Transient hyperglycemia during induction chemotherapy is associated with increased morbidity and mortality in patients with acute lymphoblastic leukemia (ALL). Treatment with glucocorticoids, ...asparaginase, and stress are the proposed causal factors. Although these risks are not exclusive to induction, glycemic control throughout the remainder of ALL/lymphoma (ALL/ALLy) therapy has not been described. Furthermore, prior research has been limited to transient hyperglycemia. This study aimed to characterize glycemic control throughout ALL/ALLy and to evaluate risk factors and outcomes associated with increased mean glucose and glucose coefficient of variation (glucose CV) during induction chemotherapy. The records for 220 pediatric/young adult patients, age 1 to 26 years, who underwent treatment for ALL/ALLy from 2010 to 2014 at Children's Hospital Colorado were retrospectively reviewed. Measures of glycemic control were calculated for each cycle. For the cycle with the highest mean glucose, induction (n=208), multivariable models were performed to identify potential risk factors and consequences of increased glucose. Highest mean glucose by cycle were induction 116 mg/dL, pretreatment 108 mg/dL, delayed intensification 96 mg/dL, and maintenance 93 mg/dL; these cycles also had the most glycemic variability. During induction, patients with Down syndrome, or who were ≥12 years and overweight/obese, had higher mean glucoses; age and overweight/obese status were each associated with increased glucose CV. In multivariable analysis, neither induction mean glucose nor glucose CV were associated with increased hazard of infection, relapse, or death.
Diabetes-related technology has undergone great advancement in recent years. These technological devices are more commonly utilized in the type 1 diabetes population, which requires insulin as the ...primary treatment modality. Available devices include insulin pumps, continuous glucose monitors, and hybrid systems referred to as automated insulin delivery systems or hybrid closed-loop systems, which combine those two devices along with software algorithms to achieve advanced therapeutic capabilities, including automatic modulation of insulin delivery based on sensor-derived glucose levels to minimize abnormal glucose trends. Use of diabetes technology is associated with significant positive health and psychosocial outcomes, yet utilization rates are generally lacking across both adult and pediatric type 1 diabetes populations in the United States and other countries. There are consistent themes in existing barriers to technology uptake reported by individuals with type 1 diabetes or parents of children with type 1 diabetes, including physical burdens associated with wearing the devices, concerns in navigating the technology and the devices' abilities to meet user expectations, high cost, inadequate resources within the healthcare team to support device use, disparities in technology access, and psychosocial barriers. It is important to understand the common barriers to uptake of not only the automated insulin delivery systems but also their component devices (insulin pumps and continuous glucose monitors) to fully support individuals in utilizing these devices and optimizing health benefits. The purpose of this article is to summarize the current automated insulin delivery devices that are available for use in management of type 1 diabetes, review common barriers to uptake of those systems and their component devices, and provide expert opinion on existing and future solutions to identified barriers. Keywords: type 1 diabetes, artificial pancreas, insulin pump, continuous glucose monitor, hybrid closed loop
Safety and significant improvement in overall glycated hemoglobin (A1C) and percentage of time spent in (TIR), below (TBR), and above (TAR) glucose range were demonstrated in the pivotal trial of ...adolescents and adults using the MiniMed™ advanced hybrid closed-loop (AHCL) system with the adjunctive, calibration-required Guardian™ Sensor 3. The present study evaluated early outcomes of continued access study (CAS) participants who transitioned from the pivotal trial investigational system to the approved MiniMed™ 780G system with the non-adjunctive, calibration-free Guardian™ 4 Sensor (MM780G+G4S). Study data were presented alongside those of real-world MM780G+G4S users from Europe, the Middle East, and Africa.
The CAS participants (
= 109, aged 7-17 years and
= 67, aged >17 years) used the MM780G+G4S for 3 months and data of real-world MM780G+G4S system users (
= 10,204 aged ≤15 years and
= 26,099 aged >15 years) were uploaded from September 22, 2021 to December 02, 2022. At least 10 days of real-world continuous glucose monitoring (CGM) data were required for analyses. Glycemic metrics, delivered insulin and system use/interactions underwent descriptive analyses.
Time in AHCL and CGM use were >90% for all groups. AHCL exits averaged 0.1/day and there were few blood glucose measurements (BGMs) (0.8/day-1.0/day). Adults in both cohorts met most consensus recommendations for glycemic targets. Pediatric groups met recommendations for %TIR and %TBR, although not those for mean glucose variability and %TAR, possibly due to low use of recommended glucose target (100 mg/dL) and active insulin time (2 h) settings (28.4% in the CAS cohort and 9.4% in the real-world cohort). The CAS pediatric and adult A1C were 7.2% ± 0.7% and 6.8% ± 0.7%, respectively, and there were no serious adverse events.
Early clinical use of the MM780G+G4S was safe and involved minimal BGMs and AHCL exits. Consistent with real-world pediatric and adult use, outcomes were associated with achievement of recommended glycemic targets. Clinical Trial Registration number: NCT03959423.
Assess the efficacy of inControl AP, a mobile closed-loop control (CLC) system.
This protocol, NCT02985866, is a 3-month parallel-group, multicenter, randomized unblinded trial designed to compare ...mobile CLC with sensor-augmented pump (SAP) therapy. Eligibility criteria were type 1 diabetes for at least 1 year, use of insulin pumps for at least 6 months, age ≥14 years, and baseline HbA
<10.5% (91 mmol/mol). The study was designed to assess two coprimary outcomes: superiority of CLC over SAP in continuous glucose monitor (CGM)-measured time below 3.9 mmol/L and noninferiority in CGM-measured time above 10 mmol/L.
Between November 2017 and May 2018, 127 participants were randomly assigned 1:1 to CLC (
= 65) versus SAP (
= 62); 125 participants completed the study. CGM time below 3.9 mmol/L was 5.0% at baseline and 2.4% during follow-up in the CLC group vs. 4.7% and 4.0%, respectively, in the SAP group (mean difference -1.7% 95% CI -2.4, -1.0;
< 0.0001 for superiority). CGM time above 10 mmol/L was 40% at baseline and 34% during follow-up in the CLC group vs. 43% and 39%, respectively, in the SAP group (mean difference -3.0% 95% CI -6.1, 0.1;
< 0.0001 for noninferiority). One severe hypoglycemic event occurred in the CLC group, which was unrelated to the study device.
In meeting its coprimary end points, superiority of CLC over SAP in CGM-measured time below 3.9 mmol/L and noninferiority in CGM-measured time above 10 mmol/L, the study has demonstrated that mobile CLC is feasible and could offer certain usability advantages over embedded systems, provided the connectivity between system components is stable.
The objective of this study was to assess the safety and performance of the Omnipod
personalized model predictive control (MPC) algorithm in adults, adolescents, and children aged ≥6 years with type ...1 diabetes (T1D) under free-living conditions using an investigational device.
A 96-h hybrid closed-loop (HCL) study was conducted in a supervised hotel/rental home setting following a 7-day outpatient standard therapy (ST) phase. Eligible participants were aged 6-65 years with A1C <10.0% using insulin pump therapy or multiple daily injections. Meals during HCL were unrestricted, with boluses administered per usual routine. There was daily physical activity. The primary endpoints were percentage of time with sensor glucose <70 and ≥250 mg/dL.
Participants were 11 adults, 10 adolescents, and 15 children aged (mean ± standard deviation) 28.8 ± 7.9, 14.3 ± 1.3, and 9.9 ± 1.0 years, respectively. Percentage time ≥250 mg/dL during HCL was 4.5% ± 4.2%, 3.5% ± 5.0%, and 8.6% ± 8.8% per respective age group, a 1.6-, 3.4-, and 2.0-fold reduction compared to ST (
= 0.1,
= 0.02, and
= 0.03). Percentage time <70 mg/dL during HCL was 1.9% ± 1.3%, 2.5% ± 2.0%, and 2.2% ± 1.9%, a statistically significant decrease in adults when compared to ST (
= 0.005,
= 0.3, and
= 0.3). Percentage time 70-180 mg/dL increased during HCL compared to ST, reaching significance for adolescents and children: HCL 73.7% ± 7.5% vs. ST 68.0% ± 15.6% for adults (
= 0.08), HCL 79.0% ± 12.6% vs. ST 60.6% ± 13.4% for adolescents (
= 0.01), and HCL 69.2% ± 13.5% vs. ST 54.9% ± 12.9% for children (
= 0.003).
The Omnipod personalized MPC algorithm was safe and performed well over 5 days and 4 nights of use by a cohort of participants ranging from youth aged ≥6 years to adults with T1D under supervised free-living conditions with challenges, including daily physical activity and unrestricted meals.
While continuous glucose monitors (CGMs), insulin pumps, and hybrid closed-loop (HCL) systems each improve glycemic control in type 1 diabetes, it is unclear how the use of these technologies impacts ...real-world pediatric care.
We found 1,455 patients aged <22 years, with type 1 diabetes duration >3 months, and who had data from a single center in between both 2016-2017 (n = 2,827) and 2020-2021 (n = 2,731). Patients were grouped by multiple daily injections or insulin pump, with or without an HCL system, and using a blood glucose monitor or CGM. Glycemic control was compared using linear mixed-effects models adjusting for age, diabetes duration, and race/ethnicity.
CGM use increased from 32.9 to 75.3%, and HCL use increased from 0.3 to 27.9%. Overall A1C decreased from 8.9 to 8.6% (P < 0.0001).
Adoption of CGM and HCL was associated with decreased A1C, suggesting promotion of these technologies may yield glycemic benefits.
Background
Highly variable insulin sensitivity, susceptibility to hypoglycemia and inability to effectively communicate hypoglycemic symptoms pose significant challenges for young children with type ...1 diabetes (T1D). Herein, outcomes during clinical MiniMed™ 670G system use were evaluated in children aged 2–6 years with T1D.
Methods
Participants (N = 46, aged 4.6 ± 1.4 years) at seven investigational centers used the MiniMed™ 670G system in Manual Mode during a two‐week run‐in period followed by Auto Mode during a three‐month study phase. Safety events, mean A1C, sensor glucose (SG), and percentage of time spent in (TIR, 70–180 mg/dl), below (TBR, <70 mg/dl) and above (TAR, >180 mg/dl) range were assessed for the run‐in and study phase and compared using a paired t‐test or Wilcoxon signed‐rank test.
Results
From run‐in to end of study (median 87.1% time in auto mode), mean A1C and SG changed from 8.0 ± 0.9% to 7.5 ± 0.6% (p < 0.001) and from 173 ± 24 to 161 ± 16 mg/dl (p < 0.001), respectively. Overall TIR increased from 55.7 ± 13.4% to 63.8 ± 9.4% (p < 0.001), while TBR and TAR decreased from 3.3 ± 2.5% to 3.2 ± 1.6% (p = 0.996) and 41.0 ± 14.7% to 33.0 ± 9.9% (p < 0.001), respectively. Overnight TBR remained unchanged and TAR was further improved 12:00 am–6:00 am. Throughout the study phase, there were no episodes of severe hypoglycemia or diabetic ketoacidosis (DKA) and no serious adverse device‐related events.
Conclusions
At‐home MiniMed™ 670G Auto Mode use by young children safely improved glycemic outcomes compared to two‐week open‐loop Manual Mode use. The improvements are similar to those observed in older children, adolescents and adults with T1D using the same system for the same duration of time.
Reliable continuous glucose monitoring (CGM) enables a variety of advanced technology for the treatment of type 1 diabetes. In addition to artificial pancreas algorithms that use CGM to automate ...continuous subcutaneous insulin infusion (CSII), CGM can also inform fault detection algorithms that alert patients to problems in CGM or CSII. Losses in infusion set actuation (LISAs) can adversely affect clinical outcomes, resulting in hyperglycemia due to impaired insulin delivery. Prolonged hyperglycemia may lead to diabetic ketoacidosis-a serious metabolic complication in type 1 diabetes. Therefore, an algorithm for the detection of LISAs based on CGM and CSII signals was developed to improve patient safety. The LISA detection algorithm is trained retrospectively on data from 62 infusion set insertions from 20 patients. The algorithm collects glucose and insulin data, and computes relevant fault metrics over two different sliding windows; an alarm sounds when these fault metrics are exceeded. With the chosen algorithm parameters, the LISA detection strategy achieved a sensitivity of 71.8% and issued 0.28 false positives per day on the training data. Validation on two independent data sets confirmed that similar performance is seen on data that was not used for training. The developed algorithm is able to effectively alert patients to possible infusion set failures in open-loop scenarios, with limited evidence of its extension to closed-loop scenarios.
In preclinical studies, thioredoxin-interacting protein overexpression induces pancreatic beta cell apoptosis and is involved in glucotoxicity-induced beta cell death. Calcium channel blockers reduce ...these effects and may be beneficial to beta cell preservation in type 1 diabetes.
To determine the effect of verapamil on pancreatic beta cell function in children and adolescents with newly diagnosed type 1 diabetes.
This double-blind, randomized clinical trial including children and adolescents aged 7 to 17 years with newly diagnosed type 1 diabetes who weighed 30 kg or greater was conducted at 6 centers in the US (randomized participants between July 20, 2020, and October 13, 2021) and follow-up was completed on September 15, 2022.
Participants were randomly assigned 1:1 to once-daily oral verapamil (n = 47) or placebo (n = 41) as part of a factorial design in which participants also were assigned to receive either intensive diabetes management or standard diabetes care.
The primary outcome was area under the curve values for C-peptide level (a measure of pancreatic beta cell function) stimulated by a mixed-meal tolerance test at 52 weeks from diagnosis of type 1 diabetes.
Among 88 participants (mean age, 12.7 SD, 2.4 years; 36 were female 41%; and the mean time from diagnosis to randomization was 24 SD, 4 days), 83 (94%) completed the trial. In the verapamil group, the mean C-peptide area under the curve was 0.66 pmol/mL at baseline and 0.65 pmol/mL at 52 weeks compared with 0.60 pmol/mL at baseline and 0.44 pmol/mL at 52 weeks in the placebo group (adjusted between-group difference, 0.14 pmol/mL 95% CI, 0.01 to 0.27 pmol/mL; P = .04). This equates to a 30% higher C-peptide level at 52 weeks with verapamil. The percentage of participants with a 52-week peak C-peptide level of 0.2 pmol/mL or greater was 95% (41 of 43 participants) in the verapamil group vs 71% (27 of 38 participants) in the placebo group. At 52 weeks, hemoglobin A1c was 6.6% in the verapamil group vs 6.9% in the placebo group (adjusted between-group difference, -0.3% 95% CI, -1.0% to 0.4%). Eight participants (17%) in the verapamil group and 8 participants (20%) in the placebo group had a nonserious adverse event considered to be related to treatment.
In children and adolescents with newly diagnosed type 1 diabetes, verapamil partially preserved stimulated C-peptide secretion at 52 weeks from diagnosis compared with placebo. Further studies are needed to determine the longitudinal durability of C-peptide improvement and the optimal length of therapy.
ClinicalTrials.gov Identifier: NCT04233034.
PDF
