Diabetic ketoacidosis (DKA) is a severe complication of diabetes, primarily affecting individuals with type 1 diabetes (T1D). However, one-third of hospitalized cases involve type 2 diabetes (T2D). Although DKA typically presents with hyperglycemia (>250 mg/dL), the increased use of sodium-glucose transporter 2 inhibitors in addition to other conditions that can increase the risk of euglycemic DKA, or DKA with normal glucose levels, has been growing. DKA hospitalizations in the United States have risen significantly. From 2009 to 2014, hospitalization rates increased 54.9%. Despite a mortality rate of <2%, the growing prevalence of diabetes continues to drive DKA-related hospitalizations, posing a significant health and economic burden. This article examines the prevalence and economic impact of DKA among various diabetes populations in the United States.

Diabetic ketoacidosis (DKA) is a critical medical emergency, with an estimated annual incidence of 4%-8% among adults with type 1 diabetes (T1D). Up to 80% of children/adolescents <15 years of age present with DKA at the time they are diagnosed with T1D. Although DKA occurs less frequently in individuals with type 2 diabetes, there has been a rise in DKA incidence in this population due to increasing use of sodium-glucose cotransporter 2 inhibitors (SGLT-2i), in which DKA often presents with only moderately elevated glucose. This is referred to as euglycemic DKA (euDKA). While DKA is traditionally linked to T1D, it also constitutes a serious clinical concern in other diabetes phenotypes, such as pregnancy and ketosis-prone diabetes. This article provides an overview of the global burden of DKA, recent advancements in ketone monitoring technologies, and the complexities surrounding diabetes classification. Furthermore, it highlights the development of a continuous dual glucose-ketone sensor and its potential applications in the clinical management of individuals at risk for DKA.

Diabetic ketoacidosis (DKA) is a serious and potentially life-threatening complication of diabetes. While clinical trials and observational studies have traditionally included DKA events as part of their safety analyses, several studies have looked specifically at the levels of blood β-hydroxybutyrate associated with DKA in both type 1 diabetes (T1D) and type 2 diabetes (T2D) populations. However, in the findings from these studies, all of the reported data on ketone levels were obtained in the presence of elevated glucose levels or DKA symptoms, using episodic ketone testing via urine ketone test strips. In this report, we present findings from a real-world analysis that investigated patterns of blood ketone testing in people with diabetes using the FreeStyle Libre Continuous Glucose Monitoring system. We also report preliminary case studies from a study currently underway that utilizes a novel dual glucose-ketone sensor to elucidate the glucose and ketone variations in a daily life in people with T1D or T2D who are treated with insulin or sodium-glucose transporter-2 inhibitors therapy.

Diabetic ketoacidosis (DKA) is a life-threatening diabetes emergency associated with mortality and severe morbidities in individuals with diabetes. DKA mainly presents with significant hyperglycemia (>250 mg/dL); however, with the increasing use of sodium-glucose transporter 2 inhibitors, we are seeing an increase in euglycemic DKA (euDKA) in both type 1 diabetes and type 2 diabetes. Although severe DKA generally requires emergency department services or inpatient hospitalization, clinicians can play an important role in helping patients prevent DKA by providing comprehensive education to their patients regarding early identification of elevated ketone states and intervention for improvement in ketone production, thus potentially preventing the severity of DKA. Although ketone monitoring is recommended for all patients at risk for developing DKA or euDKA, current ketone monitoring methods have significant limitations. Abbott Diabetes Care (Alameda, CA) is developing a dual monitoring system that continuously measures interstitial glucose and β-hydroxybutyrate using a single sensor. This article discusses how continuous dual glucose-ketone monitoring can be integrated into primary care practice when it becomes available.

This study evaluated the glycemic responses to a graded exercise test (GXT) performed by 24 adolescents with type 1 diabetes (T1D) using automated insulin delivery (AID) systems. Each participant partook in a GXT on a bicycle ergometer until volitional exhaustion. Plasma glucose and lactate levels were measured during the GXT, whereas sensor glucose was monitored in the hours thereafter. Plasma glucose levels were stable throughout the GXT (overall change of -0.26 mmol/L [-5 mg/dL], = 0.593), with no hypoglycemic events. Sensor glucose levels also remained stable and within the recommended glucose target ranges after the GXT for the remaining day and night, with only a few episodes of mild hypoglycemia. This study highlights the glycemic safety of performing GXT for adolescents utilizing AID systems.

Iscalimab is a fully human, monoclonal anti-CD40 antibody that blocks CD154-induced CD40 signaling. In a Phase 2 (2a) study, new-onset stage 3 type 1 diabetes mellitus (T1DM) participants were randomized 2:1 to iscalimab or placebo administered as a single intravenous dose followed by weekly subcutaneous injections for 1 year to evaluate safety and effects on β cell function. At 14 centers in 6 countries, 44 participants (29 M/15 F, mean age 16 years [range 12-21 years]) were randomized; 39 completed the study (26 active:13 placebo). Treatment was discontinued prematurely in seven, two of these due to a temporary trial halt during the COVID-19 pandemic. No difference in C-peptide area under the curve (C-peptide) during a mixed meal tolerance test was observed after 52 weeks (ratio active:placebo 1.173 [80% confidence interval (CI) 0.94, 1.47], = 0.18). The yearly rate of change of normalized stimulated C-peptide suggests a slower decline of β cell function: iscalimab -0.14 (80% CI -0.23, -0.05) versus placebo -0.33 (-0.42, -0.23) nmol/L per year ( = 0.04). The estimated geometric mean ratio to baseline of hemoglobin A1c at week 52 was lower with iscalimab than placebo (0.95 [80% CI 0.92-0.99] versus 1.05 [80% CI 1.00-1.11], respectively). Leukocytes, neutrophils, and monocytes were lower, whereas T and B lymphocytes were higher in iscalimab-treated participants compared with placebo. Iscalimab was generally safe and well tolerated. Five serious adverse events (AEs) occurred under iscalimab (urinary tract infection, diabetic metabolic decompensation, traumatic fracture, hypoglycemia, and large intestine infection [3.4% each]) and one under placebo (mastoiditis [6.7%]). The most common AEs were hypoglycemia, nasopharyngitis, injection site reaction, COVID-19, and neutropenia. The majority of AEs were mild-to-moderate in intensity and resolved. Iscalimab has an acceptable safety and tolerability profile. The sample size limits interpretation of efficacy results. CD40:CD154 inhibition warrants further investigation in T1DM.

Severe diabetic ketoacidosis (DKA) is a critical medical condition that often necessitates emergency treatment and hospitalization. Although DKA primarily impacts individuals with type 1 diabetes (T1D), its annual incidence among adults with T1D ranges from 4% to 8% following diagnosis. Continuous glucose monitoring (CGM) has become a standard tool for managing T1D and type 2 diabetes (T2D) in patients using insulin or aiming to improve self-management. However, advances in continuous dual glucose-ketone monitoring (DGK) technology offer new possibilities for clinical research and patient care. This article explores the potential applications of DGK in clinical research, with a focus on T1D, while also considering its broader relevance for T2D and other patient populations.

To characterize simplified meal bolus strategies in adults with insulin-treated type 2 diabetes using automated insulin delivery (AID). In the 2IQP study, a 13-week randomized, controlled trial comparing Control-IQ+ AID to continuation of pre-study insulin regimen with continuous glucose monitoring, 201 participants in the AID arm were classified by meal bolus strategy. Glycemic outcomes were compared to baseline. 68 participants' meal bolus strategies (33.8%) were classified as Carbohydrate Counting, 79 (39.3%) were classified as Preset Carbohydrate Amounts, 27 (13.4%) were classified as Fixed Insulin Doses, and 27 (13.4%) as Other Methods. All bolus strategies were associated with similar, significant improvements in HbA1c from baseline: -0.9% for Carbohydrate Counting ( < 0.001), -1.1% for Preset Carbohydrate Amounts ( < 0.001), -0.8% for Fixed Insulin Doses ( < 0.001), and -0.9% for Other Methods ( = 0.003). Hypoglycemia rates were low at baseline and remained low for all bolus strategies. As participants gained experience with the Control-IQ+ AID system, more participants opted to use a simplified bolus strategy in the second half of the study compared with the first half (63% vs. 52%). Simplified bolus strategies worked well for adults with type 2 diabetes using Control-IQ+ in the 2IQP trial. All bolus strategies led to substantial HbA1c improvements, without safety concerns.

While reference ranges for glucose levels are well-established, no physiological benchmark exists for glucose rates of change (RoC), despite the association between rapid glycemic fluctuations and adverse health outcomes. We aimed to define normative RoC values by analyzing continuous glucose monitoring (CGM) data from 153 healthy, nondiabetic individuals (Dexcom G6, up to 10 days). We calculated the percentage of time spent exceeding various RoC thresholds over 5-, 15-, 30-, and 60-min intervals, stratifying results by age and time of day. Over 15 min, the median time with RoC exceeding ±2 mg/dL/min was minimal (1.4% rising, 1.0% falling). RoC was slower when measured over longer intervals, faster when rising than falling, faster during daytime hours, and exhibited modest differences across age groups. We propose a RoC of ±2 mg/dL/min over 15 min as a normative reference, analogous to the 70-140 mg/dL glucose range.

Medicare's current coverage policy for continuous glucose monitoring (CGM) restricts their use to people with diabetes. This restriction is based on an older National Coverage Determination (NCD 40.2) that limits blood glucose testing to people with diabetes. The CGM coverage policy also requires that CGM be used only in accordance with an Food and Drug Administration (FDA) indication for its use. However, the law, regulation, and subregulatory guidance do not require such a restriction. Multiple conditions unrelated to diabetes are associated with risk of hypoglycemic events, such as postbariatric and other upper gastrointestinal surgery, glycogen storage diseases, kidney and liver failure, neuroendocrine tumors that secrete insulin, other forms of tumor-associated hyperinsulinism, and autoimmune conditions. To avoid life-threatening hypoglycemic events, these patients need access to CGM to monitor their glucose levels. Thus, the Centers for Medicare & Medicaid Services should rescind NCD 40.2. The durable medical equipment Medicare administrative contractors (MACs) responsible for establishing CGM coverage policy should remove the requirement that CGM be used only in accordance with an FDA indication for its use. This would allow the MACs to extend coverage for CGM to populations at high risk for hypoglycemia, as the evidence supports such an approach.

This study aimed to evaluate how pre-exercise glucose levels and menstrual cycle phase influence glucose responses to aerobic exercise in adults with type 1 diabetes (T1D) treated with multiple daily insulin injections, with the goal of improving personalized exercise management. We analyzed 51 moderate-intensity, 30-min aerobic sessions (17 male, 34 female) from the TAILOR/1a study. Glucose (plasma and interstitial), heart rate, and anthropometric data were collected. Female participants performed sessions in both the follicular and luteal phases. Glucose trends during exercise were clustered using k-medoids and Dynamic Time Warping. Features from clinical, glucose, and heart rate data were extracted and correlated with cluster assignment. Two distinct glucose response patterns emerged: descending and stable. Higher pre-exercise glucose levels were associated with greater glucose decline and increased hypoglycemia risk, particularly in men. Female participants more frequently exhibited stable glucose profiles, particularly during the luteal phase. Fitness and body composition influenced cluster assignment: fitter individuals-particularly women-were more likely to exhibit stable glucose trends. Pre-exercise glucose was the strongest predictor of response. The menstrual cycle phase had a modest but noticeable effect on glucose dynamics. Glucose response to exercise in T1D is highly variable and influenced by pre-exercise glycemia, sex, fitness level, and menstrual cycle phase. Women, particularly during the luteal phase, demonstrated more stable glycemic responses. These findings support the need for individualized exercise recommendations and for integrating physiological and behavioral factors into predictive models for automated insulin dosing and exercise guidance in T1D.

The rapid advancement of diabetes technology, including continuous glucose monitors (CGMs), insulin pumps, and automated insulin delivery systems, has revolutionized diabetes management. However, current care delivery paradigms have not kept pace, prolonging suboptimal health outcomes for youth with type 1 diabetes (T1D). A significant obstacle is the siloed nature of clinical data. This article explores integrating CGM data for multiple vendors into electronic health records (EHRs) to unify diabetes data in health care practices. This article describes the integration of diabetes device data, following Integration of Continuous Glucose Monitoring Data into the Electronic Health Record (iCoDE) specifications, in the EHR at an urban, tertiary, academic pediatric medical center serving approximately 500,000 pediatric lives in Southwest Ohio. The Diabetes Center provides specialized interdisciplinary care for about 2200 patients with diabetes, with an average of 200+ new onset cases/year. This project is part of the Cincinnati Children's Diabetes Clinic Initiative (ConnecT1D), funded by the Helmsley Charitable Trust, aiming to reorient diabetes care from quarterly visits to continuous, proactive care. By evaluating 6 key factors for integration (data sources types, clinical workflows, level of integration, visualizations, sustainable account management, and optimization), we successfully achieved structural interoperability of CGM device data for 3 vendor platforms into the results section of the EHR using HL7 v2.x. We present practical tips to optimize the integration experience: identify the problem, mobilize resources, negotiate contracts early, evaluate and optimize the workflow, celebrate early wins, prepare for (inevitable) stumbling blocks, keep asking questions, implement change management techniques, and evaluate integration acceptance, iterate, and monitor. While beneficial for patients and clinical workflows, integration of vendor CGM data into the EHR currently requires significant resources. Challenges remain in optimizing workflows, mapping data, and vendor variability. Ongoing monitoring, maintenance, and optimization are necessary as technology and workflows evolve.

The Omnipod® 5 Automated Insulin Delivery (AID) System is the first wearable, on-body, tubeless AID system in the United States. Clinical trials have demonstrated hemoglobin A1C (HbA1c) improvements with Omnipod 5 use. The aim of the study was to evaluate HbA1c changes after initiating Omnipod 5 in a real-world setting. This retrospective study utilized commercial and Medicare Advantage with Part D enrollees' claims data from the Optum Research Database between August 1, 2021, and December 31, 2023. The study included individuals diagnosed with type 1 diabetes (T1D) or type 2 diabetes (T2D) who initiated Omnipod 5. Participants were required to have continuous enrollment for 12 months pre- and post-initiation and at least two medical claims for diabetes during these periods. Demographic and clinical characteristics were measured at the index date, and HbA1c levels were compared pre- and post-initiation of Omnipod 5. The final sample included 2,504 users, with 792 having pre- and post-initiation HbA1c results. The mean age was 54 years; 48% were enrolled in Medicare Advantage, 90% had prior continuous glucose monitoring, and 64% had prior pump therapy. A mean reduction in HbA1c of 0.4% was observed ( < 0.001); mean reductions were 0.4% and 0.5% among those with type 1 and type 2 diabetes, respectively. Among 135 users with pre-initiation HbA1c levels ≥9%, a reduction of 1.4% was noted ( < 0.001). Pre-initiation, 31% achieved the American Diabetes Association (ADA) target of <7% compared to 44% post-initiation (increase of 13%; < 0.001). For the Healthcare Effectiveness Data and Information Set (HEDIS) target of <8%, 62% of individuals achieved the target pre-initiation compared to 78% post-initiation (increase of 16%; < 0.001). In a real-world setting, Omnipod 5 was associated with reduced HbA1c and an increased proportion of individuals achieving ADA and HEDIS glycemic targets.

Postprandial glucose control remains a challenge in people with type 1 diabetes (T1D), even when using advanced hybrid closed-loop systems (AHCL) such as the MiniMed™ 780G (MM780G) system. Missed mealtime boluses are common and can significantly impair glycemic outcomes. This study aimed to evaluate a corrective postprandial bolus strategy for missed meal boluses using the MM780G system. In a prospective, open-label, real-world study, 32 adults with T1D using the MM780G system completed three meal scenarios with standardized meals (∼60 g carbohydrates). The strategies were: (E1) premeal bolus (control), (E2) no bolus (relying on system automation), and (E3) delayed bolus (bolus covering 50% of carbohydrate content, 60 min postmeal). Each participant completed all strategies under remote supervision. Primary outcome was 4-h postprandial time in range (TIR, 70-180 mg/dL); secondary outcomes included time in tight range (TITR, 70-140 mg/dL), time above/below range, and adverse events. Premeal bolus (E1) achieved the highest TIR (85.5% ± 18.8%), significantly outperforming both E2 (52.3% ± 25.3%) and E3 (63.5% ± 24.0%, < 0.001). E3 also showed significant improvement over E2 ( < 0.001). TITR followed a similar pattern. Time between 54 and 70 mg/dL was slightly higher for E1 but remained within consensus goals. No significant differences in hypoglycemia (<54 mg/dL) were observed across strategies. Delayed bolus (E3) lowered time above 250 mg/dL compared with E2. No severe hypoglycemia or ketoacidosis occurred. Premeal bolusing yields optimal postprandial glycemic control with the MM780G. However, when a meal bolus is missed, administering a corrective bolus of 50% carbohydrate content 1 h postmeal significantly improves TIR and TITR without increasing hypoglycemia risk. If correction is not performed, the MM780G system can provide a reasonable partial compensation via autobasal and auto-correction.

Diabetic ketoacidosis (DKA) is a serious, life-threatening complication of diabetes. Although individuals who are at risk for DKA are advised to monitor ketone levels, adherence to monitoring is suboptimal. Continuous ketone monitoring is an emerging technology with the potential to address many of the limitations of current monitoring methods. Abbott Diabetes Care (Alameda, CA) has developed a continuous dual glucose-ketone sensor that measures both interstitial glucose and ketone levels simultaneously, transmitting the information in a continuous stream of data to users. However, one of the challenges in this effort was developing a sensor that can be factory-calibrated to ensure accuracy, safety, and user convenience. This article describes processes realizing factory calibration for the ketone sensor component.

Automated insulin delivery (AID) systems have been shown to be an effective therapeutic option for people with type 1 diabetes and, more recently, for people with type 2 diabetes. To date, the benefit of AID systems has been primarily assessed by glycemic parameters and has been shown to optimize glucose control for people living with diabetes. However, it is increasingly recognized that diabetes management extends beyond glucose levels alone, and there is a need to determine the effectiveness of AID systems in their entirety. This includes the need to also assess additional parameters including the impact of AID on chronic complications of diabetes, quality of life and burden of disease, reliability and durability of devices, health economics, and environmental sustainability. Surrogate endpoints to assess the future risk of microvascular and macrovascular complications and person-reported outcomes through a panel of standardized questionnaires that have been validated for AID systems may be beneficial in comprehensively assessing AID performance. The introduction of AID systems necessitates a balance between optimizing glycemia while simultaneously reducing the burden of diabetes itself and managing the challenges associated with technology use. This review aims to provide a comprehensive analysis of the need to establish endpoints beyond glycemic outcomes with AID use in people living with diabetes.

Diabetic ketoacidosis (DKA) is the most common acute complication and leading cause of mortality in children and adolescents with diabetes. While DKA is mainly seen in type 1 diabetes, youth with type 2 diabetes, especially adolescents, are also susceptible to this condition. As a standard of care, individuals at risk for DKA and their caregivers are provided with instructions for preventing and managing ketone development. However, the use of urine ketone or blood ketone monitoring is often suboptimal. Abbott Diabetes Care (Alameda, CA) is developing a dual monitoring system that continuously measures interstitial glucose and β-hydroxybutyrate using a single continuous dual glucose-ketone (DGK) sensor. The use of continuous ketone monitors in the pediatric population has the potential to improve at-home monitoring and early initiation of intervention with rising ketone levels prior to severe DKA requiring hospitalization. This article reviews the importance of ketone testing, examines current testing options, and discusses how DGK, a novel testing technology, can reduce the occurrence of DKA in children and adolescents who are living with diabetes.

The growing worldwide interest in early-stage type 1 diabetes (T1D) screening highlights the need for efficient and affordable approaches. Advanced analytical technologies such as Antibody Detection by Agglutination-PCR (ADAP) have improved large-scale sample handling, but optimal sample selection for simplified collection and processing remains a major challenge in screening designs. To assess ADAP for T1D-related autoantibody detection in different blood-derived samples to select the optimal sample type for large-scale screening. Autoantibodies against insulin (IAA), glutamate decarboxylase (GADA), protein tyrosine phosphatase IA-2 (IA2A), and zinc transporter 8 (ZnT8A) were analyzed by ADAP in 171 patients with stage 3 T1D (13.7 years; interquartile range [IQR]: 6.5-15.0) and 95 healthy controls (41.9 years; IQR: 29.5-56.7) previously studied by radiobinding assay (RBA). Comparison of sensitivity/specificity of ADAP and RBA in serum was assessed, as well as ADAP concordance across serum, plasma, EDTA-anticoagulated whole blood, and dried blood spot (DBS). Whole-blood stability was also investigated. ADAP-based detection of two or more autoantibodies in serum demonstrated high sensitivity (87.1%) and specificity (100%), with strong concordance with RBA (Cohen's kappa 0.90). Autoantibody analysis in whole blood by ADAP showed high agreement with serum, making it a consistent alternative. In contrast, DBS sampling had reduced concordance, which led to fewer positive detections and suggests a potential bias for T1D screening. A remarkable advantage was that autoantibodies in unrefrigerated whole blood remained stable for up to 7 days (IAA) and 20 days (GADA, IA2A, and ZnT8A), and also after four freeze-thaw cycles, considerably simplifying logistics. Pancreatic autoantibody detection in whole blood with ADAP provides a stable and more efficient diagnostic solution for T1D population screening, with simplified preparation, low-volume requirements, and high diagnostic consistency comparable with serum-based assays.

The Dexcom G7 continuous glucose monitor is labeled for 10 days of wear. We assessed the real-world duration of Dexcom G7 sensor wear in youth with type 1 diabetes (T1D) in this single-center retrospective cohort study. Median duration of sensor wear was calculated for youth using ≥3 sensors over a 93-day period (May 13, 2024, to August 13, 2024). Overall, 643 unique individuals (15.1 years, 45.1% female, 66.3% non-Hispanic White, 60.2% privately insured, 4.9 years T1D duration) wore 5055 sensors over the 93 days. The median sensor wear time was 8.6 days (interquartile range 7.3, 9.6). Wear time was <7.0 days for 24.8% of sensors, and just 39.9% of sensors were worn for ≥10.0 days. In summary, the real-world duration of Dexcom G7 sensor wear is <10 days for most youth with T1D. Whereas people with diabetes typically receive 36 sensors per year, with a median wear time of 8.6 days, youth would require 43 sensors or more to allow for continuous use.