The additional dose of insulin for high-protein mixed meal provides better glycemic control in children with type 1 diabetes on insulin pumps: randomized cross-over study

Dietary recommendations for people with diabetes in special situations: a position statement report by Arabic Association for the Study of Diabetes and metabolism (AASD)

BACKGROUND

Diabetes is a significant global health concern. Regional factors play a crucial role in determining the appropriate diet for patients.

MAIN BODY

The Arabic Association for the Study of Diabetes and Metabolism has developed a position statement that addresses the dietary needs of patients in the context of low income and cultural dietary habits. This statement aims to explore the most suitable diet for Middle East and North Africa (MENA) region and provide guidance for physicians to overcome barriers in optimal care. While most dietary guidelines focus on uncomplicated diabetes, it's essential to recognize that diabetes often coexists with other common diseases in our region.

CONCLUSION

International guidelines cannot be directly applied to the Egypt and Arab countries due to cultural and dietary differences. Our position statement shares valuable insights into managing diabetes in special situations and diverse clinical settings within this region. These recommendations are flexible, considering personal, cultural, and traditional differences.

Macronutrient Intake in Children and Adolescents with Type 1 Diabetes and Its Association with Glycemic Outcomes

Aims

This study aimed to identify the quantity and range of protein, fat, and carbohydrate consumed in meals and snacks in children with Type 1 diabetes (T1D), and to explore associations between the variability in fat and protein intakes with the glycemic outcomes.

Methods

This was a cross-sectional dietary study of children 6-18 years attending pediatric diabetes service in Australia. Three-day weighed food records were analyzed for the macronutrient intake. Impacts of dietary intake on glycemic outcomes were explored.

Results

Forty-eight children (63% male) aged 11.7 ± 2.9 (mean ± SD) with HbA1c 6.7 ± 1.1% (mmol/mol), BMI Z-score 0.51 ± 0.83, and daily insulin dose 0.99 units/kg completed 3-day weighed food records. Mean intakes at breakfast were 47-g carbohydrate, 15-g protein, and 12-g fat. Lunch: 49-g carbohydrate, 19-g protein, and 19-g fat. Dinner: 57-g carbohydrate, 33-g protein, and 26-g fat. Fifty-five percent (n = 80) of the dinner meals met criteria for a high-fat, high-protein (HFHP) meal. In a subset (n = 16) of participants, exploratory analysis indicated a trend of reduced %TIR (58%) in the 8 hr following HFHP dinner, compared to %TIR (74%) following non-HFHP dinner (p=0.05). Seventy-eight percent of the participants aged 12-18 years intake at dinner varied by more than 20-g fat or more than 25-g protein. There was no association between the variability in fat and protein intake at dinner with HbA1c. Saturated fat contributed to 14.7% (±3.0) of participants energy intake.

Conclusions

Children with T1D frequently consume quantities of fat and protein at dinner that have been shown to cause delayed postprandial hyperglycemia. HFHP dinners were associated with the reduced %TIR over 8 hr, presenting an opportunity for insulin-dose adjustments. Future research that explores the meal dietary variability with postprandial glycemia in this population is needed. Excessive intake of the saturated fat highlights the need for dietary interventions to reduce CVD risk. This trial is registered with ACTRN12622000002785.

Splitting Mealtime Insulin Doses for Mixed Fat and Protein Meals in Children and Adolescents with Type 1 Diabetes Using Multiple Daily Injection Regimen: A Randomized Cross-Over Trial

Aims

Assessment of the glycemic outcomes of increasing and splitting mealtime insulin doses for mixed fat and protein meals in pediatric patients with type 1 diabetes mellitus (T1DM) using multiple daily injection regimen and comparing the effects of regular insulin and fast-acting insulin on glycemic outcomes following those meals.

Methods

This single-center, randomized, cross-over trial included 43 children and adolescents with T1DM randomly assigned to receive three interventional insulin doses for lunch meals over 3 consecutive days; Intervention A (100% insulin-to-carbohydrate ratio (ICR) dose given as premeal insulin lispro with an additional insulin sensitivity factor-calculated correction dose after 3 hr), Intervention B (130% ICR dose split into 60% premeal insulin lispro and 40% postmeal insulin lispro after 30 min), and Intervention C (130% ICR dose split into 60% premeal insulin lispro and 40% postmeal regular insulin after 30 min). The test meal consisted of two slices of pizza (weight: 150 g, carbohydrates: 40 g, fat: 15 g, protein: 20 g, and calories: 380 kcal). Postprandial blood glucose levels were monitored for 6 hr.

Results

There were no significant differences in postprandial blood glucose excursions following the three interventions. However, Intervention C had a significantly lower late (3-6 hr) blood glucose area under the curve (p=0.01). Postprandial hypoglycemia developed in 12 participants (27.9%) following Interventions A and B and in 17 participants (39.5%) following Intervention C (p=0.32).

Conclusions

Using regular insulin as a postmeal portion of increased and split insulin doses provided better late postprandial glycemic outcomes following mixed fat and protein meals. However, the amount of additional insulin used needs optimization to reduce the frequency of postprandial hypoglycemia. This trial is registered with NCT04783376.

Novel Modified Algorithm for High Fat/High Energy Density Meal in Type 1 Diabetes: Less Hypoglycemia

OBJECTIVE

This aim of this study was to investigate the effect of additional insulin dosing for high fat/high energy density mixed meal over 12 hours.

METHODS

In this single-center, non-blinded, randomized, cross-over study, a high fat/high energy density test meal was used to study the impact on glycemic response of either carbohydrate counting (CC) on the first day and the Pańkowska algorithm (PA) on the second test day. The two methods were compared in 20 adolescents with type 1 diabetes (T1D), aged 9-18 years, using insulin pump therapy and continuous glucose monitoring on postprandial early (0-120 min), late (120-720 min), and total (0-720 min) glycemic response.

RESULTS

There was no difference between groups in the duration of normoglycemia in the early period. Postprandially, 50% of patients developed hypoglycemia using the PA at a median of 6.3 (5.6-7.9) hours and the PA was subsequently modified for the remaining ten patients. Area under the curve (AUC) for the early period decreased non-significantly in the CC group, indicating less normoglycemia. No significant difference was found in the AUC of the PA (no hypoglycemia n=4) and modified PA groups (no hypoglycemia n=6) over the whole period (0-12 hours). AUC for level 2 hyperglycemia was statistically greater in the PA-no hypoglycemia patients compared to modified PA-no hypoglycemia patients.

CONCLUSION

There were inter-individual differences in glycemic response to high fat/high energy density meals. An individualized approach to insulin dosing by evaluating food diary and postprandial glucose monitoring appears to be optimal for children and adolescents with T1D.

A new proposal for a second insulin bolus to optimize postprandial glucose profile in adolescents with type 1 diabetes

AIMS

To evaluate whether a second insulin bolus, calculated with a new approach, could improve postprandial glucose (PPG) after the intake of real-life high-fat (HF) and high-protein (HP) mixed meals.

METHODS

Fifteen adolescents with T1D treated with non-automated insulin pumps and CGM were enrolled. Patients received standard, HF and HP mixed meals treated with one pre-meal insulin bolus; based on differences in PPG between standard, HF and HP meals, correction boluses were calculated (30% and 60% of pre-meal bolus for HF and HP meals, respectively). Then patients received the same HF or HP meal treated with pre-meal bolus plus second insulin bolus after 3 h. Differences between postprandial variables after HF and HP meals treated with one or two insulin boluses were assessed by paired Student's t-test.

RESULTS

Treating HF and HP meals with two insulin boluses significantly reduced the postprandial BG-AUC (21% and 26% respectively, p < 0.05), increased %TIR (from 52.5 to 78.3% for HF meal; from 32.7 to 57.1% for HP meal; p < 0.01), and reduced mean BG and %TAR (p < 0.01), with no differences in %TBR.

CONCLUSIONS

The new way to calculate and administer correction boluses 3 h after HF and HP meals is effective and safe in reducing PPG and the hypoglycemia risk.

Pure-protein load for children with type 1 diabetes: is any additional insulin needed? A randomized controlled study

AIMS

Study in adults with T1D showed that delivery of insulin for pure-protein meals may not be obligatory. The aim of this study was to assess the effects of whey isolate protein drink consisting of 50 g/200 kcal from pure protein on postprandial glycemia (PPG) following with square-wave insulin bolus in comparison with no insulin strategy in T1D children on insulin pumps.

METHODS

This was a randomized, double-blind, cross-over study including 58 children with mean: age 14.62 ± 3.64 years. Participants were randomly assigned into two treatment orders: NB-SQ (no bolus on the first day) and SQ-NB (square-bolus on the first day). The primary outcome was PPG during a 5-h follow-up. The secondary outcome was the frequency of hypoglycemia and glycemic variability parameters.

RESULTS

PPG [mg/dl] since 150 min of the follow-up was significantly lower when square-wave bolus was delivered (group SQ vs NB); at 150, 180, 210, 240, 270, 300 min: 130.6 versus 154.5 (p = 0.009), 153.4 versus 124.9 (p = 0.004), 151.0 versus 118.7 (p = 0.003), 146.4 versus 114.2 (p = 0.002), 141.2 versus 107.7 (p = 0.001), 131.0 versus 105.1 (p = 0.005). We observed statistically significant difference in overall rate of hypoglycemia < 70 mg/dl between groups SQ versus NB: 6.8% versus 2.5% (p = 0.001). The overall rate of hypoglycemia below 54 mg/dl was < 1% (p = 0.452).

CONCLUSIONS

A meal containing 50 g of pure protein may be consumed without additional insulin dose. An additional square-wave bolus may be beneficial in reducing PPG. To avoid hypoglycemia, lower insulin dose should be calculated for 100 kcal from protein than for individual insulin-to-carb ratio.

Decreased Need for Correction Boluses with Universal Utilisation of Dual-Wave Boluses in Children with Type 1 Diabetes

Insulin pumps offer standard (SB), square and dual-wave boluses (DWB). Few recommendations exist on how to use these dosing options. Several studies suggest that the DWB is more effective for high-fat or high-carbohydrate meals. Our objective was to test whether time in range (TIR) improves in children with type 1 diabetes (T1D) using the universal utilization of the dual-wave boluses for all evening meals regardless of the composition of the meal. This was a 28-day long prospective randomized open-label single-center crossover study. Twenty-eight children with T1DM using a Medtronic 640G pump and continuous glucose monitoring system were randomly assigned to receive either DWB or SB for all meals starting from 6:00 p.m. based solely on the food carbohydrate count. DWB was set for 50/50% with the second part extended over 2 h. After two weeks patients switched into the alternative treatment arm. TIR (3.9−10 mmol/L), time below range (TBR) (<3.9 mmol/L) and time above range (TAR) (>10 mmol/L) and sensor glucose values were measured and compared between the groups. Twenty-four children aged 7−14 years completed the study according to the study protocol. There were no statistically significant differences in mean TIR (60.9% vs. 58.8%; p = 0.3), TBR (1.6% vs. 1.7%; p = 0.7) or TAR (37.5 vs. 39%; p = 0.5) between DWB and SB groups, respectively. Subjects in the DWB treatment arm administered significantly less correction boluses between 6 p.m. and 6 a.m. compared to those in the SB group (1.2 ± 0.8 vs. 1.7 ± 0.8, respectively; p < 0.01). DWB for evening meals in which insulin is calculated solely on the food carbohydrate content did not improve TIR compared to standard bolus in children with T1D. However, DWB enabled to use significantly less correction boluses to achieve euglycemia by the morning compared to the SB.

The Role of Protein and Fat Intake on Insulin Therapy in Glycaemic Control of Paediatric Type 1 Diabetes: A Systematic Review and Research Gaps

Carbohydrate counting (CHC) is the established form of calculating bolus insulin for meals in children with type 1 diabetes (T1DM). With the widespread use of continuous glucose monitoring (CGM) observation time has become gapless. Recently, the impact of fat, protein and not only carbohydrates on prolonged postprandial hyperglycaemia have become more evident to patients and health-care professionals alike. However, there is no unified recommendation on how to calculate and best administer additional bolus insulin for these two macronutrients. The aim of this review is to investigate: the scientific evidence of how dietary fat and protein influence postprandial glucose levels; current recommendations on the adjustment of bolus insulin; and algorithms for insulin application in children with T1DM. A PubMed search for all articles addressing the role of fat and protein in paediatric (sub-)populations (<18 years old) and a mixed age population (paediatric and adult) with T1DM published in the last 10 years was performed. Conclusion: Only a small number of studies with a very low number of participants and high degree of heterogeneity was identified. While all studies concluded that additional bolus insulin for (high) fat and (high) protein is necessary, no consensus on when dietary fat and/or protein should be taken into calculation and no unified algorithm for insulin therapy in this context exists. A prolonged postprandial observation time is necessary to improve individual metabolic control. Further studies focusing on a stratified paediatric population to create a safe and effective algorithm, taking fat and protein into account, are necessary.

Additional Insulin Is Required in Both the Early and Late Postprandial Periods for Meals High in Protein and Fat: A Randomized Trial

CONTEXT

The pattern and quantity of insulin required for high-protein high-fat (HPHF) meals is not well understood.

OBJECTIVE

This study aimed to determine the amount and delivery pattern of insulin required to maintain euglycemia for 5 hours after consuming a HPHF meal compared with a low-protein low-fat (LPLF) meal.

METHODS

This randomized crossover clinical trial, conducted at 2 Australian pediatric diabetes centers, included 10 patients (12-21 years of age) with type 1 diabetes for ≥ 1 year. Participants were randomized to HPHF meal (60 g protein, 40 g fat) or LPLF meal (5 g protein, 5 g fat) with identical carbohydrate content (30 g). A modified insulin clamp technique was used to determine insulin requirements to maintain postprandial euglycemia for 5 hours. Total mean insulin requirements over 5 hours were measured.

RESULTS

The total mean insulin requirements for the HPHF meal were significantly greater than for the LPLF meal (11.0 [CI 9.2, 12.8] units vs 5.7 [CI 3.8, 7.5] units; P = 0.001). Extra intravenous insulin was required for HPHF: 0 to 2 hours (extra 1.2 [CI 0.6, 1.6] units/h), 2 to 4 hours (extra 1.1 [CI 0.6, 1.6] units/h), and 4 to 5 hours (extra 0.6 [CI 0.1, 1.1] units/h) after the meal. There were marked inter-individual differences in the quantity of additional insulin (0.3 to 5 times more for HPHF) and the pattern of insulin delivery (0%-85% of additional insulin required in the first 2 hours).

CONCLUSION

The addition of protein and fat to a standardized carbohydrate meal almost doubled the mean insulin requirement, with most participants requiring half of the additional insulin in the first 2 hours.

Impact of Fat Intake on Blood Glucose Control and Cardiovascular Risk Factors in Children and Adolescents with Type 1 Diabetes

Nutrition therapy is a cornerstone of type 1 diabetes (T1D) management. Glycemic control is affected by diet composition, which can contribute to the development of diabetes complications. However, the specific role of macronutrients is still debated, particularly fat intake. This review aims at assessing the relationship between fat intake and glycemic control, cardiovascular risk factors, inflammation, and microbiota, in children and adolescents with T1D. High fat meals are followed by delayed and prolonged hyperglycemia and higher glycated hemoglobin A1c levels have been frequently reported in individuals with T1D consuming high amounts of fat. High fat intake has also been associated with increased cardiovascular risk, which is higher in people with diabetes than in healthy subjects. Finally, high fat meals lead to postprandial pro-inflammatory responses through different mechanisms, including gut microbiota modifications. Different fatty acids were proposed to have a specific role in metabolic regulation, however, further investigation is still necessary. In conclusion, available evidence suggests that a high fat intake should be avoided by children and adolescents with T1D, who should be encouraged to adhere to a healthy and balanced diet, as suggested by ISPAD and ADA recommendations. This nutritional choice might be beneficial for reducing cardiovascular risk and inflammation.

Insulin pump dosing strategies for meals varying in fat, protein or glycaemic index or grazing-style meals in type 1 diabetes: A systematic review

BACKGROUND

Nutritional composition and food patterns influence postprandial glycaemia in type 1 diabetes (T1D). For optimal glycaemic control, insulin dose and delivery pattern must be matched accordingly. This systematic review aimed to compare insulin dosing strategies for meals varying in fat, protein and glycaemic index (GI), and prolonged meals in T1D.

METHODS

Studies in adults and/or children with T1D on insulin pump therapy comparing the glycaemic effects of different insulin pump bolus types for these meal types were identified from biomedical databases (MEDLINE, PREMEDLINE, Embase, CINAHL and Cochrane Central Register of Controlled Trials; March 1995-April 2020) and systematically reviewed.

RESULTS

All eleven publications investigating high-fat meals (234 participants) and all seven studies investigating high-protein meals (129 participants) showed a dual-wave bolus was superior. Additional insulin further improved postprandial glycaemia, although increasing risk of hypoglycaemia in 5 of 14 studies. One study investigating GI found a dual-wave bolus reduced postprandial glycaemia and risk of hypoglycaemia. No studies were identified for grazing/degustation-style meals. Due to heterogeneity, meta-analysis was not possible.

CONCLUSION

Dual-wave boluses improve postprandial glycaemia in high-fat, high-protein and low-GI meals. Further research is needed to identify optimal bolus delivery split, duration and optimal total dose adjustment.

High-protein meals require 30% additional insulin to prevent delayed postprandial hyperglycaemia

AIM

To determine the amount of additional insulin required for a high-protein meal to prevent postprandial hyperglycaemia in individuals with type 1 diabetes using insulin pump therapy.

METHODS

In this randomized cross-over study, 26 participants aged 8-40 years, HbA_1c < 65 mmol/mol (8.1%), received a 50 g protein, 30 g carbohydrate, low-fat (< 1 g) breakfast drink over five consecutive days at home. A standard insulin dose (100%) was compared with additional doses of 115, 130, 145 and 160% for the protein, in randomized order. Doses were commenced 15-min pre-drink and delivered over 3 h using a combination bolus with 65% of the standard dose given up front. Postprandial glycaemia was assessed by 4 h of continuous glucose monitoring.

RESULTS

The 100% dosing resulted in postprandial hyperglycaemia. From 120 min, ≥ 130% doses resulted in significantly lower postprandial glycaemic excursions compared with 100% (P < 0.05). A 130% dose produced a mean (sd) glycaemic excursion that was 4.69 (2.42) mmol/l lower than control, returning to baseline by 4 h (P < 0.001). From 120 min, there was a significant increase in the risk of hypoglycaemia compared with control for 145% [odds ratio (OR) 25.4, 95% confidence interval (CI) 5.5-206; P < 0.001) and 160% (OR 103, 95% CI 19.2-993; P < 0.001). Some 81% (n = 21) of participants experienced hypoglycaemia following a 160% dose, whereas 58% (n = 15) experienced hypoglycaemia following a 145% dose. There were no hypoglycaemic events reported with 130%.

CONCLUSIONS

The addition of 30% more insulin to a standard dose for a high-protein meal, delivered using a combination bolus, improves postprandial glycaemia without increasing the risk of hypoglycaemia.

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.

Impact of dietary protein on postprandial glycaemic control and insulin requirements in Type 1 diabetes: a systematic review

AIM

Postprandial hyperglycaemia is a challenge for people living with Type 1 diabetes. In addition to carbohydrate, dietary protein has been shown to contribute to postprandial glycaemic excursions with recommendations to consider protein when calculating mealtime insulin doses. The aim of this review is to identify and synthesize evidence about the glycaemic impact of dietary protein and insulin requirements for individuals with Type 1 diabetes.

METHODS

A systematic literature search of relevant biomedical databases was performed to identify research on the glycaemic impact of dietary protein when consumed alone, and in combination with other macronutrients in individuals with Type 1 diabetes.

RESULTS

The review included 14 published studies dated from 1992 to 2018, and included studies that researched the impact of protein alone (n = 2) and protein in a mixed meal (n = 12). When protein was consumed alone a glycaemic effect was not seen until ≥ 75 g. In a carbohydrate-containing meal ≥ 12.5 g of protein impacted the postprandial glucose. Inclusion of fat in a high-protein meal enhanced the glycaemic response and further increased insulin requirements. The timing of the glycaemic effect from dietary protein ranged from 90 to 240 min. Studies indicate that the postprandial glycaemic response and insulin requirements for protein are different when protein is consumed alone or with carbohydrate and/or fat.

CONCLUSIONS

This systematic review provides evidence that dietary protein contributes to postprandial glycaemic excursions and insulin requirements. These insights have important implications for the education of people with Type 1 diabetes and highlights the need for more effective insulin dosing strategies for mixed macronutrient meals.

Postprandial Glucose Control in Type 1 Diabetes: Importance of the Gastric Emptying Rate

The achievement of optimal post-prandial (PP) glucose control in patients with type 1 diabetes (T1DM) remains a great challenge. This review summarizes the main factors contributing to PP glucose response and discusses the likely reasons why PP glucose control is rarely achieved in T1DM patients. The macronutrient composition of the meal, the rate of gastric emptying and premeal insulin administration are key factors affecting the PP glucose response in T1DM. Although the use of continuous insulin infusion systems has improved PP glucose control compared to conventional insulin therapy, there is still need for further ameliorations. T1DM patients frequently present a delayed gastric emptying (GE) that produces a lower but more prolonged PP hyperglycemia. In addition, delayed GE is associated with a longer time to reach the glycemic peak, with a consequent mismatch between PP glucose elevation and the timing of premeal insulin action. On this basis, including GE time and meal composition in the algorithms for insulin bolus calculation of the insulin delivery systems could be an important step forward for optimization of PP glucose control in T1DM.