Mitigation Strategies for a Missed Meal Bolus in People with Type 1 Diabetes Using the Minimed™ 780G System.

Background: A missed or late meal insulin bolus can impact glycemia in type 1 diabetes (T1D). Aim: To study glucose control after missed and late meal boluses in T1D adults using a prototype enhanced hybrid closed-loop (E-HCL) system (Medtronic) providing automated basal insulin and correction boluses. Methods: Twelve T1D adults (median HbA1c 6.8% [IQR 6.2-7.2] | 51mmol/mol [44-55] participated. After 1-week run-in at home in Open Loop, E-HCL was activated during 1-week supervised hotel phase followed by 3 weeks free-living at-home. Participants consumed a standardized 40g carbohydrate dinner in the supervised phase. Four hours of post-prandial glucose data following a standard bolus pre-meal in E-HCL at home were compared in a pairwise manner to 1) Pre-meal bolus in Open Loop Run-In; 2) 20minute Late bolus in E-HCL supervised; 3) Missed bolus in E-HCL supervised using Wilcoxon Signed-Rank Test. Results: Late bolus was associated with mild hypoglycemia and higher glucose variability; missed bolus was associated with hyperglycemia (Table). Overall time in CL was 99.98%. E-HCL at home vs. Open Loop (run-in) had greater time-in-70-180mg/dL range (85.3 vs. 75.0%, p=0.003). There was no severe hypoglycemia or ketoacidosis. Conclusions: While glucose excursions were modest, the administration and timing of meal boluses influenced post-meal glycemia in well-controlled T1D adults using E-HCL. Disclosure M.H. Lee: Research Support; Self; Medtronic. Speaker's Bureau; Self; AstraZeneca. S. Vogrin: None. B. Paldus: Other Relationship; Self; Australian Diabetes Society, JDRF, Medtronic. H. Jones: None. V.R. Obeyesekere: None. C.M. Sims: Stock/Shareholder; Self; Medtronic. S.A. Wyatt: Other Relationship; Self; Animas Corporation, Medtronic. G.M. Ward: None. S.A. McAuley: Research Support; Self; JDRF, Medtronic. Speaker's Bureau; Self; Australian Diabetes Society, Eli Lilly and Company. R. MacIsaac: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Novo Nordisk Inc. Speaker's Bureau; Self; AstraZeneca, Novo Nordisk Inc. Other Relationship; Self; AstraZeneca, Novo Nordisk Inc. B. Krishnamurthy: None. V. Sundararajan: None. A. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker's Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc. D.N. O'Neal: None.

Closing the loop

Possible Ways to Improve Postprandial Glucose Control in Type 1 Diabetes.

Introduction and Objective: Fat and protein content of meals impact PPG excursion in individuals with Type 1 Diabetes (T1D). PPG management can be even more challenging in an FCL system with no premeal boluses. We explored how meal composition may impact glycemic outcomes when managing insulin in FCL. Methods: Thirty-four participants in 3 cohorts (adults, young adults, adolescents) with T1D (14-53 years old, 62% female, HbA1c 8.0±1.1%) tested the University of Virginia neural network-based system (AIDANET) during a five-day FCL study in supervised settings. Study staff recorded each meal's carbohydrate, protein, and fat content using food labels. Linear regression was used to determine the association between meal composition and PPG (4 hours following a meal) CGM metrics, adjusting for gender and age. Results: Overall, 301 meals were included in the analysis. The average carbohydrate, fat, and protein contents of the meals were 63.9 ± 34.8, 32.4 ± 23.3, and 32.6 ±17.5 grams, respectively. Unsurprisingly, larger carbohydrate amounts were associated with larger PPG excursions. There was no association between fat and protein content and the 4-hour incremental area under the curves (AUC). However, the protein content significantly reduced the AUC during the second hour after meal onset (Coefficient -45.53 mg/dl*min, p-value <0.002). AUC during the third and fourth hours after meal onset was significantly increased by fat content (Coefficient 32.57, 44.21, and p-values < 0.018 and 0.002, respectively). Fat also increased time to peak (Coefficient 0.57, p-value <0.003), while protein decreased peak PPG (Coefficient -0.66, p-value < 0.008). Time in range improved with more protein (Coefficient 0.003, p-value<0.025). However, time in tight range was not impacted by fat or protein. Conclusion: Meal composition significantly impacts FCL PPG profiles, and automatically accounting for its effects may further improve glycemic outcomes. Disclosure L. Ekhlaspour: Other Relationship; Medtronic. Advisory Panel; Abbott, Medtronic. Consultant; Jaeb Center for Health Research. Research Support; MannKind Corporation. Speaker's Bureau; Insulet Corporation. Advisory Panel; Sequel Med Tech. Other Relationship; Tandem Diabetes Care, Inc. Research Support; Abbott. Other Relationship; Sanofi. J.Y. Hosseinipour: None. A. Narayan: None. Z.D. Perez: None. V. Holmes: None. M.D. Breton: Speaker's Bureau; Sinocare Inc, Tandem Diabetes Care, Inc. Consultant; Roche Diabetes Care, Boydsense. S.A. Brown: Research Support; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc, Tolerion, Roche Diabetes Care. Other Relationship; MannKind Corporation. G.P. Forlenza: Advisory Panel; Medtronic. Research Support; Medtronic, Dexcom, Inc. Consultant; Dexcom, Inc. Research Support; Insulet Corporation. Consultant; Insulet Corporation. Research Support; Tandem Diabetes Care, Inc. Advisory Panel; Tandem Diabetes Care, Inc. Research Support; Abbott. Advisory Panel; Sequel Med Tech. E. Cengiz: Advisory Panel; Novo Nordisk, Arecor Therapeutics, Eli Lilly and Company, Tandem Diabetes Care, Inc, Portal Insulin, MannKind Corporation. Funding Breakthrough T1D

Introduction and Objective: Diabetes management and outcomes often differ by sex, influenced by biological and psychobehavioral factors. Our objective was to examine sex differences in glycemic outcomes during the safety and feasibility testing of the AIDANET automated insulin delivery system (AID) Methods: Participants with T1D enrolled in a randomized crossover trial of usual care (overwhelmingly AID with meal bolus, UC) vs the AIDANET system in FCL (without premeal boluses). FCL management consisted of a supervised phase followed by a week of home use. Glycemic metrics for FCL home use compared to UC were analyzed by sex subgroups considering males (M) and females of reproductive age not using contraception (FRA) Results: Of the 34 participants completing the trial, 12 were M and 10 FRA. For M, FCL showed significant improvements in TAR, TAR250 and mean glucose (UC: 185±29.1 mg/dL, FCL:169.2±17.3 mg/dL, p=0.046); and non-inferiority for TIR, TTR 70-140mg/dL (p=0.014) and TBR54. For FRA, FCL showed non-inferiority on mean glucose (UC: 184.3±42.9 mg/dL, FCL:161±14.6 mg/dL, p=0.031), TTR (p=0.030), TAR250 and TBR54; and increased TBR. Conclusion: AIDANET in FCL improved glycemia in males without compromising it in females, while eliminating the need for manual meal boluses. Glycemia could be improved for females with T1D by devising innovative FCL systems that account for the sex differences. Disclosure M. Moscoso-Vasquez: Other Relationship; Dexcom, Inc. Research Support; Tandem Diabetes Care, Inc, National Institute of Diabetes and Digestive and Kidney Diseases. J.Y. Hosseinipour: None. D. Flanagan: None. D. Fulkerson: None. S.A. Brown: Research Support; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc, Tolerion, Roche Diabetes Care. Other Relationship; MannKind Corporation. L. Ekhlaspour: Other Relationship; Medtronic. Advisory Panel; Abbott, Medtronic. Consultant; Jaeb Center for Health Research. Research Support; MannKind Corporation. Speaker's Bureau; Insulet Corporation. Advisory Panel; Sequel Med Tech. Other Relationship; Tandem Diabetes Care, Inc. Research Support; Abbott. Other Relationship; Sanofi. G.P. Forlenza: Advisory Panel; Medtronic. Research Support; Medtronic, Dexcom, Inc. Consultant; Dexcom, Inc. Research Support; Insulet Corporation. Consultant; Insulet Corporation. Research Support; Tandem Diabetes Care, Inc. Advisory Panel; Tandem Diabetes Care, Inc. Research Support; Abbott. Advisory Panel; Sequel Med Tech. M.D. Breton: Speaker's Bureau; Sinocare Inc, Tandem Diabetes Care, Inc. Consultant; Roche Diabetes Care, Boydsense. E. Cengiz: Advisory Panel; Novo Nordisk, Arecor Therapeutics, Eli Lilly and Company, Tandem Diabetes Care, Inc, Portal Insulin, MannKind Corporation. Funding Breakthrough T1D (2-SRA-2023-1275-M-B)

Background: Forgetting a premeal bolus can lead to hyperglycemia in patients with type 1 diabetes (T1D). A prototype e-HCL system was designed to automatically deliver basal insulin and correction boluses based on sensor glucose (SG) values. The effect of the system on hyperglycemia due to unannounced medium-sized meals was assessed. Methods: Twelve subjects with T1D aged 15-25 years (median 17 years) underwent a 1-week hotel phase of e-HCL Auto Mode use, followed by a 3-week unsupervised at-home phase of use. On the third day of the hotel phase, a ∼40gm-carbohydrate (carb) dinner was consumed without a premeal bolus. Five hours of postprandial data were analyzed and compared to data captured after 40gm-carb meals eaten during the at-home phase, but accompanied by a premeal bolus. Results: Meals without a premeal bolus resulted in postprandial SG levels statistically similar to those observed for meals accompanied by a premeal bolus (Table). Conclusion: These data suggest that e-HCL can handle unannounced medium-sized meals to a similar extent as meals of equal size accompanied by premeal boluses. This may improve overall glycemic control of patients who underestimate or frequently forget to administer premeal boluses. Disclosure A. Roy: Employee; Self; Medtronic MiniMed, Inc. B. Grosman: Employee; Self; Medtronic. N. Parikh: None. D. Wu: None. L.J. Lintereur: Employee; Self; Medtronic MiniMed, Inc. N. Kurtz: Employee; Self; Medtronic MiniMed, Inc. F.R. Kaufman: Employee; Self; Medtronic.

Advances in diabetes technology have transformed the treatment paradigm for T1D, yet the burden of the disease remains significant. The pediatric population poses unique challenges to glucose management with unpredictable exercise and food consumption. The Omnipod 5 System is a novel hybrid closed-loop (HCL) system with fully on-body operation. A tubeless insulin pump (pod) containing a personalized Model Predictive Control algorithm communicates directly with a Dexcom G6 continuous glucose monitor (CGM, or sensor) to automate insulin delivery. Therapy customization is enabled through glucose targets from 110–150 mg/dL, adjustable by time of day, which is a critical component to individualize glucose management in children. We report on the first, pivotal outpatient safety evaluation of the Omnipod 5 System in a large cohort of children with T1D.Participants aged 6–13.9y with T1D≥6 months and A1C<10% used the HCL system for 3 months at home after a 14-day run-in phase of their standard therapy (ST, included both pump therapy and multiple daily injections). The primary safety and effectiveness endpoints, respectively, were occurrence of severe hypoglycemia (SH) and diabetic ketoacidosis (DKA), and change in A1C and sensor glucose percent time in target range (TIR) (70–180 mg/dL) during HCL compared with ST.Participants (N=112) were aged (mean±SD) 10.3±2.2y with T1D duration 4.7±2.6y and baseline A1C 7.7±0.9% (range 5.8–10.3%). TIR increased significantly from ST to HCL, from 52.5±15.6% to 68.0±8.1% (p<0.0001), corresponding to an additional 3.7 hours/day in target range. A1C at end of study was reduced by 0.7% to 7.0±0.6% (p<0.0001). Percentages of time in hyperglycemia were reduced: >180 mg/dL from 45.3±16.7% to 30.2±8.7% and ≥250 mg/dL from 19.1±13.1% to 9.6±5.4% (both p<0.0001). Percentages of time in hypoglycemia remained low from ST to HCL: <54 mg/dL from 0.4±0.8% to 0.3±0.3% and <70 mg/dL from 2.2±2.7% to 1.8±1.4% (both p>0.05). Mean glucose decreased from 183±32 to 160±15 mg/dL (p<0.0001). During the HCL phase there was 1 episode of SH (delayed eating after pre-meal bolus) and 1 episode of DKA (suspected infusion site failure) reported. Virtually all participants completing the pivotal study (99%) continued system use during an extension phase.In this multi-center pivotal study in a large cohort of children with T1D, the Omnipod 5 System was safe and effective when used for 3 months at home. There were significant improvements in both TIR and A1C, while time below range (<70 mg/dL) remained low. The beneficial glycemic outcomes are critical for children, given that neurologic outcomes can be negatively impacted by hyperglycemia. The current results and commitment to the extension phase emphasize the safe and effective use of the HCL system, as well as the preference for the Omnipod 5 System over participants’ previous therapy.

Type 1 Diabetes in Children and Adolescents.

There is a clear unmet need in people living with type 1 diabetes (T1D). Although the quality of life of people with T1D has improved, issues like hypoglycemia, weight gain and variability in glucose profiles remain. In this review, the clinical efficacy and safety of empagliflozin, a sodium-glucose cotransporter type 2 (SGLT2) inhibitor in T1D, is described based on a review of phase 2 and 3 studies to date. Empagliflozin and SGLT2 inhibitors, in general, are effective glucose-lowering drugs, which also work in people with T1D. Recent phase II and III studies, including the EASE trials for empagliflozin, showed a clear beneficial effect on HbA1c, body weight, glucose variability and total daily insulin use in people with T1D. No increase in hypoglycemia risk, in particular severe hypoglycemia, was observed, but genital infections were more prevalent. The use of SGLT2 inhibitors comes with a decrease in insulin doses, making individuals more prone to diabetic ketoacidosis (DKA). The uniqueness of the EASE program is that here, a very low dose of empagliflozin was used, with less, but still present, effects on metabolic outcomes, but interestingly a lower risk of DKA. Importantly, even in the higher doses of empagliflozin, it is clear that the overall risk for DKA remains low, most likely by educating patients and caretakers intensively on this subject. In conclusion, evidence is building on the potential of using empagliflozin, like other SGLT2 inhibitors, in T1D. However, to date, the use of empagliflozin is not approved in people with T1D. Clinicians will have to weigh the potential short- and long-term benefits of these adjunct therapies versus the potential acute side effects, in particular, the small but real risk of DKA in the individual T1D patient.

Real-world data of 12-month adjunct sodium-glucose co-transporter-2 inhibitor treatment in type 1 diabetes from the German/Austrian DPV registry: Improved HbA1c without diabetic ketoacidosis.

To evaluate the long-term effectiveness and safety of the AndroidAPS (AAPS) system in adults with type 1 diabetes (T1D) under real-world clinical conditions. This retrospective, single-center study included 27 adults with T1D (mean age 39 ± 9.6 years; 55.6% women; diabetes duration 21.5 ± 11.3 years) who initiated AAPS and were followed for 12 months. Glycemic metrics were obtained from real-time continuous glucose monitoring (rtCGM) data. Primary outcomes were changes in time in range (TIR; 70-180 mg/dL) and HbA1c. Secondary outcomes included time in tight range (TITR; 70-140 mg/dL), time below range (TBR), coefficient of variation (CV), and the glycemic risk index (GRI). Safety outcomes included severe hypoglycemia and diabetic ketoacidosis (DKA). TIR increased from 67.8% at baseline to 84.1% at 6 months and 79.9% at 12 months (P < 0.001). HbA1c decreased from 6.6% to 6.1% and 6.0%, respectively. TITR improved by 14.8% at 6 months and 10.6% at 12 months, while GRI decreased from 40.2 to 21.3. Over 88% of participants achieved TIR > 70% and CV < 36% at both follow-ups, and up to 74% achieved TITR > 50% at 6 months, remaining at 63% at 12 months. No episodes of severe hypoglycemia or DKA were reported. AAPS demonstrated sustained long-term effectiveness and safety in adults with T1D under real-world clinical practice conditions. Glycemic outcomes were comparable to those reported with commercially available closed-loop automated insulin delivery systems, supporting AAPS as a viable and effective advanced management option for T1D.

Background: Late-meal blousing increases the risk of hyperglycemia following a meal using meter blood glucose data. We used data from the Donors to the Tidepool Big Data Donation project to evaluate real-life bolusing and glycemic excursions using continuous glucose monitoring (CGM). Methods: We analyzed 214,087 meal boluses from 120 subjects, mean age 22 years (range 3-66), average CGM glucose 155mg/dL (range 103-239 mg/dL). We screened for meals meeting the following criteria: carbs of ≥20g, premeal glucose between 70 and 200mg/dL, no glucose &amp;lt;70mg/dL in the hour prior to bolus, no other insulin bolus 2 hours prior and 4 hours post bolus, 95% of CGM readings available 30 min before and 4 hour after the meal bolus. A pre-meal bolus was defined by the glucose rising &amp;lt;0.4mg/dL/min and a late meal boluses by a glucose rise of ≥1mg/dL/min in the 20 minutes prior to the bolus. Results: The post meal bolus had significantly higher CGM glucose levels at the time of bolus (p&amp;lt;0.001), and a significantly higher post prandial peak glucose (p&amp;lt;0.001). There was no statistical difference in the average amount of meal carbs for the two groups. Conclusions: Using integrated pump and CGM data from a large data base, late meal bolusing occurred with 12% of selected meal boluses and was associated with higher CGM values at the time of bolus, and higher peak post prandial CGM values. Disclosure L.M. Norlander: None. E.T. Nykaza: None. B. Arbiter: Employee; Self; Tidepool Project. Stock/Shareholder; Self; Abbott Laboratories, Dexcom, Inc. B.A. Buckingham: Advisory Panel; Self; ConvaTec Inc., Novo Nordisk Inc., Profusa, Inc. Consultant; Self; Medtronic MiniMed, Inc. Research Support; Self; Beta Bionics, ConvaTec Inc., Dexcom, Inc., Insulet Corporation, Medtronic MiniMed, Inc., Tandem Diabetes Care. Other Relationship; Self; Insulet Corporation, Tandem Diabetes Care. R. Lal: Consultant; Self; Abbott.

Background and Aims: Timely and accurate mealtime insulin dosing is an ongoing challenge for people with type 1 diabetes (T1D). This multinational study aimed to assess attitudes, behaviours and the overall impact of pre-meal (15-20 minutes) bolus insulin dosing from the perspective of adults with T1D, parents of children with T1D and physicians.Materials and Methods: Online surveys were conducted in 2711 participants (recruited from an online panel) who chose to take part across USA, Canada, UK, Japan, Spain and France between 25 Nov 2019 and 06 Feb 2020. Participants were 1401 adults aged ≥18 with T1D, 350 parents who live with children with T1D aged ≤15 years and 960 physicians who have practised for 4-40 years. Adults/children had T1D for ≥6 months and were taking a bolus insulin (excluding fast-acting insulinaspart). Physicians were responsible for starting or managing treatment for T1D and the prescription of mealtime insulin. This analysis provides a country average assuming equal sizes for each country, to give an overall indication of results across the six countries in the study.Results: Of the surveyed adults with T1D (46% male; mean age was 43 years; mean of 19 years with T1D), 72% administered their bolus insulin by injection and 28% used an insulin pump. Continuous glucose monitoring (CGM) was used by 43% of adults. Of the parents surveyed (64% male; mean age was 10 years; mean of 4 years with T1D), 74% administered their bolus insulin by injection and 26% used an insulin pump, with 58% using CGM. The findings indicate that a majority (96%) of both adults with T1D and parents of children with T1D understood the importance of administering bolus insulin accurately. However, few adults (35%) and parents (47%) felt very confident in estimating the amount of insulin required accurately and 91% of adults and 96% of parents experienced challenge(s) with pre-meal insulin dosing. Almost all physicians (99.6%) reported that they believed their patients with T1D faced challenge(s) with pre-meal bolus insulin dosing. Of those surveyed, 25% of adults and 38% of parents forgot to administer pre-meal insulin ≥1 a week, and 70%of adults and 81%of parents reported that they/their child ate more or less than anticipated following their mealtime insulin ≥1 aweek. Accordingly, 68% of adults and 79% of parents indicated that they/their child needed to take corrective action ≥1 a week by either eating more or taking more insulin. A majority of participants (82% of adults, 93% of parents) felt that administering insulin 15-20 minutes before a meal had a negative impact on their/their child's day-to-day life; 91% of physicians concurred that this creates an extra burden in the day-to-day lives of people with T1D. When asked their preference, 73%of adults and 67% of parents preferred bolus insulin administration either immediately before (42% adults, 44% parents) or after (31% adults, 23% parents) a meal. A high proportion of adults with T1D (67%) and parents (72%) claimed that taking bolus insulin immediately before or after a meal would have a positive impact on their overall quality of life.Conclusion: Based on the study findings, although the importance of accurate mealtime dosing was well recognized, bolus insulin dosing still poses clear challenges to most people with T1D. Given the choice, the majority of participants would prefer to administer insulin immediately prior to or following a meal, as this was perceived to improve quality of life.

AimsTo use electronic health record data from real‐world clinical practice to assess demographics, clinical characteristics and disease burden of adults with type 1 diabetes (T1D) in the United States.Materials and methodsRetrospective observational study of adults with T1D for ≥24 months at their first visit with a T1D diagnosis code (“index date”) between July 2014 and June 2016 in the Optum Humedica database. Demographic characteristics, acute complications (severe hypoglycaemia [SH], diabetic ketoacidosis [DKA]), microvascular complications, cardiovascular (CV) events and health care resource utilization during the 12 months before the index date (“baseline period”) were compared between patients with optimal versus suboptimal glycaemic control (glycated haemoglobin [HbA1c] <7.0% vs. ≥7.0% [53 mmol/mol]) at the closest measurement to the index date.ResultsOf 31 430 adults with T1D, 79.9% had suboptimal glycaemic control (mean HbA1c 8.8% [73 mmol/mol]). These patients were more likely to be younger, African American, uninsured or on Medicaid, obese, smokers, have uncontrolled hypertension and have depression. Despite worse glycaemic control and increased CV risk factors of uncontrolled hypertension, obesity and smoking, rates of coronary heart disease and stroke were not higher in these patients. Patients with suboptimal glycaemic control also experienced more diabetes complications (including SH, DKA and microvascular disease) and utilized more emergency care, with more emergency department visits and inpatient stays.ConclusionThis real‐world study of >30 000 adults with T1D showed that individuals with suboptimal versus optimal glycaemic control differed significantly in terms of health care coverage, comorbidities, diabetes‐related complications, health care utilization and CV risk factors. However, suboptimal control was not associated with increased risk of CV outcomes.

Type-1 diabetic individuals differ with regard to both, the formation of circulating insulin antibodies, and the incidence of severe hypoglycaemia. To assess the association of insulin binding to antibodies with the incidence of severe hypoglycaemia. In a cross sectional study, 73 children with type-1 diabetes mellitus (median age 14 years, duration of diabetes 6 years) were investigated, 22 of whom had experienced severe hypoglycaemia during the past 18 months, and 51 had never experienced severe hypoglycaemia. Of the patients with severe hypoglycaemia 16 had experienced severe unexplained hypoglycaemias, and 6 had experienced severe hypoglycaemias which were explicable (by missed meals, unplanned physical exercise etc.). Insulin binding was measured in a blinded central laboratory by radioimmunoassay, and expressed as ratio bound/unbound insulin; a binding >15% was considered relevant insulin binding. A total of 38 patients displayed relevant insulin binding (17 of whom had experienced severe hypoglycaemia), and 35 patients did not (5 of whom had experienced severe hypoglycaemia; p=0.0055, Fisher's exact test). Patients with relevant insulin binding were younger (12.2 vs 14.5 years, p=0.006) than patients without relevant insulin binding. From the 16 patients with inexplicable severe hypoglycaemia, 15 displayed relevant insulin binding, compared to 2 of the 6 patients with explicable severe hypoglycaemia (p=0.009). The association of any severe hypoglycaemia, and of inexplicable severe hypoglycaemia, with relevant insulin binding was significant (odds ratio 4.8 (95%CI 1.5-15.2), and 22.1(95%CI 2.7-179.6), p<0.006). Patients with/without relevant insulin binding, or with/without severe hypoglycaemia, did not differ significantly regarding sex, duration of diabetes, number of insulin injections per day, HbA1c and C-peptide levels (ANOVA). Insulin binding to antibodies >15% appears to be a strong risk factor for inexplicable severe hypoglycaemias in type-1 diabetic children.