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.

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.

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.

Increasing Use of Diabetes Devices: What Do Health Care Professionals Need?

Despite evidence of improved diabetes outcomes with diabetes technology such as continuous glucose monitoring (CGM) systems, insulin pumps, and hybrid closed-loop (HCL) insulin delivery systems, these devices are underutilized in clinical practice for the management of insulin-requiring diabetes. This low uptake may be the result of health care providers' (HCPs') lack of confidence or time to prescribe and manage devices for people with diabetes. We administered a survey to HCPs in primary care, pediatric endocrinology, and adult endocrinology practices in the United States. Responding HCPs expressed a need for device-related insurance coverage tools and online data platforms with integration to electronic health record systems to improve diabetes technology uptake in these practice settings across the United States.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

A Randomized Comparison of Postprandial Glucose Excursion Using Inhaled Insulin Versus Rapid-Acting Analog Insulin in Adults With Type 1 Diabetes Using Multiple Daily Injections of Insulin or Automated Insulin Delivery.

OBJECTIVE: To compare postprandial glucose excursions following a bolus with inhaled technosphere insulin (TI) or subcutaneous rapid-acting analog (RAA) insulin. RESEARCH DESIGN AND METHODS: A meal challenge was completed by 122 adults with type 1 diabetes who were using multiple daily injections (MDI), a nonautomated pump, or automated insulin delivery (AID) and who were randomized to bolus with their usual RAA insulin (n = 61) or TI (n = 61). RESULTS: The primary outcome, the treatment group difference in area under the curve for glucose >180 mg/dL over 2 h, was less with TI versus RAA (adjusted difference -12 mg/dL, 95% CI -22 to -2, P = 0.02). With TI, the glucose excursion was smaller (P = 0.01), peak glucose lower (P = 0.01), and time to peak glucose shorter (P = 0.006). Blood glucose <70 mg/dL occurred in one participant in each group. CONCLUSIONS: Postmeal glucose excursion was smaller with TI than with RAA insulin in a cohort that included both AID and MDI users.

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.

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.