Prudence E. Lopez

Aim: To determine the glycaemic impact of an increased insulin dose, split insulin dose and regular insulin for a high fat, high protein breakfast in people with type 1 diabetes using multiple daily injections (≥4/day).Methods: In this cross‐over trial, participants received the same high fat, high protein breakfast (carbohydrate:30 g, fat:40 g, protein:50 g) for 4 days. Four different insulin strategies were randomly allocated and tested; 100% of the insulin‐to‐carbohydrate ratio (ICR) given in a single dose using aspart insulin (100Asp), 125% ICR given in a single dose using aspart (125Asp) or regular insulin (125Reg) and 125% ICR given in a split dose using aspart insulin (100:25Asp). Insulin was given 0.25 hr pre‐meal and for 100:25Asp, also 1 hr post‐meal. Postprandial sensor glucose was measured for 5 hr.Results: In all, 24 children and adults were participated. The 5‐hr incremental area under the curves for 100Asp, 125Asp, 125Reg and 100:25Asp were 620 mmol/L.min [95% CI: 451,788], 341 mmol/L.min [169,512], 675 mmol/L.min [504,847] and 434 mmol/L.min [259,608], respectively. The 5‐hr incremental area under the curve for 125Asp was significantly lower than for 100Asp (p = 0.016) and for 125Reg (p = 0.002). There was one episode of hypoglycaemia in 125Reg.Conclusions: For a high fat, high protein breakfast, giving 125% ICR preprandially, using aspart insulin significantly improved postprandial glycaemia without hypoglycaemia. There was no additional glycaemic benefit from giving insulin in a split dose (100:25%) or replacing aspart with regular insulin.

Aims: To determine if the frequency of severe diabetic ketoacidosis at presentation of new‐onset type 1 diabetes to an Australian tertiary centre increased during the initial period of restrictions resulting from the COVID‐19 pandemic (March to May 2020).Methods: Data were collected on presentations of newly diagnosed type 1 diabetes as well as on all paediatric presentations to the emergency department of a tertiary centre between 2015 and 2020. Data from the period of initial COVID restrictions in Australia (March to May 2020) were compared to the period March to May of the previous 5 years (pre‐pandemic periods).Results: The number of new diagnoses of type 1 diabetes was comparable in the pandemic period and pre‐pandemic periods (11 in 2020 vs range 6–10 in 2015–2019). The frequency of severe diabetic ketoacidosis was significantly higher in the pandemic period compared to the pre‐pandemic periods (45% vs 5%; P P <0.007), odds ratio 7.5 (95% CI 1.7, 33.5). None of the individuals tested positive for COVID‐19. Presentations of people aged <18 years to the emergency department decreased by 27% in the pandemic period compared to the average of the pre‐pandemic periods (4799 vs 6550; range 6268 to 7131).Conclusions: A significant increase in the frequency of severe diabetic ketoacidosis at presentation of type 1 diabetes was observed during the initial period of COVID‐19 restrictions. We hypothesize that concern about presenting to hospital during a pandemic led to a delay in diagnosis. These data have important implications for advocacy of seeking healthcare for non‐pandemic‐related conditions during a global pandemic.

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.

Aim: To compare systematically the impact of two novel insulin‐dosing algorithms (the Pankowska Equation and the Food Insulin Index) with carbohydrate counting on postprandial glucose excursions following a high fat and a high protein meal.Methods: A randomized, crossover trial at two Paediatric Diabetes centres was conducted. On each day, participants consumed a high protein or high fat meal with similar carbohydrate amounts. Insulin was delivered according to carbohydrate counting, the Pankowska Equation or the Food Insulin Index. Subjects fasted for 5 h following the test meal and physical activity was standardized. Postprandial glycaemia was measured for 300 min using continuous glucose monitoring.Results: 33 children participated in the study. When compared to carbohydrate counting, the Pankowska Equation resulted in lower glycaemic excursion for 90–240 min after the high protein meal (p < 0.05) and lower peak glycaemic excursion (p < 0.05). The risk of hypoglycaemia was significantly lower for carbohydrate counting and the Food Insulin Index compared to the Pankowska Equation (OR 0.76 carbohydrate counting vs. the Pankowska Equation and 0.81 the Food Insulin Index vs. the Pankowska Equation). There was no significant difference in glycaemic excursions when carbohydrate counting was compared to the Food Insulin Index.Conclusion: The Pankowska Equation resulted in reduced postprandial hyperglycaemia at the expense of an increase in hypoglycaemia. There were no significant differences when carbohydrate counting was compared to the Food Insulin Index. Further research is required to optimize prandial insulin dosing.

Background Young children with type 1 diabetes (T1D) present unique challenges for intensive diabetes management. We describe an intensive diabetes program adapted for young children and compare glycemic control, anthropometry, dietary practices and insulin regimens before and after implementation. Methods Cross sectional data from children with T1D aged ≥0.5 to 1c (HbA_1c); severe hypoglycemia episodes; body mass index standard deviation scores (BMI‐SDS); diabetes ketoacidosis (DKA) episodes; and insulin regimen—twice daily injections, multiple daily injections, or continuous subcutaneous insulin infusion. Results Mean HbA_1c declined by 12 mmol/mol over the study period (P < .01). The proportion of children achieving a mean HbA_1c < 58 mmol/mol increased significantly from 31% in 2004 to 64% in 2010 (P < .01), and from 64% in 2010 to 83% in 2016 (P = .04). The mean BMI‐SDS was significantly lower in 2010 when compared with 2004 (P<.01); however, this trend plateaued between 2010 and 2016 (P = .97). Severe hypoglycemia and DKA occurred infrequently. The prevalence of overweight or obesity increased from 2010 to 2016 (P = .03). Conclusions The JHCH intensive diabetes management program has resulted in 83% of young children in 2016 achieving target glycemia without an increase in severe hypoglycemia or DKA. Overweight remains a challenge in this population warranting action to reduce weight and protect these children from future obesity‐related health risks.

Aims: To determine the optimum combination bolus split to maintain postprandial glycaemia with a high‐fat and high‐protein meal in young people with Type 1 diabetes.Methods: A total of 19 young people (mean age 12.9 ± 6.7 years) participated in a randomized, repeated‐measures trial comparing postprandial glycaemic control across six study conditions after a high‐fat and high‐protein meal. A standard bolus and five different combination boluses were delivered over 2 h in the following splits: 70/30 = 70% standard /30% extended bolus; 60/40=60% standard/40% extended bolus; 50/50=50% standard/50% extended bolus; 40/60=40% standard/60% extended bolus; and 30/70=30% standard/70% extended bolus. Insulin dose was determined using the participant's optimized insulin:carbohydrate ratio. Continuous glucose monitoring was used to assess glucose excursions for 6 h after the test meal.Results: Standard bolus and combination boluses 70/30 and 60/40 controlled the glucose excursion up to 120 min. From 240 to 300 min after the meal, the glucose area under the curve was significantly lower for combination bolus 30/70 compared with standard bolus (P=0.004).Conclusions: High‐fat and high‐protein meals require a ≥60% insulin:carbohydrate ratio as a standard bolus to control the initial postprandial rise. Additional insulin at an insulin:carbohydrate ratio of up to 70% is needed in the extended bolus for a high fat and protein meal to prevent delayed hyperglycaemia.