Reduced Efficacy of Glucagon-Like Peptide-1 Receptor Agonists Therapy in People With Type 1 Diabetes and Genetic Forms of Obesity.

BACKGROUND: Once weekly Glucagon-Like Peptide-1 Receptor Agonists (GLP-1 RA) have been shown to improve glycemic outcomes and cause significant weight loss. However, 9% to 27% of individuals have little or no response to these drugs. In this article, we investigated the efficacy of GLP-1 RA therapy among adults with type 1 diabetes and obesity likely related to genetic mutations compared with obesity likely unrelated to genetic mutations. METHODS: In this retrospective study, we compared body weight and glycated hemoglobin (HbA1c) change with the use of GLP-1 RA therapy (including a dual agonist, Tirzepatide) over six months among adults with type 1 diabetes and obesity likely (n = 11, median age 39.5 years with a median BMI of 43.0 kg/m2) versus unlikely related to genetic mutation(s) (n = 15, median age 45.8 years with a median BMI of 38.7 kg/m2). RESULTS: Six months of GLP-1 RA treatment resulted in a numerically lower reduction of weight (-5.75 ± 9.46 kg vs -8.65 ± 9.36 kg, P = .44) and HbA1c (-0.28 ± 0.96% vs -0.43 ± 0.57%, P = .64) among individuals with obesity likely versus unlikely related to a genetic mutation(s), respectively. Fewer individuals with genetic obesity met goal weight loss ≥5% or HbA1c decrease ≥0.4% than did individuals with obesity unlikely related to a genetic cause (36.4% vs 80.0%, P = .04). CONCLUSIONS: The weight loss and glycemic lowering effects of GLP-1 RA therapy may be decreased in people with type 1 diabetes and obesity likely related to genetic causes. Further research is needed to understand GLP-1 RA mechanisms via energy regulating genes.

Limitations of 14-Day Continuous Glucose Monitoring Sampling for Assessment of Hypoglycemia and Glycemic Variability in Type 1 Diabetes.

Continuous glucose monitoring (CGM) has become the standard of care in diabetes management with the recent advances in technology and accessibility in the last decade. An International Consensus was established to define CGM metrics and its goals in diabetes care. The 2019 International Consensus suggested 14 days of CGM sampling for the assessment of CGM metrics stating the limitations that may occur for hypoglycemia and glycemic variability metrics. Since then, several studies assessed the correlation between CGM metrics and duration of the sampling period. This review summarized the studies that investigated the relationship between 14-day CGM sampling to 90-day CGM data in >70% CGM users for all CGM metrics and highlighted possible solutions for more accurate CGM sampling durations in type 1 diabetes (T1D). Accumulating evidence showed that 14-day CGM sampling correlates well with 90-day CGM data for mean glucose, time in 70-180 mg/dL, and hyperglycemia metrics; however, it correlates weakly for hypoglycemia and glycemic variability metrics. In the studies included in this review, in adults with T1D, minimum sampling duration was 14 days for mean glucose, time in 70-180 mg/dL, and time in hyperglycemia (>180 and >250 mg/dL); however, minimum sampling duration varied between 21 to 30 days for time <70 mg/dL, 30 to 35 days for time <54 mg/dL, and 28 to 35 days for coefficient of variation. Longer than 14 days of CGM, sampling was required to properly assess hypoglycemia and glycemic variability in T1D.

Efficacy and Safety of Tirzepatide in Adults With Type 1 Diabetes: A Proof of Concept Observational Study.

BACKGROUND: Tirzepatide is approved by the United States Food and Drug Administration (FDA) for the management of type 2 diabetes. The efficacy and safety of this drug have not been studied in people with type 1 diabetes (T1D). METHODS: In this single-center, retrospective, observational study, hemoglobin A1C (HbA1c), weight, body mass index (BMI), and continuous glucose monitoring (CGM) data were collected from electronic health records of adults with T1D at initiation of tirzepatide and at subsequent clinic visits over 8 months. Primary outcomes were reduction in HbA1c and percent change in body weight and secondary outcomes were change in CGM metrics and BMI over 8 months from baseline. RESULTS: The mean (±SD) age of the 26 adults (54% female) with T1D was 42 ± 8 years with a mean BMI of 36.7 ± 5.3 kg/m2. There was significant reduction in HbA1c by 0.45% at 3 months and 0.59% at 8 months, and a significant reduction in body weight by 3.4%, 10.5%, and 10.1% at 3, 6, and 8 months after starting tirzepatide. Time in target range (TIR = 70-180 mg/dL) and time in tight target range (TITR = 70-140 mg/dL) increased (+12.6%, P = .002; +10.7%, P = .0016, respectively) and time above range (TAR >180 mg/dL) decreased (-12.6%, P = .002) at 3 months, and these changes were sustained over 8 months. The drug was relatively safe and well tolerated with only 2 patients discontinuing the medication. CONCLUSIONS: Tirzepatide significantly reduced HbA1c and body weight in adults with T1D. A randomized controlled trial is needed to establish efficacy and safety of this drug in T1D.

Emerging Technologies and Therapeutics for Type 1 Diabetes.

Recent years witnessed advancements in diabetes technologies and therapeutics. People with type 1 diabetes have more options to control their blood glucose, prevent hypoglycemia, and spend more time with their loved ones. Newer diabetes technologies and therapeutics improve the quality of life and boost the confidence of people with type 1 diabetes. In parallel to changes in the diabetes technology field, stem cell research has been evolving. Gene editing and production of ß cells from stem cells are ongoing. The current focus of cure studies is how to increase the survival of cells produced with stem cells. New adjunctive therapies are under development.

Racial Disparities in Diabetes Technology Adoption and Their Association with HbA1c and Diabetic Ketoacidosis.

Aim: Poorer glycemic control and higher diabetic ketoacidosis (DKA) rates are seen in racial/ethnic minorities with type 1 diabetes (T1D). Use of diabetes technologies such as continuous glucose monitors (CGM), continuous subcutaneous insulin infusion (CSII) and automated insulin delivery (AID) systems has been shown to improve glycemic control and reduce DKA risk. We examined race/ethnicity differences in diabetes technology use and their relationship with HbA1c and DKA. Methods: Data from patients aged ≥12 years with T1D for ≥1 year, receiving care from a single diabetes center, were examined. Patients were classified as Non-Hispanic White (n=3945), Non-Hispanic Black (Black, n=161), Hispanic (n=719), and Multiracial/Other (n=714). General linear models and logistic regression were used. Results: Black (OR=0.22, 0.15-0.32) and Hispanic (OR=0.37, 0.30-0.45) patients were less likely to use diabetes technology. This disparity was greater in the pediatric population (p-interaction=0.06). Technology use associated with lower HbA1c in each race/ethnic group. Among technology users, AID use associated with lower HbA1c compared to CGM and/or CSII (HbA1c of 8.4% vs 9.2%, respectively), with the greatest difference observed for Black adult AID users. CSII use associated with a lower odds of DKA in the past year (OR=0.73, 0.54-0.99), a relationship that did not vary by race (p-interaction =0.69); this inverse association with DKA was not observed for CGM or AID. Conclusion: Disparities in diabetes technology use, DKA, and glycemic control were apparent among Black and Hispanic patients with T1D. Differences in technology use ameliorated but did not fully account for disparities in HbA1c or DKA.

Prevalence of fear of hypoglycemia in adults with type 1 diabetes using a newly developed screener and clinician's perspective on its implementation.

INTRODUCTION: Fear of hypoglycemia (FoH) affects quality of life, emotional well-being, and diabetes management among people with type 1 diabetes (PwT1D). American Diabetes Association's (ADA) guidelines recommend assessing FoH in clinical practice. However, existing FoH measures are commonly used in research and not in clinical practice. In this study, prevalence of FoH was assessed in PwT1D using a newly developed FoH screener for clinical practice; its association with established measures and outcomes was also determined. In addition, healthcare providers' (HCPs) perspectives on implementing FoH screener into real-world practice were explored. RESEARCH DESIGN AND METHODS: This multiphase observational study used mixed methods in two phases. First, we collected a cross-sectional survey (including the screener) from PwT1D (≥18 years) from T1D Exchange Quality Improvement Collaborative adult clinics. Pearson correlations and regression analyses were performed on diabetes outcome measures using screener scores. Second, we conducted focus groups among HCPs who treat PwT1D and descriptive analysis to summarize results. RESULTS: We included 553 PwT1D. Participants had a mean±SD age of 38.9±14.2 years and 30% reported a high FoH total score. Regression analyses showed that higher A1c and higher number of comorbidities were significantly associated with high FoH (p<0.001). High FoH worry and behavior scores were significantly associated with 8-Item Patient Health Questionnaire and 7-Item Generalized Anxiety Disorder Scale scores. Participants with ≥1 severe hypoglycemia event(s) and impaired awareness of hypoglycemia had higher odds of high FoH. Eleven HCPs participated in focus group interviews; they expressed that the FoH screener is clinically necessary and relevant but poses implementation challenges that must be addressed. CONCLUSIONS: Our results demonstrate FoH is common in PwT1D and affects their psychosocial well-being and diabetes management. In alignment with ADA position statement, HCP focus group results emphasize importance of screening for FoH. Implementing this newly developed FoH screener may help HCPs identify FoH in PwT1D.

Increased Technology Use Associated With Lower A1C in a Large Pediatric Clinical Population.

OBJECTIVE: 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. RESEARCH DESIGN AND METHODS: 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. RESULTS: 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). CONCLUSIONS: Adoption of CGM and HCL was associated with decreased A1C, suggesting promotion of these technologies may yield glycemic benefits.

Health Care Professionals' Perspectives on Use of Diabetes Technologies for Managing Visually Impaired Patients With Diabetes.

BACKGROUND: Despite well-established safety and efficacy of diabetes technologies in management of diabetes, their utility in visually impaired patients is currently unknown. We aimed to identify providers' preferences and challenges to prescribing diabetes technologies for visually impaired patients. METHODS: A survey-based study among health care providers in the United States seeing visually impaired patients with diabetes and using diabetes technologies was conducted. The quantitative and qualitative responses were analyzed using Student t test and χ2 tests. RESULTS: Of 79 providers, 66 completed the survey and were included in the analysis. Insulin pens and hybrid closed-loop systems were preferred insulin delivery systems for managing visually impaired patients with diabetes. Despite 96% of the providers recommending continuous glucose monitoring (CGM) for their visually impaired patients with diabetes, only 55% were aware of the voice-activation feature of Dexcom G6. Voice activation to announce glucose values and audible glucose alerts were two major incentives for selecting CGM. System initialization was seen as a prevalent challenge of using CGM in visually impaired patients with diabetes. Providers who are using CGM for visually impaired patients reported benefits for patients using the voice-activation feature for six months included HbA1c reductions of >0.5% (by 87% of providers) and less hypoglycemia (by 45% of providers). CONCLUSIONS: The CGM is the preferred glucose monitoring method for managing visually impaired patients with diabetes. Providers face many challenges of initiating CGM in these high-risk patients. Voice-activation feature of G6 CGM is underutilized and providers who used the system reported positive outcomes in visually impaired patients.

Analysis of Human Leukocyte Antigen DR Alleles, Immune-Related Adverse Events, and Survival Associated With Immune Checkpoint Inhibitor Use Among Patients With Advanced Malignant Melanoma.

Importance: Treatment with immune checkpoint inhibitors (ICIs) has increased survival in patients with advanced malignant melanoma but can be associated with a wide range of immune-related adverse events (irAEs). The role of human leukocyte antigen (HLA)-DR alleles in conferring irAE risk has not been well studied. Objective: To evaluate the association between irAEs and treatment response, survival, and the presence of HLA-DR alleles after ICI therapy in advanced melanoma. Design, Setting, and Participants: This case-control study used the patient registry and biobanked samples from the tertiary referral University of Colorado Cancer Center. Specimens and clinical data were collected between January 1, 2010, and December 31, 2021. Patients with advanced (stage III unresectable and stage IV) melanoma who received ICI therapy (n = 132) were included in the analysis. Exposures: Immune checkpoint inhibitors (anti-cytotoxic T-lymphocyte antigen 4, anti-programmed cell death protein 1 or its ligand, or the combination) for the treatment of advanced melanoma. Main Outcomes and Measures: The association between irAEs and response to therapy, survival, and HLA-DR alleles. Results: Among the cohort of 132 patients with advanced melanoma (mean [SD] age, 63.4 [7.2] years; 85 men [64%] and 47 women [36%]) treated with ICIs, 73 patients had at least 1 irAE and 59 did not have an irAE. Compared with patients without an irAE, patients with an irAE had higher treatment response rates (50 of 72 [69%] vs 28 of 57 [49%]; P = .02) and increased survival (median, 4.8 [IQR, 0.2-9.6] vs 3.2 [IQR, 0.1-9.2] years; P = .02). Specific HLA-DR alleles were associated with the type of irAE that developed: 7 of 10 patients (70%) who developed type 1 diabetes had DR4; 6 of 12 (50%) who developed hypothyroidism had DR8; 5 of 8 (63%) who developed hypophysitis had DR15; 3 of 5 (60%) who developed pneumonitis had DR1; and 8 of 15 (53%) who developed hepatitis had DR4. Conclusions and Relevance: These findings suggest that IrAEs are associated with treatment response rates and increased survival after ICI therapy for advanced melanoma. Because distinct HLA-DR alleles are associated with given adverse events, HLA genotyping before ICI therapy may aid in identifying risk for specific irAEs that could develop with such treatment.

Impact of Different Types of Data Loss on Optimal Continuous Glucose Monitoring Sampling Duration.

Aims: To determine if a longer duration of continuous glucose monitoring (CGM) sampling is needed to correctly assess the quality of glycemic control given different types of data loss. Materials and Methods: Data loss was generated in two different methods until the desired percentage of data loss (10-50%) was achieved with (1) eliminating random individual CGM values and (2) eliminating gaps of a predefined time length (1-5 h). For CGM metrics, days required to cross predetermined targets for median absolute percentage error (MdAPE) for the different data loss strategies were calculated and compared with current international consensus recommendation of >70% of optimal data sampling. Results: Up to 90 days of CGM data from 291 adults with type 1 diabetes were analyzed. MdAPE threshold crossing remained virtually constant for random CGM data loss up to 50% for all CGM metrics. However, the MdAPE crossing threshold increased when losing data with longer gaps. For all CGM metrics assessed in our study (%T70-180, %T < 70, %T < 54, %T > 180, and %T > 250), up to 50% data loss in a random manner did not cause any significant change on optimal sampling duration; however, >30% of data loss in gaps up to 5 h required longer optimal sampling duration. Conclusions: Optimal sampling duration for CGM metrics depends on percentage of data loss as well as duration of data loss. International consensus recommendation for 70% CGM data adequacy is sufficient to report %T70-180 with 2 weeks of data without large data gaps.

Efficacy and Safety of Tandem Control IQ Without User-Initiated Boluses in Adults with Uncontrolled Type 1 Diabetes.

Background: Adults with poorly controlled type 1 diabetes (T1D) who are missing meal boluses are typically excluded from clinical trials of diabetes technologies. We investigated the long-term real-life outcomes of the Tandem Control IQ automated insulin delivery (AID) system in adults with T1D who are missing meal boluses. Methods: In this single-center study with 30 adults with T1D, we evaluated efficacy (A1c and time in target range [TIR]) and safety (time below range [TBR]) in adults with T1D who initiated Tandem Control IQ with minimal or no user-initiated boluses (auto >90%) compared with age, gender, and diabetes duration matched adults with T1D with intermediate (auto 50%-90%) and high bolusing behaviors (auto 10%-49%). Results: Regardless of engagement with Control IQ system, there were significant improvements in A1c and TIR in all three groups over 3, 6, and 12 months. Compared with baseline, there was significant decrease in A1c by 1.6% ± 0.8% and increase in TIR by 19.3% ± 6.4% (P < 0.001 for both) over 12 months of Tandem Control IQ use in auto >90% use group without increasing TBR. Conclusions: Tandem Control IQ is effective in lowering A1c and improving TIR without increasing TBR regardless of users' engagement with the system. Therefore, adults with T1D with high A1c who are mostly missing meal boluses should not be considered as inappropriate candidates for Control IQ AID system.

Accuracy and Safety of Dexcom G7 Continuous Glucose Monitoring in Adults with Diabetes.

Background: We evaluated the accuracy and safety of a seventh generation (G7) Dexcom continuous glucose monitor (CGM) during 10.5 days of use in adults with diabetes. Methods: Adults with either type 1 or type 2 diabetes (on intensive insulin therapy or not) participated at 12 investigational sites in the United States. In-clinic visits were conducted on days 1 or 2, 4 or 7, and on the second half of day 10 or the first half of day 11 for frequent comparisons with comparator blood glucose measurements obtained with the YSI 2300 Stat Plus glucose analyzer. Participants wore sensors concurrently on the upper arm and abdomen. Accuracy evaluation included the proportion of CGM values within 15% of comparator glucose levels >100 mg/dL or within 15 mg/dL of comparator levels ≤100 mg/dL (%15/15), along with the %20/20 and %30/30 agreement rates. The mean absolute relative difference (MARD) between temporally matched CGM and comparator values was also calculated. Results: Data from 316 participants (619 sensors, 77,774 matched pairs) were analyzed. For arm- and abdomen-placed sensors, overall MARDs were 8.2% and 9.1%, respectively. Overall %15/15, %20/20, and %30/30 agreement rates were 89.6%, 95.3%, and 98.8% for arm-placed sensors and were 85.5%, 93.2%, and 98.1% for abdomen-placed sensors. Across days of wear, glucose concentration ranges, and rates of change, %20/20 agreement rates varied by no more than 9% from the overall %20/20. No serious adverse events were reported. Conclusions: The G7 CGM provides accurate glucose readings with single-digit MARD with arm or abdomen placement in adults with diabetes. Clinicaltrials.gov: NCT04794478.

Continuous Glucose Monitoring Initiation Within First Year of Type 1 Diabetes Diagnosis Is Associated With Improved Glycemic Outcomes: 7-Year Follow-Up Study.

OBJECTIVE: To evaluate long-term glycemic outcomes of continuous glucose monitoring (CGM) initiation within the first year of type 1 diabetes diagnosis. RESEARCH DESIGN AND METHODS: Patients with type 1 diabetes (N = 396) were divided into three groups: 1) CGM (CGM use within 1 year of diabetes diagnosis and continued through the study), 2) no-CGM (no CGM use throughout the study), and 3) new-CGM (CGM use after 3 years since diabetes diagnosis). Patients were followed up to 7 years. RESULTS: A1c was significantly lower in the CGM compared with the no-CGM group throughout 7 years of follow-up (least squares mean A1c values: 6 months, 7.3% vs. 8.1%; 1 year, 7.4% vs. 8.6%; 2 years, 7.7% vs. 9.1%; 3 years, 7.6% vs. 9.3%; 4 years, 7.4% vs. 9.6%; 5 years, 7.6% vs. 9.7%; 6 years, 7.5% vs. 10.0%; and 7 years, 7.6% vs. 9.8%; for all, P < 0.001) adjusting for age at diagnosis, sex, and insulin delivery method. CONCLUSIONS: CGM initiation within first year of type 1 diabetes diagnosis results in long-term improvement in A1c.

Mitigation of Rebound Hyperglycemia With Real-Time Continuous Glucose Monitoring Data and Predictive Alerts.

BACKGROUND: Excess carbohydrate intake during hypoglycemia can lead to rebound hyperglycemia (RH). We investigated associations between RH and use of real-time continuous glucose monitoring (rtCGM) and an rtCGM system's predictive alert. METHODS: RH events were series of sensor glucose values (SGVs) >180 mg/dL starting within two hours of an antecedent SGV <70 mg/dL. Events were characterized by their frequency, duration (consecutive SGVs >180 mg/dL × five minutes), and severity (area under the glucose concentration-time curve). To assess the impact of rtCGM, data gathered during the four-week baseline phase (without rtCGM) and four-week follow-up phase (with rtCGM) from 75 participants in the HypoDE clinical trial (NCT02671968) of hypoglycemia-unaware individuals were compared. To assess the impact of predictive alerts, we identified a convenience sample of 24 518 users of an rtCGM system without predictive alerts who transitioned to a system whose predictive alert signals an SGV ≤55 mg/dL within 20 minutes (Dexcom G5 and G6, respectively). RH events from periods of blinded versus unblinded rtCGM wear and from periods of G5 and G6 wear were compared with paired t tests. RESULTS: Compared to RH events in the HypoDE baseline phase, the mean frequency, duration, and severity of events fell by 14%, 12%, and 23%, respectively, in the follow-up phase (all P < .05). Compared to RH events during G5 use, the mean frequency, duration, and severity of events fell by 7%, 8%, and 13%, respectively, during G6 use (all P < .001). CONCLUSIONS: Rebound hypreglycemia can be objectively quantified and mitigated with rtCGM and rtCGM-based predictive alerts.

Evaluation of Accuracy and Safety of the Next-Generation Up to 180-Day Long-Term Implantable Eversense Continuous Glucose Monitoring System: The PROMISE Study.

Background: Use of continuous glucose monitoring (CGM) systems is being rapidly adopted as standard of care for insulin-requiring patients with diabetes. The PROMISE study (NCT03808376) evaluated the accuracy and safety of the next-generation implantable Eversense CGM system for up to 180 days. Methods: This was a prospective multicenter study involving 181 subjects with diabetes at 8 USA sites. All subjects were inserted with a primary sensor. Ninety-six subjects had a second sensor, either an identical sensor or a modified sensor (sacrificial boronic acid [SBA]), inserted in their other arm (53 and 43 subjects, respectively). Accuracy was evaluated by comparing CGM to YSI 2300 glucose analyzer (Yellow Springs Instrument [YSI]) values during 10 clinic visits (day 1-180). Confirmed event detection rates, calibration stability, sensor survival, and serious adverse events (SAEs) were evaluated. Results: For primary sensors, the percent CGM readings within 20%/20% of YSI values was 92.9%; overall mean absolute relative difference (MARD) was 9.1%. The confirmed alert detection rate at 70 mg/dL was 93% and at 180 mg/dL was 99%. The median percentage of time for one calibration per day was 56%. Sixty-five percent of the primary sensors survived to 180 days. For the SBA sensors, the percent CGM readings within 20%/20% of YSI values was 93.9%; overall MARD was 8.5%. The confirmed alert detection rate at 70 mg/dL was 94% and at 180 mg/dL was 99%. The median percentage of time for one calibration per day was 63%. Ninety percent of the SBA sensors survived to 180 days. No device- or insertion/removal procedure-related SAEs were reported. Conclusion: These data show the next-generation Eversense CGM system had sustained accuracy and safety up to 180 days, with an improved calibration scheme and survival, using the primary or SBA sensors.

Comparison of Cgmanalysis, a Free Open-Source Continuous Glucose Monitoring Data Management and Analysis Software, with Commercially Available CGM Platforms: Data Standardization for Diabetes Technology Research.

Background: Cgmanalysis is an open-source software based on the R programming language for data management and descriptive analysis of data from continuous glucose monitoring (CGM). We sought to validate the summary measures calculated by cgmanalysis against the results from proprietary software associated with four CGM commercially available models. Methods: Two weeks of data from 188 patients with type 1 diabetes using commercially available CGMs. Freestyle Libre Gen 1 (n = 53), Medtronic Guardian 3 (n = 52), Dexcom G6 reported by Dexcom Clarity (n = 48), and Dexcom G6 reported by Tandem (n = 35) were analyzed using proprietary software and cgmanalysis. Agreement was assessed using scatterplots, Bland-Altman plots, and equivalence tests. Results: Good agreement was obtained for all glycemic summary measures for all CGMs assessed. None of the differences between the cgmanalysis package and the manufacturers' software were outside the prespecified bounds of equivalence. Conclusions: Cgmanalysis is a validated open-source software to analyze commercially available CGM data and can be used to standardize diabetes technology research.

Differentiating Diabetic Ketoacidosis and Hyperglycemic Ketosis Due to Cannabis Hyperemesis Syndrome in Adults With Type 1 Diabetes.

OBJECTIVE: To differentiate diabetic ketoacidosis (DKA) from hyperglycemic ketosis due to cannabis hyperemesis syndrome (HK-CHS) in adults with type 1 diabetes. RESEARCH DESIGN AND METHODS: Of 295 adults with type 1 diabetes who were seen with DKA-related ICD-10 codes, 68 patients with 172 DKA events meeting the inclusion criteria were analyzed. Cannabis use was defined as a positive urine test result for cannabis. Linear mixed models were used to define HK-CHS (pH ≥7.4 with bicarbonate ≥15 mmol/L [mEq/L]), and sensitivity and specificity were calculated using the receiver operating characteristic (ROC) curve. RESULTS: Cannabis users had significantly higher pH (7.42 ± 0.01 vs. 7.09 ± 0.02) and bicarbonate (19.2 ± 0.61 vs. 9.1 ± 0.71 mmol/L) (P < 0.0001) compared with nonusers. The area under the ROC curve for a positive cannabis urine test result predicting HK-CHS was 0.9892. CONCLUSIONS: In patients who present with DKA and higher pH, especially pH ≥7.4, cannabis use should be considered in the differential diagnosis.