Changes in Basal and Bolus Insulin Requirements with Tirzepatide as an Adjunctive Therapy in Adults with Type 1 Diabetes Using Tandem Control-IQ

INTRODUCTION

This study was aimed at investigating changes in insulin requirements and glycemic outcomes in adults with type 1 diabetes (T1D) using Control IQ (Tandem Diabetes) automated insulin delivery system (AID) over 8 months of tirzepatide treatment.

METHODS

In this single-center, observational study, we collected demographic, A1c, weight, sensor glucose, and insulin dose data for adults with T1D who were using AID and initiated tirzepatide adjunct therapy for clinical indications (n = 11, median age 37, 64% female and mean body mass index of 39.6 kg/m2). Data were compared from baseline and over 8 months.

RESULTS

Within 2 months of tirzepatide treatment, there were significant reductions in total daily insulin [median (IQR) 73.9 (47.6-95.8) to 51.7 (46.7-66.8) units/day, p < 0.001], basal insulin [47 (28.2-51.8) to 32.4 (25.5-46.3) units/day, p < 0.001], and bolus insulin [31.4 (19.9-38.3) to 17.9 (14.9-22.2) units/day, p < 0.001] requirements. Insulin dose reduction from 2 to 8 months was modest. The frequency of user-initiated boluses did not differ throughout the study. Despite reductions in total insulin requirement, time in range (70-180 mg/dl) increased by 7%, A1c reduced by 0.5%, weight reduced by 9%, without increase in time below 70 mg/dl.

CONCLUSIONS

This pilot study provides clinical guidance on insulin titration for adults with T1D who may initiate tirzepatide therapy. Based on the findings of this study, we recommend reducing 25% of total daily insulin dose at tirzepatide initiation in adults with T1D using AID with baseline A1c of less than 7.5%. Higher doses of tirzepatide were associated with greater weight loss, however, the reduction in insulin requirement was minimal.

Efficacy and Safety of Tirzepatide in Overweight and Obese Adult Patients with Type 1 Diabetes

Introduction and Objective: Most patients with type 1 diabetes (T1D) in the United States are overweight (OW) or obese (OB), contributing to insulin resistance and suboptimal glucose control. The primary Food and Drug Administration-approved treatment for T1D is insulin, which may adversely affect weight. Tirzepatide is approved for managing type 2 diabetes, improves glucose control, facilitates weight loss, and improves cardiovascular disease outcomes. We assessed the use of tirzepatide in OW/OB subjects with T1D. Methods: This was a retrospective single-center real-world study in 62 OW/OB adult patients with T1D who were prescribed tirzepatide (treated group) and followed for 1 year. At least 3 months of use of tirzepatide was one of the inclusion criteria. Based on the inclusion criteria, this study represents 62 patients out of 184 prescribed tirzepatide. The control group included 37 OW/OB patients with T1D (computer frequency matched by age, duration of diabetes, gender, body mass index (BMI), and glucose control) who were not using any other weight-loss medications during the same period. The mean (±standard deviation [SD]) dose of weekly tirzepatide at 3 months was 5.6 ± 1.9 mg that increased to 9.7 ± 3.3 mg at 1 year. Results: The gender, mean baseline age, duration of diabetes, and glycosylated hemoglobin (HbA1c) were similar in the two groups, whereas BMI and weight were higher in the treated group. There were significantly larger declines in BMI and weight in the treated group than in controls across all time points among those in whom data were available. HbA1c decreased in the treated group as early as 3 months and was sustained through a 1-year follow-up (-0.67% at 1 year). As expected, insulin dose decreased at 3 months and throughout the study period. There were no reported hospitalizations from severe hypoglycemia or diabetic ketoacidosis. The mean glucose, time-in-range, time-above-range, SD, and coefficient of variation (continuous glucose monitoring metrics) significantly improved in the treated group. Conclusions: In this pilot (off label) study, we conclude that tirzepatide facilitated an average 18.5% weight loss (>46 pounds) and improved glucose control in OW/OB patients with T1D at 1 year. For safe use of tirzepatide in patients with T1D, we strongly recommend a large prospective randomized control trial in OW/OB patients with T1D.

Time in Range Is Associated with Incident Diabetic Retinopathy in Adults with Type 1 Diabetes: A Longitudinal Study

Abstract Objective: To evaluate the association between continuous glucose monitoring (CGM)-based time in various ranges and the subsequent development of diabetic retinopathy (incident DR) in adults with type 1 diabetes. Methods: Between June 2018 and March 2022, adults with type 1 diabetes with incident DR or no retinopathy (control) were identified. CGM data were collected retrospectively for up to 7 years before the date of eye examination defining incident DR or control. Associations between incident DR and CGM metrics were evaluated using logistic regression models. Results: This analysis included 71 adults with incident DR (mean age 27 years, 52% females, and mean diabetes duration 15 years) and 92 adults without DR (mean age 38 years, 48% females, and mean diabetes duration 20 years). Adjusting for age, diabetes duration, and CGM type, each 0.5% increase in glycated hemoglobin (HbA1c), 10 mg/dL increase in mean glucose, 5% decrease in time in target range 70-180 mg/dL (TIR), 5% decrease in time in tight target range 70-140 mg/dL (TITR), and 5% increase in time above 180 mg/dL (TAR) were associated with 24%, 22%, 18%, 28%, and 20% increase in odds of incident DR, respectively. Spearman correlations of TIR, TITR, TAR, and mean glucose with each other were all ≥0.97. Conclusion: Similar to HbA1c, TIR, TITR, TAR, and mean glucose were associated with increased risk for incident DR in adults with type 1 diabetes. These CGM metrics are highly correlated indicating that they provide similar information on glycemic control and diabetic retinopathy risk.

Diabetes Technology Meeting 2023

Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 1 to November 4, 2023. Meeting topics included digital health; metrics of glycemia; the integration of glucose and insulin data into the electronic health record; technologies for insulin pumps, blood glucose monitors, and continuous glucose monitors; diabetes drugs and analytes; skin physiology; regulation of diabetes devices and drugs; and data science, artificial intelligence, and machine learning. A live demonstration of a personalized carbohydrate dispenser for people with diabetes was presented.

Control-IQ Technology Use in Individuals With High Insulin Requirements: Results From the Multicenter Higher-IQ Trial

BACKGROUND

Control-IQ technology version 1.5 allows for a wider range of weight and total daily insulin (TDI) entry, in addition to other changes to enhance performance for users with high basal rates. This study evaluated the safety and performance of the updated Control-IQ system for users with basal rates >3 units/h and high TDI in a multicenter, single arm, prospective study.

METHODS

Adults with type 1 diabetes (T1D) using continuous subcutaneous insulin infusion (CSII) and at least one basal rate over 3 units/h (N = 34, mean age = 39.9 years, 41.2% female, diabetes duration = 21.8 years) used the t:slim X2 insulin pump with Control-IQ technology version 1.5 for 13 weeks. Primary outcome was safety events (severe hypoglycemia and diabetic ketoacidosis (DKA)). Central laboratory hemoglobin A1c (HbA1c) was measured at system initiation and 13 weeks. Participants continued using glucagon-like peptide-1 (GLP-1) receptor agonists, sodium-glucose transport protein 2 (SGLT-2) inhibitors, or other medications for glycemic control and/or weight loss if on a stable dose.

RESULTS

All 34 participants completed the study. Fifteen participants used a basal rate >3 units/h for all 24 hours of the day. Nine participants used >300 units TDI on at least one day during the study. There were no severe hypoglycemia or DKA events. Time in range 70-180 mg/dL was 64.8% over the 13 weeks, with 1.0% time <70 mg/dL. Hemoglobin A1c decreased from 7.69% at baseline to 6.87% at 13 weeks (-0.82%, P < .001).

CONCLUSIONS

Control-IQ technology version 1.5, with wider range of weight and TDI input and enhancements for users with high insulin requirements, was safe in individuals with T1D in this study.

Future of Time-in-Range Goals in the Era of Advanced Hybrid Closed-Loop Automated Insulin Delivery Systems

The concept of maintaining blood glucose levels within the 70-180 mg/dL range, known as time-in-range, has raised questions regarding its representation of true physiological euglycemia. Some have speculated that focusing on the time spent within the 70-140 mg/dL range, introduced as time in tight range (TITR) through the International Consensus statement, could serve as a more precise metric for assessing normoglycemia in individuals with type 1 diabetes. This article delves into the current status of TITR as an emerging marker and explores how advanced hybrid closed-loop systems may offer a promising avenue for achieving this higher level of glycemic control.

Safety and Feasibility Evaluation of Automated User Profile Settings Initialization and Adaptation With Control-IQ Technology

BACKGROUND

Optimization of automated insulin delivery (AID) settings is required to achieve desirable glycemic outcomes. We evaluated safety and efficacy of a computerized system to initialize and adjust insulin delivery settings for the t:slim X2 insulin pump with Control-IQ technology in adults with type 1 diabetes (T1D).

METHODS

After a 2-week continuous glucose monitoring (CGM) run-in period, adults with T1D using multiple daily injections (MDI) (N = 33, mean age 36.1 years, 57.6% female, diabetes duration 19.7 years) were transitioned to 13 weeks of Control-IQ technology usage. A computerized algorithm generated recommendations for initial pump settings (basal rate, insulin-to-carbohydrate ratio, and correction factor) and weekly follow-up settings to optimize glycemic outcomes. Physicians could override the automated settings changes for safety concerns.

RESULTS

Time in range 70 to 180 mg/dL improved from 45.7% during run-in to 69.1% during the last 30 days of Control-IQ use, a median improvement of 18.8% (95% confidence interval [CI]: 13.6-23.9, P < .001). This improvement was evident early in the study and was sustained over 13 weeks. Time <70 mg/dL showed a gradual decreasing trend over time. Percentage of participants achieving HbA1c <7% went from zero at baseline to 55% at study end (P < .001). Only six of the 318 automated settings adaptations (1.9%) were overridden by study investigators.

CONCLUSIONS

Computerized initiation and adaptation of Control-IQ technology settings from baseline MDI therapy was safe in adults with T1D. The use of this simplified system for onboarding and optimizing Control-IQ technology may be useful to increase uptake of AID and reduce staff and patient burden in clinical care.

Changes in the glycaemia risk index and its association with other continuous glucose monitoring metrics after initiation of an automated insulin delivery system in adults with type 1 diabetes

AIM

To evaluate the glycaemia risk index (GRI) and its association with other continuous glucose monitoring (CGM) metrics after initiation of an automated insulin delivery (AID) system in patients with type 1 diabetes (T1D).

MATERIALS AND METHODS

Up to 90 days of CGM data before and after initiation of an AID system from 185 CGM users with T1D were collected. GRI and other CGM metrics were calculated using cgmanalysis R software and were analysed for 24 hours, for both night-time and daytime. GRI values were assigned to five GRI zones: zone A (0-20), B (21-40), C (41-60), D (61-80) and E (81-100).

RESULTS

Compared with baseline, GRI and its components decreased significantly after AID initiation (GRI: 48.7 ± 21.8 vs. 29 ± 13; hypoglycaemia component: 2.7 ± 2.8 vs. 1.6 ± 1.7; hyperglycaemia component: 25.3 ± 14.5 vs. 15 ± 8.5; P < .001 for all). The GRI was inversely correlated with time in range before (r = -0.962) and after (r = -0.961) AID initiation (P < .001 for both). GRI was correlated with time above range (before: r = 0.906; after = 0.910; P < .001 for both), but not with time below range (P > .05). All CGM metrics improved after AID initiation during 24 hours, for both daytime and night-time (P < .001 for all). Metrics improved significantly more during night-time than daytime (P < .01).

CONCLUSIONS

GRI was highly correlated with various CGM metrics above, but not below target range, both before and after AID initiation.

Retained Diabetes Devices-A Literature Review

BACKGROUND

Diabetes management and treatment requires the use of many devices that frequently must puncture the skin, creating a risk of unintentional retention in the body as a retained diabetes device. In this article, we reviewed case studies about retained diabetes devices and presented analyses of the success rate of current imaging techniques in identifying retained devices and the success rate of device removal.

METHODS

PubMed and Google Scholar were searched for articles about retained diabetes devices. Relevant articles that included sufficient details about discovery and removal of the device were included. The success rate of identification and the success rate of removal of retained devices were both calculated as percentages.

RESULTS

Sixteen case studies of retained diabetes devices were identified. These devices included parts of continuous glucose monitors and infusion sets, a lancet, and various types of needles for insulin injection. Each case is presented with details about the year of publication, the retained diabetes device, the company that produced the device, the age and gender of the patient, the type of diabetes that the patient had, the location of the device, the reason for initial discovery of the retained device, the process of locating the device, the success rate for removal of the device, and the removal procedure of the device. Analysis revealed a 100% success rate for the use of imaging technology including X-rays and computed tomography to identify a retained diabetes device. The patients with retained diabetes devices had a 62.5% success rate for eventual removal of the device.

CONCLUSIONS

With the increasing use of injected, inserted, and implanted diabetes wearables for digital health, it is likely that some of the devices will detach, break apart, or otherwise become retained in the body. It is important to be aware of available technologies to identify retained diabetes devices so that it will be possible in most cases to surgically remove these devices if they detach or become retained.

Longitudinal Trends in Glycemic Outcomes and Technology Use for Over 48,000 People with Type 1 Diabetes (2016-2022) from the T1D Exchange Quality Improvement Collaborative

Objective: Previous studies revealed that hemoglobin A1c (HbA1c) increased overall in the United States in the past decade. In addition, health inequities in type 1 diabetes (T1D) outcomes by race/ethnicity and insurance type persist. This study examines the trends in HbA1c from 2016 to 2022 stratified by race/ethnicity and insurance in a large multicenter national database. Research Design and Methods: We analyzed glycemic outcomes and diabetes device use trends for >48,000 people living with type 1 diabetes (PwT1D) from 3 adult and 12 pediatric centers in the T1D Exchange Quality Improvement Collaborative (T1DX-QI), comparing data from 2016 to 2017 with data from 2021 to 2022. Results: The mean HbA1c in 2021-2022 was lower at 8.4% compared with the mean HbA1c in 2016-2017 of 8.7% (0.3% improvement; P < 0.01). Over the same period, the percentage of PwT1D using a continuous glucose monitor (CGM), insulin pump, or hybrid closed-loop system increased (45%, 12%, and 33%, respectively). However, these improvements were not equitably demonstrated across racial/ethnic groups or insurance types. Racial/ethnic and insurance-based inequities persisted over all 7 years across all outcomes; comparing non-Hispanic White and non-Hispanic Black PwT1D, disparate gaps in HbA1c (1.2%-1.6%), CGM (30%), pump (25%-35%), and hybrid-closed loop system (up to 20%) are illuminated. Conclusion: Population-level data on outcomes, including HbA1c, can provide trends and insights into strategies to improve health for PwT1D. The T1DX-QI cohort showed a significant improvement in HbA1c from 2016 to 2022. Improvements in diabetes device use are also demonstrated. However, these increases were inconsistent across all racial/ethnic groups or insurance types, an important focus for future T1D population health improvement work.

Insulin Pump Utilization in 2017-2021 for More Than 22,000 Children and Adults With Type 1 Diabetes: A Multicenter Observational Study

This large type 1 diabetes cohort study showed that insulin pump utilization has increased over time and that use differs by sex, insurance type, and race/ethnicity. Insulin pump use was associated with more optimal A1C, increased use of continuous glucose monitoring (CGM), and lower rates of diabetic ketoacidosis and severe hypoglycemia. People who used an insulin pump with CGM had lower rates of acute events than their counterparts who used an insulin pump without CGM. These findings highlight the need to improve access of diabetes technology through provider engagement, multidisciplinary approaches, and efforts to address health inequities.

Minimum Sampling Duration for Continuous Glucose Monitoring Metrics to Achieve Representative Glycemic Outcomes in Suboptimal Continuous Glucose Monitor Use

BACKGROUND

Two weeks of continuous glucose monitoring (CGM) sampling with >70% CGM use is recommended to accurately reflect 90 days of glycemic metrics. However, minimum sampling duration for CGM use <70% is not well studied. We investigated the minimum duration of CGM sampling required for each CGM metric to achieve representative glycemic outcomes for <70% CGM use over 90 days.

METHODS

Ninety days of CGM data were collected in 336 real-life CGM users with type 1 diabetes. CGM data were grouped in 5% increments of CGM use (45%-95%) over 90 days. For each CGM metric and each CGM use category, the correlation between the summary statistic calculated using each sampling period and all 90 days of data was determined using the squared value of the Spearmen correlation coefficient (R2).

RESULTS

For CGM use 45% to 95% over 90 days, minimum sampling period is 14 days for mean glucose, time in range (70-180 mg/dL), time >180 mg/dL, and time >250 mg/dL; 28 days for coefficient of variation, and 35 days for time <54 mg/dL. For time <70 mg/dL, 28 days is sufficient between 45 and 80% CGM use, while 21 days is required >80% CGM use.

CONCLUSION

We defined minimum sampling durations for all CGM metrics in suboptimal CGM use. CGM sampling of at least 14 days is required for >45% CGM use over 90 days to sufficiently reflect most of the CGM metrics. Assessment of hypoglycemia and coefficient of variation require a longer sampling period regardless of CGM use duration.

Association Between Diabetes Technology Use and Glycemic Outcomes in Adults With Type 1 Diabetes Over a Decade

OBJECTIVE

To evaluate change in mean clinic HbA1c from 2014 to 2021 with diabetes technology use in adults with type 1 diabetes.

RESEARCH DESIGN AND METHODS

In this single-center study, we analyzed diabetes technology use and mean clinic HbA1c among unique adults (age ≥18 years) with type 1 diabetes (last visit of the year per patient) between 1 January 2014 and 31 December 2021 from the electronic medical record. Diabetes technology use was defined as the use of continuous glucose monitors (CGMs) without an automated insulin delivery (AID) system or an AID system. Diabetes technology use and HbA1c over time were analyzed using mixed models adjusted for age, sex, and visit year.

RESULTS

A total of 15,903 clinic visits over 8 years (mean 1,988 patients per year, 4,174 unique patients, 52.7% female, 80.0% Non-Hispanic White) showed significant increases in CGM and AID use (P < 0.001 for both), resulting in an increase of diabetes technology use from 26.9% in 2014 to 82.7% in 2021. These increases were associated with a lower mean clinic HbA1c (7.7-7.5%, P < 0.001) and a higher percentage of adults achieving an HbA1c <7.0% (32.3-41.7%, P < 0.001) from 2014 to 2021. The HbA1c difference between technology users and nonusers increased over time from 0.36% (95% CI 0.26-0.47%, P < 0.001) in 2014 to 0.93% (95% CI 0.80-1.06%, P < 0.001) in 2021.

CONCLUSIONS

Adopting diabetes technology in adults with type 1 diabetes decreased HbA1c and increased the number of people achieving an HbA1c <7.0%, supporting the current international recommendation to offer AID systems to most individuals with type 1 diabetes.

Assessing the relationship between low-calorie sweetener use and quality of life measures in adults with type 1 diabetes

BACKGROUND

To evaluate use of low-calorie sweeteners (LCS) among adults with type 1 diabetes (T1D) and its impact on quality of life (QOL).

METHODS

In this single center, cross-sectional survey study with 532 adults with T1D, Food related QOL (FRQOL), LCS specific questionnaire (LCSSQ), Diabetes Self-Management Questionnaire (DSMQ), Food Frequency Questionnaire (FFQ), Audit of Diabetes-Dependent QOL (AddQOL), Type 1 Diabetes and Life (T1DAL) questionnaires were administered through RedCAP, a secure, HIPAA-compliant web-based application. Demographics and scores of adults who used LCS in last month (recent users) and others (non-users) were compared. Results were adjusted for age, sex, diabetes duration and other parameters.

RESULTS

Of 532 participants (mean age 36 ± 13, 69% female), 99% heard LCS before, 68% used them in the last month, 73% reported better glucose control with LCS use and 63% reported no health concerns about LCS use. Recent LCS users were older and had a longer diabetes duration and more complications (hypertension, or any complication) than non-users. However, A1c, AddQOL, T1DAL, FRQOL scores did not differ significantly between recent LCS users and non-users. DSMQ scores, DSMQ management, diet, health care scores did not differ between two groups; however, recent LCS users had lower physical activity score than non-users (p = 0.001).

CONCLUSIONS

Most of the adults with T1D have used LCS and perceived that LCS use improved their QOL and glycemic control; however, these were not verified with questionnaires. There was no difference in QOL questionnaires except DSMQ physical activity between recent LCS users and not users with T1D. However, more patients in need to increase their QOL may be using LCS; therefore, associations between the exposure and outcome can be bi-directional.

Relationship Between Daytime Versus Nighttime Continuous Glucose Monitoring Metrics with A1C in Adults with Type 1 Diabetes

Objective: To evaluate influence of daytime versus nighttime continuous glucose monitoring (CGM)-based metrics on A1C in adults with type 1 diabetes (T1D). Research Design and Methods: CGM data from 407 adults with T1D (age 39 ± 15 years, diabetes duration 20 ± 12 years, A1C 7.3% ± 1.4% and 53% female) from two studies were included in this analysis. The association between daytime (6 AM-10.59 PM) and nighttime (11 PM-5.59 AM) CGM variables such as mean glucose, time in range (TIR; 70-180 mg/dL), time in tight target range (TTIR; 70-140 mg/dL), and time above range (TAR >180 mg/dL) was examined within five A1C categories (<7%, 7%-7.9%, 8%-8.9%, 9%-9.9%, and ≥10%). Results: Although mean glucose was increasing with higher A1C, there was no statistical difference in mean glucose between daytime versus nighttime within five A1C groups (143.2 ± 22.7 vs. 143.6 ± 25.0 for A1C <7%, 171.4 ± 17.3 vs. 175.3 ± 28.8 for A1C 7.0%-7.9%, 193.4 ± 19.4 vs. 195.3 ± 29.5 for A1C 8.0%-8.9%, 214.9 ± 28.8 vs. 219.7 ± 36.1 for A1C 9.0%-9.9% and 244.0 ± 39.0 vs. 239.9 ± 50.9 for A1C ≥10%, P > 0.05). Similarly, there was no difference between various CGM metrics by daytime versus nighttime within five A1C groups. Differences between five A1C groups' daytime versus nighttime mean glucose, TIR, TTIR, and TAR were also not statistically significant (all P > 0.05) Conclusion: Daytime versus nighttime glycemic control has similar influence on A1C in adults with T1D.

Glucagon receptor antagonist volagidemab in type 1 diabetes: a 12-week, randomized, double-blind, phase 2 trial

Hyperglucagonemia contributes to hyperglycemia in patients with type 1 diabetes (T1D); however, novel therapeutics that block glucagon action could improve glycemic control. This phase 2 study evaluated the safety and efficacy of volagidemab, an antagonistic monoclonal glucagon receptor (GCGR) antibody, as an adjunct to insulin therapy in adults with T1D. The primary endpoint was change in daily insulin use at week 12. Secondary endpoints included changes in hemoglobin A1c (HbA1c) at week 13, in average daily blood glucose concentration and time within target range as assessed by continuous blood glucose monitoring (CGM) and seven-point glucose profile at week 12, incidence of hypoglycemic events, the proportion of subjects who achieve HbA1c reduction of ≥0.4%, volagidemab drug concentrations and incidence of anti-drug antibodies. Eligible participants (n = 79) were randomized to receive weekly subcutaneous injections of placebo, 35 mg volagidemab or 70 mg volagidemab. Volagidemab produced a reduction in total daily insulin use at week 12 (35 mg volagidemab: -7.59 units (U) (95% confidence interval (CI) -11.79, -3.39; P = 0.040 versus placebo); 70 mg volagidemab: -6.64 U (95% CI -10.99, -2.29; P = 0.084 versus placebo); placebo: -1.27 U (95% CI -5.4, 2.9)) without meeting the prespecified significance level (P &lt; 0.025). At week 13, the placebo-corrected reduction in HbA1c percentage was -0.53 (95% CI -0.89 to -0.17, nominal P = 0.004) in the 35 mg volagidemab group and -0.49 (95% CI -0.85 to -0.12, nominal P = 0.010) in the 70 mg volagidemab group. No increase in hypoglycemia was observed with volagidemab therapy; however, increases in serum transaminases, low-density lipoprotein (LDL)-cholesterol and blood pressure were observed. Although the primary endpoint did not meet the prespecified significance level, we believe that the observed reduction in HbA1c and tolerable safety profile provide a rationale for further randomized studies to define the long-term efficacy and safety of volagidemab in patients with T1D.

Diabetes Technology Meeting 2021

Diabetes Technology Society hosted its annual Diabetes Technology Meeting on November 4 to November 6, 2021. This meeting brought together speakers to discuss various developments within the field of diabetes technology. Meeting topics included blood glucose monitoring, continuous glucose monitoring, novel sensors, direct-to-consumer telehealth, metrics for glycemia, software for diabetes, regulation of diabetes technology, diabetes data science, artificial pancreas, novel insulins, insulin delivery, skin trauma, metabesity, precision diabetes, diversity in diabetes technology, use of diabetes technology in pregnancy, and green diabetes. A live demonstration on a mobile app to monitor diabetic foot wounds was presented.

Factors Associated With Improved A1C Among Adults With Type 1 Diabetes in the United States

Many adults with diabetes do not reach optimal glycemic targets, and, despite advances in diabetes management, diabetes technology use remains significantly lower in racial/ethnic minority groups. This study aimed to identify factors associated with achieving the recommended A1C target of <7% using data on 12,035 adults with type 1 diabetes from 15 centers participating in the T1D Exchange Quality Improvement Collaborative. Individuals attaining the target A1C were more likely to be older, White, have private health insurance, and use diabetes technology and less likely to report depressive symptoms or episodes of severe hypoglycemia or diabetic ketoacidosis than those with higher A1C levels. These findings highlight the importance of overcoming inequities in diabetes care.

A randomized controlled trial of transition from insulin pump to multiple daily injections using insulin degludec

AIM

To evaluate two methods of transition from an insulin pump to multiple daily injections (MDI) using long-acting insulin degludec (IDeg).

MATERIALS AND METHODS

After a 1-week run-in period, adults with type 1 diabetes for longer than 1 year and HbA1c 48-69 mmol/mol (6.5%-8.5%), who had been using an insulin pump at least for 6 months, were randomly transitioned to either standard of care (discontinued insulin pump and started IDeg in 1:1 dose) or overlap (IDeg 1:1 at pump basal dose, but pump continued for the first 48 hours with a gradual basal reduction; 50% from 0-24 hours, 75% from 24-48 hours and then pump discontinued). Participants used blinded Dexcom G6 and the IDeg dose was not changed during the trial. Primary (% time above 180 mg/dL) and secondary (% time in 70-180 mg/dL and below 70 mg/dL) outcomes were compared between the two groups during 7 days of randomization.

RESULTS

Age, gender, diabetes duration and basal/bolus insulin doses were similar between patients randomized to standard of care (n = 17) or overlap (n = 13) transition. Compared with overlap transition, the standard of care group spent 4.8% more time in hyperglycaemia (least square mean 4.8% [95% CI -3.3%, 12.9%]) and 5.3% less time in range (-5.3% [-12.6%, -2.0%]), without a significant difference in hypoglycaemia (0.5% [-2.3%,3.4%]). No treatment-related adverse events were noted in either group.

CONCLUSION

The overlap transition method may result in a significant improvement in time-in-range without increasing hypoglycaemia during the first week of transition from an insulin pump to MDI using IDeg in adults with type 1 diabetes.

Suicide and Self-inflicted Injury in Diabetes: A Balancing Act

Glycemic control in type 1 diabetes mellitus (T1DM) remains a challenge for many, despite the availability of modern diabetes technology. While technologies have proven glycemic benefits and may reduce excess mortality in some populations, both mortality and complication rates remain significantly higher in T1DM than the general population. Diabetes technology can reduce some burdens of diabetes self-management, however, it may also increase anxiety, stress, and diabetes-related distress. Additional workload associated with diabetes technologies and the dominant focus on metabolic control may be at the expense of quality-of-life. Diabetes is associated with significantly increased risk of suicidal ideation, self-harm, and suicide. The risk increases for those with diabetes and comorbid mood disorder. For example, the prevalence of depression is significantly higher in people with diabetes than the general population, and thus, people with diabetes are at even higher risk of suicide. The Center for Disease Control and Prevention reported a 24% rise in US national suicide rates between 1999 and 2014, the highest in 30 years. In the United Kingdom, 6000 suicides occur annually. Rates of preventable self-injury mortality stand at 29.1 per 100 000 population. Individuals with diabetes have an increased risk of suicide, being three to four times more likely to attempt suicide than the general population. Furthermore, adolescents aged 15 to 19 are most likely to present at emergency departments for self-inflicted injuries (9.6 per 1000 visits), with accidents, alcohol-related injuries, and self-harm being the strongest risk factors for suicide, the second leading cause of death among 10 to 24 year olds. While we have developed tools to improve glycemic control, we must be cognizant that the psychological burden of chronic disease is a significant problem for this vulnerable population. It is crucial to determine the psychosocial and behavioral predictors to uptake and continued use of technology in order to aid the identification of those individuals most likely to realize benefits of any intervention as well as those individuals who may require more support to succeed with technology.

Case series of a hybrid closed-loop system used in pregnancies in clinical practice

BACKGROUND

Hybrid closed-loop (HCL) therapy is rarely studied in pregnancy. We present three cases of women with type 1 diabetes who used the Medtronic 670G HCL system for most or all of gestation.

METHODS

The Medtronic 670G system has a manual mode (no automated insulin delivery) and an auto mode (AM, HCL therapy). Women in this case series used AM off-label in gestation.

RESULTS

Case 1 started HCL therapy in the second trimester, her sensor glucose time spent <3.9 and >10 mmol/L improved thereafter. Case 1 had average sensor glucose (ASG) levels of 6.4 ± 2.4 mmol/L in the first trimester, 7.0 ± 2.7 mmol/L in the second trimester before HCL use, 7.1 ± 2.1 mmol/L in the second trimester after HCL use, and 6.8 ± 1.9 mmol/L in the third trimester. Case 1 continued AM during operative delivery and post-partum. Cases 2 and 3 used HCL therapy throughout gestation but with inconsistent time in AM. When they increased time in AM their glycaemic indices improved. Case 2 had ASG of 9.5 ± 3.4, 8.6 ± 2.9, and 7.9 ± 2.5 mmol/L in the first through third trimesters, respectively. Case 3 had ASG of 11.1 ± 4.8 and 3.9 to 10 mmol/L in the first and second trimesters, respectively. Case 2 continued HCL therapy post-partum, Case 3 did not.

CONCLUSIONS

CareLink® Clinical Software only reports the non-pregnant time in range. Nonetheless, this represents the first report of HCL therapy in pregnancy with a system approved by the Food and Drug Administration in non-pregnant populations.

Cannabis Use Is Associated With Increased Risk for Diabetic Ketoacidosis in Adults With Type 1 Diabetes: Findings From the T1D Exchange Clinic Registry

OBJECTIVE

We examined the frequency of diabetic ketoacidosis (DKA) in cannabis users compared with nonusers in the T1D Exchange clinic registry (T1DX).

RESEARCH DESIGN AND METHODS

The association between cannabis use by total substance score for cannabis (TSC) and DKA in the past 12 months was examined using a logistic regression model adjusted for potential confounders among adults in the T1DX.

RESULTS

Of 932 adults with type 1 diabetes, 61 had a TSC >4, which classified them as moderate cannabis users. Adjusting for sex, age at study visit, and HbA_1c, cannabis use was associated with a twofold increase in risk for DKA among adults with type 1 diabetes (odds ratio 2.5 [95% CI 1.0-5.9]).

CONCLUSIONS

Cannabis use was associated with an increased risk for DKA among adults in the T1DX. Providers should inform their patients of the potential risk of DKA with cannabis use.

Efficacy of Hybrid Closed-Loop System in Adults with Type 1 Diabetes and Gastroparesis

We evaluated the efficacy of 670 G HCL on changes in HbA1c and continuous glucose monitor (CGM)-based glucose metrics at 3 and 6 months between five adults with T1D with gastroparesis and nine age-, sex-, and diabetes duration-matched T1D without gastroparesis. At baseline, there were no differences in age, gender, diabetes duration, and total daily insulin requirement between two groups. Median duration of gastroparesis diagnosis was 4.3 years (interquartile range [IQR]: 3.7, 5.9 years). Reduction in HbA1c [difference in HbA1c from baseline to 6 months, median (IQR): 0.3% (0.3%, 0.3%) vs. 0.5% (0.3%, 0.9%); P = 0.20] and CGM time spent in normoglycemia at 6 months [median (IQR): 73% (68%, 80%) vs. 67% (64%, 74%); P = 0.24] were not different between the groups. HCL has similar efficacy in glucose control in adults with T1D with gastroparesis and appears to be safe in this population.

Association Between Cannabis Use and Risk for Diabetic Ketoacidosis in Adults With Type 1 Diabetes

This survey study investigates whether cannabis use is associated with risk of diabetic ketoacidosis in adults with type 1 diabetes.

The cortisol stress response induced by surgery: A systematic review and meta-analysis

OBJECTIVE

Surgery is a stressor that can be categorized by duration and severity and induces a systemic stress response that includes increased adrenal cortisol production. However, the precise impact of surgical stress on the cortisol response remains to be defined.

DESIGN

We performed a systematic review and meta-analysis to assess the cortisol stress response induced by surgery and to stratify this response according to different parameters.

METHODS

We conducted a comprehensive search in several databases from 1990 to 2016. Pairs of reviewers independently selected studies, extracted data and evaluated the risk of bias. Cortisol concentrations were standardized, pooled in meta-analysis and plotted over time.

RESULTS

We included 71 studies reporting peri-operative serum cortisol measurements in 2953 patients. The cortisol response differed substantially between moderately/highly invasive and minimally invasive surgical procedures. Minimally invasive procedures did not show a peri-operative cortisol peak, whereas more invasive surgeries caused a cortisol surge that was more pronounced in older subjects, women and patients undergoing open surgery and general anaesthesia. The duration of the procedure and the use of etomidate for induction of anaesthesia did not affect the cortisol response.

CONCLUSIONS

The peri-operative cortisol stress response is dynamic and influenced by patient-specific, surgical and anaesthetic features. However, the available evidence is derived from highly heterogeneous studies, with only two of 71 studies measuring cortisol by mass spectrometry, which currently prevents a precise and reproducible definition of this response.

New-onset insulin-dependent diabetes due to nivolumab

Nivolumab, a monoclonal antibody against programmed cell death-1 receptor, is increasingly used in advanced cancers. While nivolumab use enhances cancer therapy, it is associated with increased immune-related adverse events. We describe an elderly man who presented in ketoacidosis after receiving nivolumab for metastatic renal cell carcinoma. On presentation, he was hyperpneic and laboratory analyses showed hyperglycemia and anion-gapped metabolic acidosis consistent with diabetic ketoacidosis. No other precipitating factors, besides nivolumab, were identified. Pre-nivolumab blood glucose levels were normal. The patient responded to treatment with intravenous fluids, insulin and electrolyte replacement. He was diagnosed with insulin-dependent autoimmune diabetes mellitus secondary to nivolumab. Although nivolumab was stopped, he continued to require multiple insulin injection therapy till his last follow-up 7 months after presentation. Clinicians need to be alerted to the development of diabetes mellitus and diabetic ketoacidosis in patients receiving nivolumab.

Alcohol Consumption, Diabetes Risk, and Cardiovascular Disease Within Diabetes

PURPOSE OF REVIEW

The purpose of the study is to examine and summarize studies reporting on the epidemiology, the risk of developing diabetes, and the cardiovascular effects on individuals with diabetes of different levels of alcohol consumption.

RECENT FINDINGS

Men consume more alcohol than women in populations with and without diabetes. Light-to-moderate alcohol consumption decreases the incidence of diabetes in the majority of the studies, whereas heavy drinkers and binge drinkers are at increased risk for diabetes. Among people with diabetes, light-to-moderate alcohol consumption reduces risks of cardiovascular diseases and all-cause mortality. Alcohol consumption is less common among populations with diabetes compared to the general population. Moderate alcohol consumption reduces the risk of diabetes and, as in the general population, improves cardiovascular health in patients with diabetes. Type of alcoholic beverage, gender, and body mass index are factors that affect these outcomes.

Role of Mobile Technology to Improve Diabetes Care in Adults with Type 1 Diabetes: The Remote-T1D Study iBGStar® in Type 1 Diabetes Management

INTRODUCTION

The role of mobile technology in patient-reported outcomes (PRO) and glycemic control in adults with type 1 diabetes (T1D) needs further evaluation.

METHODS

The single-center, prospective, 6-month, open-label, investigator-initiated study randomized 100 subjects with T1D in a 1:1 fashion to a control group using self-monitoring of blood glucose (SMBG) with Accu-Chek Nano® and an intervention group using SMBG with iPhone plus glucose meter (iBGStar®). The primary endpoint was the change in PRO (hypoglycemia fear score, behavior and worry subscores). Secondary outcomes were the improvement in glycemic variability indices and the reduction in A1c values.

RESULTS

Baseline demographics and glycosylated hemoglobin (A1c) values were similar in the two groups. There was a significant decrease in A1c value at 6 months in iBGStar® group compared to the control group (-0.16 vs. -0.51, p = 0.04). The total insulin dose increased significantly in the iBGStar® group at 3 months but did not change at 6 months. The hypoglycemia fear scale (PRO) improved in both groups at 6 months (-1.4 ± 10.0 vs. -3.9 ± 12.5, p = 0.32).

CONCLUSION

The use of iBGStar® resulted in better glycemic control and improvement in some PRO (hypoglycemia fear and behavior scores) compared to the control group at 6 months with no increased risk of hypoglycemia.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov: NCT01825382.

FUNDING

Sanofi.