Glucose Variability Indices Research Articles

Different Measures of Hyperglycemia Are Negatively Associated With Skin Microvascular Flowmotion: TheMaastricht Study.

Diabetes can lead to microvascular complications such as diabetic neuropathy, nephropathy, and retinopathy. Hyperglycemia may initiate microvascular function impairment early in the course of diabetes, even prior to its clinical establishment during the pre-diabetes stage. Microvascular vasomotion, that is, the rhythmic arteriolar constriction and dilation, is an important function that regulates oxygen and nutrient delivery within the tissue and regulates peripheral resistance. Using laser Doppler flowmetry (LDF), vasomotion in skin microcirculation can be measured as flowmotion. Changes in flowmotion have been shown in individuals with obesity, and type 1 or type 2 diabetes mellitus. However, no data are available on associations between hyperglycemia and flowmotion in the general population. Our aim was to study whether measures of hyperglycemia were associated with different components of skin microvascular flowmotion (SMF) in a population-based cohort (The Maastricht Study). Data from 7293 participants of The Maastricht Study were used. SMF was measured using LDF. Endothelial, neurogenic and myogenic component SMF power were used as dependent variables. We investigated the associations of glucose metabolism status (normal glucose metabolism, prediabetes, and type 2 diabetes mellitus), measures of hyperglycemia (fasting plasma glucose [FPG], 2-h post-load glucose [2 h-PG], HbA1c, advanced glycation end-products [AGEs] assessed as skin autofluorescence [SAF]), and indices of glucose variability (incremental glucose peak [IGP] and continuous glucose monitoring [CGM] -assessed as standard deviation [SD]) with each component of SMF power. We used linear regression analyses with adjustments for confounders, and trend analyses. We observed consistent negative associations between HbA1c levels and all three (endothelial, neurogenic, and myogenic) skin microvascular flowmotion (SMF) powers in the additionally adjusted model. Similarly, in the conservative model, we found that multiple hyperglycemia metrics such as GMS trend, PreD, T2DM, FPG, 2 h-PG, and HbA1c were consistently negatively associated with all three SMF powers. We showed that skin microvascular flowmotion is reduced in individuals with (pre)diabetes. In addition, different measures of hyperglycemia are negatively associated with skin microvascular flowmotion.

Twenty-Four Hour Glucose Profiles and Glycemic Variability during Intermittent Religious Dry Fasting and Time-Restricted Eating in Subjects without Diabetes: A Preliminary Study.

Intermittent religious fasting increases the risk of hypo- and hyperglycemia in individuals with diabetes, but its impact on those without diabetes has been poorly investigated. The aim of this preliminary study was to examine the effects of religious Bahá'í fasting (BF) on glycemic control and variability and compare these effects with time-restricted eating (TRE). In a three-arm randomized controlled trial, 16 subjects without diabetes were assigned to a BF, TRE, or control group. Continuous glucose monitoring and food intake documentation were conducted before and during the 19 days of the intervention, and the 24 h mean glucose and glycemic variability indices were assessed. The BF and TRE groups, but not the control group, markedly reduced the daily eating window while maintaining macronutrient composition. Only the BF group decreased caloric intake (-677.8 ± 357.6 kcal, p = 0.013), body weight (-1.92 ± 0.95 kg, p = 0.011), and BMI (-0.65 ± 0.28 kg, p = 0.006). Higher maximum glucose values were observed during BF in the within-group (+1.41 ± 1.04, p = 0.039) and between-group comparisons (BF vs. control: p = 0.010; TRE vs. BF: p = 0.022). However, there were no alterations of the 24 h mean glucose, intra- and inter-day glycemic variability indices in any group. The proportions of time above and below the range (70-180 mg/dL) remained unchanged. BF and TRE do not exhibit negative effects on glycemic control and variability in subjects without diabetes.

Positive association between the proinsulin-to-C-peptide ratio and prolonged hyperglycemic time in type 2 diabetes.

The proinsulin-to-C-peptide (PI:C) ratio is an index applied during the early stage of pancreatic β-cell dysfunction. The aim of this study was to identify the characteristics associated with the PI:C ratio to discuss pancreatic β-cell dysfunction progression during the natural course of type 2 diabetes and its relationship with glycemic management. This multicenter, prospective observational study included 272 outpatients with type 2 diabetes. Continuous glucose monitoring was performed and fasting blood samples were collected and analyzed. We identified the clinical factors associated with the PI:C ratio by multiple regression analysis. The mean age of the cohort was 68.0 years, mean hemoglobin A1c 7.1% (54 mmol/mol), and mean body mass index 24.9 kg/m2. Multiple regression analysis showed that a prolonged time above the target glucose range (>180 mg/dL) and high body mass index contributed to a high PI:C ratio. However, no associations were found between the PI:C ratio and glucose variability indices. These findings suggested that the PI:C ratio is positively associated with a prolonged hyperglycemic time in type 2 diabetes, whereas its relationship with glucose variability remains unclear.

THU341 Associations Of Longitudinal Nighttime Sleep Characteristics With Nighttime/Daytime Glucose Values As Assessed By Continuous Glucose Monitoring In Type 2 Diabetes

Abstract Disclosure: Y. Li: None. K.K. Danielson: None. J.C. Park: None. J. McAnany: None. F.Y. Chau: None. B. Prasad: None. E.C. Hanlon: None. S. Reutrakul: None. Background: Sleep disturbances have been shown to be associated with incident diabetes and poor glycemic control. Recently, evidence emerged that nightly sleep may affect glucose levels both during that night and the following day. In this study, we explored the association of serial measures of nightly sleep parameters with night/day glucose levels in patients with type 2 diabetes (T2D). Methods: Baseline data of 28 T2D patients participating in an ongoing study exploring the relationship between diabetes retinopathy (DR) and sleep (NCT 04547439) were included. Sleep was objectively recorded using 14-days actigraphy. Sleep parameters nightly included sleep duration, sleep efficiency, wake time after sleep onset (WASO), and mid-sleep time (MST, time between sleep time and waketime). Glucose was recorded using blinded continuous glucose monitors (CGM). CGM data were divided into nighttime and daytime glucose values, utilizing the sleep time from actigraphy. CGM parameters included mean glucose, percent time spent in range (TIR%; glucose values 70-180 mg/dL), percent time above range (>180 mg/dL), and percent time below range (<70 mg/dL). Glucose variability indices included percent coefficient of variation (%CV) and Continuous Overall Net Glycemic Action (CONGA). Longitudinal mixed linear regression models, adjusting for age, sex, insulin use and DR status, were used to determine the associations between sleep parameters and nighttime/subsequent daytime CGM values. Associations were considered statistically significant at p<0.01 due to the multiple comparisons. Results: Mean (SD) age was 55.0 (6.5) years, A1C was 7.8 (1.5)%, 57% of the participants were female and 60.1% had DR. Average sleep duration was 6.1 (1.0) hours, sleep efficiency was 79.8 (9.6)%, WASO was 49.0 (27.1) minutes and MST was 3:25 (1:23) AM. There were a total of 281 nights and 254 days of CGM recordings. For nighttime CGM analyses, sleep duration (mins) was significantly longer in %TIR of ≥70% vs. <70% (β=57, SE=13, p=0.0005), but there were no associations of duration with other CGM parameters. WASO (log) was positively associated with CONGA (β=2.3, SE=0.9, p=0.008). Earlier MST was associated with greater glucose variability including higher CONGA (β=−1.6, SE=0.4, p<0.0001), and %CV (β=−1.6, SE=0.4, p<0.0001). For the following day CGM analyses, only the association between earlier MST and greater time spent below range (β=−0.7, SE=0.2, p=0.006) was significant. Conclusion: Longer nightly sleep duration was associated with higher nighttime %TIR, while poor sleep continuity was associated with higher nighttime glucose variability. In contrast to previous findings, earlier sleep timing was associated with unfavorable glucose profiles both during nighttime and daytime. These pilot data highlighted the associations between nighttime sleep and metabolic control, and should be explored in a larger cohort. Presentation: Thursday, June 15, 2023

Effects of reducing free sugars on 24-hour glucose profiles and glycemic variability in subjects without diabetes.

The Western diet, especially beverages and high processed food products, is high in sugars which are associated with the development of obesity and diabetes. The reduction of refined carbohydrates including free and added sugars improves glycemic control in individuals with diabetes, but the data regarding effects in subjects without diabetes are limited. This study aimed to evaluate the effects of reducing free sugar intake on 24-h glucose profiles and glycemic variability using continuous glucose monitoring (CGM). In the randomized controlled study, 21 normal weight and overweight/obese subjects (BMI 18-40 kg/m2) without diabetes were assigned to a 4-week reduced-sugar (RS) diet or control diet after a 2-week baseline phase. During the baseline phase, all participants were advised not to change their habitual diet. During the intervention phase, RS participants were asked to avoid added sugar and white flour products, whereas participants of the control group were requested to proceed their habitual diet. Anthropometric parameters and HbA1c were assessed before and at the end of the intervention phase. Interstitial glucose was measured using continuous glucose monitoring (CGM), and the food intake was documented by dietary records for 14 consecutive days during the baseline phase and for the first 14 consecutive days during the intervention phase. Mean 24-h glucose as well as intra- and inter-day indices of glucose variability, i.e., standard deviation (SD) around the sensor glucose level, coefficient of variation in percent (CV), mean amplitude of glucose excursions (MAGE), continuous overlapping net glycemic action (CONGA), and mean absolute glucose (MAG), were calculated for the baseline and intervention phases. During the intervention, the RS group decreased the daily intake of sugar (i.e., -22.4 ± 20.2 g, -3.28 ± 3.61 EN %), total carbohydrates (-6.22 ± 6.92 EN %), and total energy intake (-216 ± 108 kcal) and increased the protein intake (+2.51 ± 1.56 EN %) compared to the baseline values, whereby this intervention-induced dietary changes differed from the control group. The RS group slightly reduced body weight (-1.58 ± 1.33 kg), BMI, total fat, and visceral fat content and increased muscle mass compared to the baseline phase, but these intervention-induced changes showed no differences in comparison with the control group. The RS diet affected neither the 24-h mean glucose levels nor intra- and inter-day indices of glucose variability, HbA1c, or diurnal glucose pattern in the within- and between-group comparisons. The dietary reduction of free sugars decreases body weight and body fat which may be associated with reduced total energy intake but does not affect the daily mean glucose and glycemic variability in individuals without diabetes. German Clinical Trials Register (DRKS); identifier: DRKS00026699.

Characteristics of glucose variability in different types of diabetes mellitus in young patients

Introduction. Rare types of diabetes mellitus including MODY (Maturity-Onset Diabetes of the Young) are quite complicated to verification and differential diagnosis. That is often leads to diagnostic delays, medical errors in choosing treatment tactics. This kind of event could aggravate the course of the disease and must be prevented.Aim. Evaluation the characteristics of glucose variability (GV) in different types of diabetes mellitus (DM) in young people using continuous glucose monitoring (CGM) systems is necessary to understand the diagnostic value of the method.Materials and methods. We studied 72 patients with clinical signs of MODY who underwent a molecular genetics study to verify the type of DM. According to the results of the study, patients were divided into 3 groups: with genetically confirmed MODY2 (n = 31), MODY3 (n = 16); comparison group consists of the patients with type 2 diabetes (n = 25). All patients at the second stage underwent CGM for 14 days. At the third stage, the obtained patterns of glycemia were presented in the form of GV indices using the GLINVA program, and an in-depth analysis of glucose variability was performed.Results. Some features in the characteristics of the glycemic profile in young people with monogenic forms of DM were noticed. It was determined that in MODY2 the level of fasting plasma glucose (FPG) (p = 0.004) and HbA1c (p = 0.010) was significantly lower than in MODY3, and low GV was determined during the day, which probably causes a lower incidence of diabetic complications than other types of diabetes. In individuals with MODY3, higher FPG and HbA1c values were found, in contrast to MODY2 and type 2 diabetes. MODY3 profile is characterized with significantly higher GV and longer time spent above the target ranges (compared to type 2 diabetes).Conclusions. The approach to evaluate the glycemic profile used in the study is modern and affordable. It could become a tool for determining criteria for diagnosing the type of diabetes in patients with clinical manifestations of MODY.

(Pre)diabetes, glycemia, and daily glucose variability are associated with retinal nerve fiber layer thickness in The Maastricht Study

Retinopathy and neuropathy in type 2 diabetes are preceded by retinal nerve fibre layer (RNFL) thinning, an index of neurodegeneration. We investigated whether glucose metabolism status (GMS), measures of glycaemia, and daily glucose variability (GV) are associated with RNFL thickness over the entire range of glucose tolerance. We used cross-sectional data from The Maastricht Study (up to 5455 participants, 48.9% men, mean age 59.5 years and 22.7% with type 2 diabetes) to investigate the associations of GMS, measures of glycaemia (fasting plasma glucose [FPG], 2-h post-load glucose [2-h PG], HbA1c, advanced glycation endproducts [AGEs] assessed as skin autofluorescence [SAF]) and indices of daily GV (incremental glucose peak [IGP] and continuous glucose monitoring [CGM]-assessed standard deviation [SD]) with mean RNFL thickness. We used linear regression analyses and, for GMS, P for trend analyses. We adjusted associations for demographic, cardiovascular risk and lifestyle factors, and, only for measures of GV, for indices of mean glycaemia. After full adjustment, type 2 diabetes and prediabetes (versus normal glucose metabolism) were associated with lower RNFL thickness (standardized beta [95% CI], respectively − 0.16 [− 0.25; − 0.08]; − 0.05 [− 0.13; 0.03]; Ptrend = 0.001). Greater FPG, 2-h PG, HbA1c, SAF, IGP, but not CGM-assessed SD, were also associated with lower RNFL thickness (per SD, respectively − 0.05 [− 0.08; − 0.01]; − 0.06 [− 0.09; − 0.02]; − 0.05 [− 0.08; − 0.02]; − 0.04 [− 0.07; − 0.01]; − 0.06 [− 0.12; − 0.01]; and − 0.07 [− 0.21; 0.07]). In this population-based study, a more adverse GMS and, over the entire range of glucose tolerance, greater glycaemia and daily GV were associated with lower RNFL thickness. Hence, early identification of individuals with hyperglycaemia, early glucose-lowering treatment, and early monitoring of daily GV may contribute to the prevention of RNFL thinning, an index of neurodegeneration and precursor of retinopathy and neuropathy.

Cardiovascular Autonomic Neuropathy Is Associated With Increased Glucose Variability in People With Type 1 Diabetes.

We investigated the association between the cardiovascular autonomic neuropathy (CAN) diagnosis and glucose variability (GV) in type 1 diabetes (T1D), as autonomic dysfunction previously has been associated with increased GV. CAN was assessed by three recommended cardiovascular reflex tests (CARTs). Glucose metrics were obtained from 10-day blinded continuous glucose monitoring (CGM). Between-group differences in GV indices were assessed by regression analyses in 24 participants with T1D with CAN and 24 matched control subjects without CAN. The CAN diagnosis was associated with 4.9% (95% CI 1.0, 8.7) higher coefficient of variation (CV) (P = 0.014), 0.7 mmol/L (0.3, 1.1) higher SD (P = 0.002) of glucose, and 1.4 mmol/mol (0.0, 2.7) higher mean amplitude of glycemic excursions (P = 0.047). Lower measures of CARTs were associated with higher CV, SD, and time above range values. The CAN diagnosis associates with a significantly higher GV in T1D, despite a high prevalence of routine CGM use.

Association between hypoglycaemic glucose variability and autonomic function in type1 diabetes with impaired hypoglycaemia awareness

Cardiovascular autonomic neuropathy (CAN) is suggested to underlie hypoglycaemic risk in impaired awareness of hypoglycaemia (IAH). We assessed the prevalence of CAN and the association between glucose variability (GV) and cardiovascular autonomic function in patients with type 1 diabetes (T1DM) and IAH.This study is a post-hoc-analysis of results obtained with the IN-CONTROL-trial, designed to assess the effects of continuous glucose monitoring (CGM) on glycaemia. Forty participants (aged 46.4 ± 11.4 years, diabetes duration 29.1 ± 13.5 years, HbA1c 7.5 ± 0.8%(58.2 ± 8.8 mmol/mol)) underwent 2-week blinded CGM measurements to obtain GV indices. Standardized cardiovascular reflex tests were used to determine the presence of CAN. Cardiovascular autonomic function was assessed with heart rate variability (HRV) measures.14(35%) participants were classified as having CAN. Participants with CAN had lower percentage time spent in hypoglycaemic range and low blood glucose index(LBGI). After correction for confounders, a significant positive association was found between the coefficient of variation (CV) or time spent in hypoglycaemic range and HRV measures SDRR or RMSSD, and between LBGI and RMSSD.In patients with T1DM and IAH, hypoglycaemic parameters were associated with better cardiovascular autonomic function and lower prevalence of CAN. This suggests that autonomic neuropathy does not seem to further deteriorate hypoglycaemic risk in patients with IAH.

1387-P: Impacts of Androgen-Deprivation Therapy on Glucose Metabolism

Study Objective: to assess the impacts of androgen deprivation therapy (ADT) in prostate cancer (PCa) management on glucose metabolism Study Design: follow-up study Materials and Methods: A total of 99 consecutive patients with PCa who received ADT followed-up at Pletnev and 62th Moscow Hospitals. The mean age was 69±8,64 y.o. Fasting plasma glucose (FPG) , HbA1c, body mass index (BMI) , waist circumference (WC) , were measured at baseline, after 3, 6 and 12 months ADT with gonadotropin releasing hormone agonists (GnRH agonists) . Ambulatory glycemic profiles (AGP) were obtained in patients with elevated glycemia who received ADT with GnRH agonists for at least 6 months by Flash glucose monitoring systems. Glucose variability indices (AUC, CONGA, JINDEX) were calculated. Study Results: During ADT there were an increase in FPG and HbA1c over 12 months of ADT regardless of baseline age, BMI, WC, with a maximum increase during the first 3 months of treatment, and progressively after 6 months and 12 months. FPG (mmol/l) initially, 3, 6 and 12 months, were respectively 5,18±0,91; 5,67±0,93; 5,77±0,96; 5,90±1,12 (for all differences p ≤ 0.001) . HbA1c (%) 5,36+0,66; 5,66±0,83; 5,77±0,82; 5,89±0,83 (for all differences p ≤ 0.001) . The proportion of individuals with prediabetes were increased, according to ADA criteria (5,6-6.9 mmol/l) after 3 months 36%, after 6 months 41%, and after 12 months 66%. The impact on glucose metabolism ware in also AGP changes, manifested by an increase in the total daily glycemic load (mean AUC 172,49 (p≤0.001) , glycemic variability (mean CONGA 6,817 (p≤0.001) , and an increased in postprandial glycemia (JINDEX 22,945 (p≤0.001) . Conclusion: ADT with GnRH agonists did worsen metabolic parameters: early, progressive, clinically significant impair of glucose metabolism regardless of baseline age, BMI, WC. AGP deteriorations were increased of glucose variability, total glycemic load gained and peak glycemic values rose. Disclosure E.Y.Gritskevich: None. A.Gritskevich: None. T.Demidova: None.

Reference values of 24-hour, day-time and nocturnal glucose variability parameters in subjects with normal glucose tolerance

BACKGROUND : Glucose variability (GV) is recognized as a risk factor for microvascular and macrovascular complications of diabetes and hypoglycemia. A number of indices have been proposed to assess GV, but there are no generally accepted normal reference values for these indices. AIM : To establish the reference values of 24-hour, day-time and nocturnal GV parameters derived from continuous glucose monitoring (CGM) data in young and middle-aged subjects with normal glucose tolerance. MATERIALS AND METHODS : A blind 6–7-day CGM was performed in 50 subjects, 20 men and 30 women, aged from 22 to 56 years, with normal values of the oral glucose tolerance test and glycated hemoglobin A1c. GV parameters: Standard Deviation (SD), Coefficient of Variation (CV), Mean Amplitude of Glycemic Excursions (MAGE), 2-hour Сontinuous Overlapping Net Glycemic Action (CONGA), Lability Index (LI), J-index, Mean Absolute Glucose rate of change (MAG), М-value, High Blood Glucose Index (HBGI), Low Blood Glucose Index (LBGI) were calculated for 24-hour records, day-time (6.00–23.59) and night (0.00–5.59) hours. RESULTS : 95% confidence intervals for 24-hour records were: mean glucose 5.2–6.6 mmol/L, SD 0.5–1.3 mmol/L, CV 9.1–23.2% , MAGE 1.2–3.2 mmol/L, CONGA 4.3–5.9 mmol/L, MAG 0.5–2.1 mmol×L -1 ×h -1 , LI 0.1–1.3 (mmol/L) 2 ×h -1 , J-index 11.3–18.6 (mmol/L) 2 , M-value 0.4–4.4, HBGI 0.1–1.9, LBGI 0.3–3.2.The following day-time values were estimated: mean glucose 5.3–6.7 mmol/L, SD 0.5–1.4 mmol/L, CV 8.7–24.5%, MAGE 1.2–3.4 mmol/L, CONGA 4.3–5.9 mmol/L, MAG 0.6–2.5 mmol×L -1 ×h -1 , LI 0.2–1.6 (mmol/L) 2 ×h -1 , J-index 11.2–19.6 (mmol/L) 2 , M-value 0.2–3.8, HBGI 0.1–1.9, LBGI 0.3–3.0. The values for nocturnal hours were: mean glucose 4.7–6.4 mmol/L, SD 0.3–0.9 mmol/L, CV 5.3–17.9%, MAGE 0.7–2.7 mmol/L, CONGA 4.1–5.8 mmol/L, MAG 0.3–1.8 mmol×L -1 ×h -1 , LI 0.05–0.8 (mmol/L) 2 ×h -1 , J-index 8.5–17.5 (mmol/L) 2 , M-value 0.2–5.2, HBGI 0–0.9, LBGI 0.3–3.6. CONCLUSION : The obtained reference values of the GV indices should be taken into account in research and in clinical practice when interpreting the results of CGM in young and middle-aged people.

Glucose variability during the early course of acute pancreatitis predicts two‐year probability of new‐onset diabetes: A prospective longitudinal cohort study

BackgroundAcute pancreatitis (AP) is the largest contributor to diabetes of the exocrine pancreas. However, there is no accurate predictor at the time of hospitalisation for AP to identify individuals at high risk for new‐onset diabetes.ObjectiveTo investigate the accuracy of indices of glucose variability (GV) during the early course of AP in predicting the glycated haemoglobin (HbA1c) trajectories during follow‐up.MethodsThis was a prospective longitudinal cohort study of patients without diabetes at the time of hospitalisation for AP. Fasting blood glucose was regularly measured over the first 72 h of hospital admission. The study endpoint was the HbA1c trajectories ‐ high‐increasing, moderate‐stable, normal‐stable ‐ over two years of follow‐up. Multinomial logistic regression analyses were conducted to investigate the associations between several common GV indices and the HbA1c trajectories, adjusting for covariates (age, sex, and body mass index). A sensitivity analysis constrained to patients with non‐necrotising AP was conducted.ResultsA total of 120 consecutive patients were studied. All patients in the high‐increasing HbA1c trajectory group had new‐onset diabetes at 18 and 24 months of follow‐up. Glycaemic lability index had the strongest significant direct association (adjusted odds ratio = 13.69; p = 0.040) with the high‐increasing HbA1c trajectory. High admission blood glucose, standard deviation of blood glucose, and average real variability significantly increased the patients' odds of taking the high‐increasing HbA1c trajectory by at least two‐times. Admission blood glucose, but not the other GV indices, had a significant direct association (adjusted odds ratio = 1.46; p = 0.034) with the moderate‐stable HbA1c trajectory. The above findings did not change materially in patients with non‐necrotising AP alone.ConclusionsHigh GV during the early course of AP gives a prescient warning of worsening HbA1c pattern and new‐onset diabetes after hospital discharge. Determining GV during hospitalisation could be a relatively straightforward approach to early identification of individuals at high risk for new‐onset diabetes after AP.

Carotid Artery Disease in Subjects with Type 2 Diabetes: Risk Factors and Biomarkers.

Carotid atherosclerosis (CA) and, especially, carotid artery stenosis (CAS), are associated with a high risk of cardiovascular events in subjects with type 2 diabetes (T2D). In this study, we aimed to identify risk factors and biomarkers of subclinical CA and CAS in T2D individuals. High-resolution ultrasonography of carotid arteries was performed in 389 patients. Ninety-five clinical parameters were evaluated, including diabetic complications and comorbidities; antihyperglycemic, hypolipidemic, and antihypertensive therapy; indices of glycemic control and glucose variability (GV); lipid panels; estimated glomerular filtration rate (eGFR); albuminuria; blood cell count; and coagulation. Additionally, serum levels of calponin-1, relaxin, L-citrulline, and matrix metalloproteinase-2 and -3 (MMP-2, -3) were measured by ELISA. In univariate analysis, older age, male sex, diabetes duration, GV, diabetic retinopathy, chronic kidney disease, coronary artery disease, peripheral artery disease, and MMP-3 were associated with subclinical CA. In addition to these factors, long-term arterial hypertension, high daily insulin doses, eGFR, and L-citrulline were associated with CAS. In multivariate logistic regression, age, male sex, BMI, GV, and eGFR predicted CA independently; male sex, BMI, diabetes duration, eGFR, and L-citrulline were predictors of CAS. These results can be used to develop screening and prevention programs for CA and CAS in T2D subjects.

Efficacy of omarigliptin, once-weekly dipeptidyl peptidase-4 inhibitor, in patients with type 2 diabetes.

BACKGROUNDOmarigliptin is one of several once-weekly dipeptidyl peptidase-4 inhibitors (DPP-4is). Despite the high frequency of switching from various daily DPP-4is to omarigliptin in actual clinical practice, data regarding its efficacy in patients with type 2 diabetes (T2D) after switching are limited.AIMTo analyze the efficacy of omarigliptin in Japanese patients with T2D who had previously received treatment with other glucose-lowering agents.METHODSForty-nine T2D patients treated for the first time with omarigliptin were recruited retrospectively and divided into four groups defined as either add-on or switched from daily DPP-4is: switched from linagliptin, switched from sitagliptin, and switched from vildagliptin. During a 3-mo follow-up, the clinical parameters among these groups were assessed and compared, with the impact of the switch on glycemic variability as measured by continuous glucose monitoring also being evaluated in the switched groups.RESULTSHemoglobin A1c levels saw a significant decrease of -0.32% ± 0.41% in the add-on group (P = 0.002). However, the other groups’ variables depended on the pre-switch daily DPP-4i: switched from linagliptin, -0.05% ± 0.22%; switched from sitagliptin, -0.17% ± 0.33%; and switched from vildagliptin, 0.45% ± 0.42%, which saw significant worsening (P = 0.0007). Multivariate logistic regression analysis revealed that switching from vildagliptin to omarigliptin was independently associated with worsening glycemic control (P = 0.0013). The mean and standard deviation of sensor glucose value, the mean amplitude of glycemic excursions, and the mean of daily difference significantly improved when switching the patient from either linagliptin or sitagliptin to omarigliptin. However, in patients switched from vildagliptin, not only did the glucose variability indices see no improvements, the mean of daily difference even underwent significant worsening.CONCLUSIONAdministering omarigliptin as add-on therapy or switching to it from sitagliptin and linagliptin, but not vildagliptin, improves glycemic control and thus should help in decision making when selecting DPP-4is for T2D patients.

Variations in Sleep Characteristics and Glucose Regulation in Young Adults With Type 1 Diabetes.

Short sleep duration and sleep disruptions are associated with impaired glucoregulation in type 1 diabetes (T1D). However, the mechanistic pathways between sleep and glucose variability remain unclear. To determine within- and between-person associations between objective sleep-wake characteristics and glucose variability indices. Multilevel models were used to analyze concurrent sleep and glucose patterns over 7 days in 42 young adults with T1D in their natural home environment. Young adults with T1D (mean age 22.2 ± 3.0 years, HbA1c 7.2%, 32.6% male) for at least 6 months with no other medical or major psychiatric comorbidity were included. Sleep-wake characteristics were measured via wrist actigraphy and glucose variability indices via a continuous glucose monitor (CGM). Lower sleep efficiency predicted higher glucose variability (less time in range β = 0.011 and more time in hyperglycemia β = -0.011) within-person. A longer wake after sleep onset and more sleep disruptions were associated with higher glucose variability between persons (β = 0.28 and 0.31). Higher glucose variability predicted poorer sleep within-person (delayed bedtime, waketime, mid-sleep time, and lower sleep efficiency), while higher glucose variability was associated with poorer sleep and more sleep disruptions between persons (lower sleep efficiency, longer wake after sleep onset, and a higher sleep fragmentation index). Clinicians can address the reciprocal nature of the sleep-glucose relationship by optimizing sleep and targeting efforts toward a euglycemic range overnight. Sleep habits are a modifiable personal target in diabetes care.

Maternal glucose variability during pregnancy & birthweight percentile in women with pre-gestational diabetes

Introduction Pre-gestational diabetes mellitus (PGDM) is a major risk factor for fetal overgrowth. Interestingly, even in relatively well controlled PGDM women, as determined by average glucose indices such HbA1c, there is an increased rate of LGA (large for gestational age). Glucose variability (GV) has emerged as an important independent risk factor for several diabetes complications. The aim of this study was to determine the relationship between maternal GV indices and neonatal birth percentile. Methods This was a historical cohort study that included all consecutive PGDM women monitored in a single tertiary care center. Clinical and demographic variables, as well as data regarding glucose control, were prospectively recorded. Mean, standard deviation (SD) and coefficient of variance (CV) of glucose values were calculated. Pearson correlations coefficient was used to determine the correlation between glucose indices and birth percentile. The analysis was repeated after adjustment for several confounders. Results Mean birthweight and birthweight percentile were 3212 ± 532 g and 66.9%, respectively. There was a statistically significant correlation between birthweight percentile and maternal glucose SD (β = 0.28, p = .002) and maternal glucose CV (β = 0.21, p = .019). There was no significant correlation between birthweight percentile and mean glucose values. The association between the maternal glucose SD and birthweight percentile remained statistically significant after adjustment for maternal age, pre-pregnancy BMI and duration of diabetes. Conclusion There is an association between maternal glucose variability indices (SD and CV) during pregnancy and neonatal birth percentile. Larger studies are needed to confirm these results.

340-P: Nocturnal Hypoglycemia Prediction in Hospitalized Patients with Type 1 Diabetes Using Combined Supervised and Unsupervised Ensemble Learning

The Aim: To assess the efficacy of combined supervised and unsupervised ensemble machine learning based on continuous glucose monitoring (CGM) data for short-term prediction of nocturnal hypoglycemia (NH) in hospitalized patients with type 1 diabetes (T1D). Materials and Methods: We analyzed CGM records with a minimal duration of 72 hours obtained from 406 adult patients admitted to tertiary referral hospital. An episode of NH was defined as ≥3 consequent glucose values of <3.9 mmol/L recorded between 0 and 6 am. Depending on predictor sequence length (30 min - 1 h) and horizon (H) of forecasting (5-30 min), we obtained 209-256 and near 4∙104 records with and without NH respectively. Twenty nine metrics, including mean, minimal and maximum glucose, range, gradient, linear, quadratic and cubic trend coefficients, dynamic time wrapping similarity-based indices, and a number of glucose variability indices, were evaluated. The ensemble clustering was used for extraction of representative samples. Random Forest ensemble model was applied for NH prediction. The obtained quality metrics were averaged over 100 random partitions of the dataset on training and testing subsets. Results: The quality metrics did not depend significantly on predictor sequence length; we used 30 min as a baseline. Depending on H, values of sensitivity and specificity varied from 98% and 97% (H=5 min) to 85% and 87% (H=30 min). The false alarm ratio values were very high (>90%) due to the unbalanced nature of data. Minimal glucose, low blood glucose index, and increment in the penultimate value of sequence were the most important predictors assessed with Random Forest algorithm. Conclusions: The results demonstrate the usefulness of ensemble machine learning models based on CGM time series data for prediction of NH events in hospitalized patients with T1D. Additional studies are needed for improving false alarm ratio metrics of forecasting quality. Disclosure V. Berikov: None. J. F. Semenova: None. V. Klimontov: Advisory Panel; Self; Boehringer Ingelheim International GmbH, Sanofi, Research Support; Self; Boehringer Ingelheim International GmbH, Speaker’s Bureau; Self; AstraZeneca, Medtronic. Funding Russian Science Foundation (20-15-00057)

Greater daily glucose variability and lower time in range assessed with continuous glucose monitoring are associated with greater aortic stiffness: The Maastricht Study

AimsCVD is the main cause of morbidity and mortality in individuals with diabetes. It is currently unclear whether daily glucose variability contributes to CVD. Therefore, we investigated whether glucose variability is associated with arterial measures that are considered important in CVD pathogenesis.MethodsWe included participants of The Maastricht Study, an observational population-based cohort, who underwent at least 48 h of continuous glucose monitoring (CGM) (n = 853; age: 59.9 ± 8.6 years; 49% women, 23% type 2 diabetes). We studied the cross-sectional associations of two glucose variability indices (CGM-assessed SD [SDCGM] and CGM-assessed CV [CVCGM]) and time in range (TIRCGM) with carotid–femoral pulse wave velocity (cf-PWV), carotid distensibility coefficient, carotid intima–media thickness, ankle–brachial index and circumferential wall stress via multiple linear regression.ResultsHigher SDCGM was associated with higher cf-PWV after adjusting for demographics, cardiovascular risk factors and lifestyle factors (regression coefficient [B] per 1 mmol/l SDCGM [and corresponding 95% CI]: 0.413 m/s [0.147, 0.679], p = 0.002). In the model additionally adjusted for CGM-assessed mean sensor glucose (MSGCGM), SDCGM and MSGCGM contributed similarly to cf-PWV (respective standardised regression coefficients [st.βs] and 95% CIs of 0.065 [−0.018, 0.167], p = 0.160; and 0.059 [−0.043, 0.164], p = 0.272). In the fully adjusted models, both higher CVCGM (B [95% CI] per 10% CVCGM: 0.303 m/s [0.046, 0.559], p = 0.021) and lower TIRCGM (B [95% CI] per 10% TIRCGM: −0.145 m/s [−0.252, −0.038] p = 0.008) were statistically significantly associated with higher cf-PWV. Such consistent associations were not observed for the other arterial measures.ConclusionsOur findings show that greater daily glucose variability and lower TIRCGM are associated with greater aortic stiffness (cf-PWV) but not with other arterial measures. If corroborated in prospective studies, these results support the development of therapeutic agents that target both daily glucose variability and TIRCGM to prevent CVD.Graphical abstract

Sleep-wake characteristics, daytime sleepiness, and glycemia in young adults with type 1 diabetes.

The purpose of this study was to describe objective sleep-wake characteristics and glycemia over 7-14 days in young adults with type 1 diabetes. In addition, person-level associations among objective sleep-wake characteristics (total sleep time, sleep variability, and sleep fragmentation index), daytime sleepiness, and glycemia (glycemic control and glucose variability) were examined. In this cross-sectional study, objective sleep-wake characteristics were measured via actigraphy and glucose variability via continuous glucose monitoring over 6-14 days. At baseline, participants completed the Psychomotor Vigilance Test, the Trail Making Test, and questionnaires on daytime sleepiness, sleep quality, and sleep disturbance including sleep diaries. Forty-six participants (mean age, 22.3 ± 3.2 years) wore a wrist actigraph and underwent continuous glucose monitoring concurrently for 6-14 days. Greater sleep variability was directly associated with greater glucose variability (mean of daily differences; r = .33, P = .036). Higher daytime sleepiness was directly associated with greater glucose variability (mean of daily differences; r = .50, P = .001). The association between sleep variability and glucose variability (mean of daily differences) was no longer significant when accounting for daytime sleepiness and controlling for type 1 diabetes duration (P > .05). A higher sleep fragmentation index was associated with greater glucose variability (B = 1.27, P = .010, pr2 = 0.40) after controlling for type 1 diabetes duration and accounting for higher daytime sleepiness. Sleep-wake variability, sleep fragmentation, daytime sleepiness, and the associations with glycemia are new dimensions to consider in young adults with type 1 diabetes. Sleep habits in this population may explain higher glucose variability, and optimizing sleep may improve overall diabetes management. Griggs S, Hickman RL Jr, Strohl KP, Redeker NS, Crawford SL, Grey M. Sleep-wake characteristics, daytime sleepiness, and glycemia in young adults with type 1 diabetes. J Clin Sleep Med. 2021;17(9):1865-1874.

643 Rest Activity Rhythms, Symptom Burden, and Glucose Variability in Young Adults with Type 1 Diabetes

Abstract Introduction Circadian alignment is an important element in individual health, and one behavioral marker, rest-activity rhythm (RAR), may influence disease management in young adults with type 1 diabetes (T1D). Thus, in this descriptive study, we examined whether circadian rhythm is correlated with symptoms (emotional and diabetes distress, and diabetes physical symptom burden) and glucose variability in young adults with T1D. Methods Using convenience sampling, young adults with T1D underwent concurrent actigraphy and continuous glucose monitoring for 6–14 days to generate the following RAR parameters: (MESOR, amplitude, acrophase, and circadian quotient) and glucose variability indices (coefficient of variation and time in range). Participants completed the 8-item Epworth Sleepiness Scale, 8-item PROMIS v1.0 Emotional Distress Scale, 17-item Diabetes Distress Scale, and 34-item Diabetes Symptom Checklist-Revised. Cosinor analysis was used to compute the RAR parameters and linear regression modeling procedures were performed to determine the associations among the study variables. Results The sample included 46 young adults (mean age 22.3±3.2; 32.6% male; 84.8% non-Hispanic White, A1C mean 7.2±1.1%, BMI 27.0±4.4 kg/m2). A more robust rhythm (higher amplitude) was associated with a lower diabetes symptom burden (ß=-0.31, p=.035). A higher circadian quotient was associated with less daytime sleepiness (ß=-0.41, p=.004). All associations between the RAR parameters and symptom measures remained statistically significant (p<.05) after adjustment for sex and BMI. The associations between the RAR parameters and glucose variability indices were not significant. Conclusion RAR was associated with daytime sleepiness, as well as symptom burden in young adults with T1D even after consideration of sex and BMI. Future investigators should clarify the causality of these associations and the potential for improving the strength and stability of RAR in the mitigation of daytime sleepiness and symptoms. Support (if any) This research is or was partially supported by grants from the American Academy of Sleep Medicine (220-BS-19), National Institute of Nursing Research (K99NR018886 & T32NR0008346), Sigma Theta Tau International, and Dexcom provided continuous glucose monitors (G4) free of charge for participants who did not have a device.