes were not significantly different (P = 0.32). The 70-g meal produced higher glucose excursions after 2.5 h, with a maximum difference of 1.9 mmol/l at 3 h (P = 0.01), but the BGLs remained within international postprandial targets.

CONCLUSIONS

In patients using intensive insulin therapy, an individually calculated insulin dose for 60 g of carbohydrate maintains postprandial BGLs for meals containing between 50 and 70 g of carbohydrate. A single mealtime insulin dose will cover a range in carbohydrate amounts without deterioration in postprandial control.

The importance of carbohydrate counting in the treatment of children with diabetes

Carbohydrate (Carb) counting is a meal planning approach for patients with diabetes mellitus that focuses on carbohydrate as the primary nutrient affecting postprandial glycemic response. The concept of carb counting is not new. In the early 1990's the Diabetes Control and Complications Trial (DCCT) used carb counting as one of its education tools. More recently, short acting insulin analogues and insulin pumps have made the role of carb counting important and popular. Carb counting can be used in conjunction with a meal plan to set carbohydrate targets at each meal and snack. It is also used, perhaps more commonly, to estimate carbohydrate intake and adjust insulin around mixed meals and snacks using insulin to carbohydrate ratio. This effectively addresses the variable eating habits of most children and adolescents. The method may be adapted for patients who use a conventional insulin regimen and may meet the needs of patients who use multiple daily injections (MDI) or an insulin pump. Carb counting can make food planning flexible and enjoyable for patients, and the meal planning approach is very important for the physical growth and psychological development of children with diabetes. This paper describes the importance of carb counting for childhood diabetes as well as some of the special aspects associated with it.

Characteristics of basal insulin requirements by age and gender in Type-1 diabetes patients using insulin pump therapy

Establishment of appropriate basal insulin levels is an essential component of intensive insulin therapy. While the existence of a "dawn phenomenon" is widely recognized, the present study sought to establish whether diurnal basal insulin patterns exist in Type-1 diabetes, and whether these patterns vary by age and gender. Participant data was drawn from 322 Type-1 insulin pump users treated at a private diabetes education practice in suburban Philadelphia. All participants completed a battery of fasting tests designed to match basal insulin levels to endogenous glucose production and insulin sensitivity. Analysis of resultant basal patterns revealed significant differences between juvenile (age < or =20) and adult (age >20) basal insulin patterns. The younger group exhibited a more pronounced and sustained night-time peak; the older group exhibiting a briefer and less pronounced early-morning peak. Lower overall basal insulin requirements were found in the youngest (age < or =10) and oldest (age >60) groups. No noteworthy gender differences were found. Results can serve as a guide for clinicians when initiating and fine-tuning patients who utilize basal/bolus insulin therapy.

Intensive treatment of type 1 diabetes

There have been amazing advances for the treatment of type 1 diabetes. As clinicians proceed into the twenty-first century, it is appropriate to reflect both about accomplishments and about the prospects of improved therapeutic options. Regarding the former, perhaps no advance can be compared to the discovery of insulin. Since then, the improvements in therapy have appeared to be too slow for physicians, patients, and their families. In actuality, over the past 20 years, the pace for the development of new tools for the treatment of this once fatal disease has been remarkable. The treatment of type 1 diabetes has evolved with advances in the treatment of microvascular, neuropathic, and macrovascular complications. The future is even more promising, with the possibility of even preventing the disease before the development of hyperglycemia. The challenge for the present is teaching all individuals involved with the management of patients with type 1 diabetes to manage the condition as effectively as possible.

Use of carbohydrate counting for meal planning in type I diabetes

Certain questions often arise regarding carbohydrate counting, such as: Why use carbohydrate counting? Where does one start? How much carbohydrate is prescribed? How does one balance the diet? How is carbohydrate counting taught to patients? Which patients are the best candidates for carbohydrate counting? This article provides possible answers to these questions based on clinical experience at the Vanderbilt University Medical Center Diabetes Research and Training Center, and the Diabetes Control and Complications Trial.

Nutrition interventions for intensive therapy in the Diabetes Control and Complications Trial. The DCCT Research Group

As part of an intensive treatment regimen that had as its goal achieving and maintaining blood glucose levels in the normal range in individuals with insulin-dependent diabetes mellitus, dietitians in the Diabetes Control and Complications Trial implemented varying nutrition intervention strategies to counsel patients to attain normoglycemia. Dietary management encompassed recommendations on altering insulin dosages for varying food intake. Nutrition intervention was tailored to best meet a participant's life-style, motivation, ability to grasp information, diet history, and specific intensive insulin therapy. Dietitians were integral participants in the team management of individuals in the intensive treatment group. Selected nutrition interventions--Healthy Food Choices, exchange systems, carbohydrate counting, and total available glucose--and behavior management approaches were coupled with intensive insulin therapy. Case presentations illustrate each nutrition intervention in the attainment of normoglycemia.

Insulin requirement of simple and complex carbohydrate foods in type 1 (insulin-dependent) CSII-treated diabetic subjects, obtained by biostator. Correlation with glycaemic index

The aim of this work was to observe whether different types of carbohydrates might require different insulin doses. Five type 1 CSII-treated diabetic subjects (age 39 +/- 4 years), C-peptide negative and in optimal metabolic control (HbA1c 7.5 +/- 0.2) were selected for the study. They were connected to the Biostator 6 times with an interval of 4-10 days between sessions and fed a meal containing 75 g of carbohydrates of different types: bread, pasta, potatoes, apples, oranges and sucrose. The following net (above basal) insulin requirement for the 30 meals were found (IU - mean + SD): bread 9.15 +/- 1.97; pasta 6.00 +/- 1.37; potatoes 7.05 +/- 2.58; apples 4.54 +/- 1.42; oranges 6.21 +/- 2.62; sucrose 7.83 +/- 2.33. A statistically significant difference was found by ANOVA among insulin requirements for foods (p less than 0.05). Single comparisons between bread and the other foods showed a statistically significant difference only between bread and apple (p less than 0.05). Mean coefficient of variation was 33.9% for the subjects and 30.7% for the meals. A significant correlation was found between Jenkins' glycaemic index and insulin requirement (r = 0.897; p less than 0.001). In conclusion, the high intraindividual variability of insulin requirement does not advice the use of the glycaemic index during optimized insulin therapy.