Time In Tight Range in children and adolescents with type 1 diabetes: A cross-sectional observational single centre study evaluating efficacy of new advanced technologies.

INTRODUCTION: Early and tight glycaemic control is crucial to prevent long-term complications of Type 1 Diabetes (T1D). The aim of our study was to compare glucose metrics, including Time In Tight Range (TITR), in a real-world setting. METHODS: We performed a single-centre cross-sectional study in 534 children and adolescents with T1D. Participants were divided into four groups (multiple daily injections + real-time Continuous glucose monitoring (CGM), multiple daily injections + intermittently scanned CGM, sensor augmented pump (SAP), and Advanced Hybrid Closed-Loop (AHCL). Demographical and clinical data were collected and analysed. RESULTS: The group with AHCL showed significantly higher Time In Range (TIR) (71.31% ± 10.88) than SAP (57.82% ± 14.98; p < 0.001), MDI + rtCGM (54.56% ± 17.04; p < 0.001) and MDI + isCGM (52.17% ± 19.36; p < 0.001) groups with a lower Time Above Range (p < 0.001). The group with AHCL also showed lower Time Below Range than MDI + isCGM and SAP groups (p < 0.01). The overall TITR was 37% ± 14 with 19% of participants who reached a TITR ≥50% with a mean TIR of 81%. AHCL had significantly higher TITR (45.46% ± 11.77) than SAP (36.25% ± 13.53; p < 0.001), MDI + rtCGM (34.03% ± 13.89; p < 0.001) and MDI + isCGM (33.37% ± 15.84; p < 0.001) groups with a lower Coefficient of Variation (p < 0.001). CONCLUSIONS: Our study indicates that AHCL ensures a better glycaemic control with an improvement in both TIR and TITR, along with a reduction in CV. Implementation of automated insulin delivery systems should be considered in the treatment of children and adolescents with T1D.

Determinants of sub-optimal glycemic control among patients enrolled in a medicine dispensing programme in KwaZulu-Natal: A cohort study, 2018-2021.

BACKGROUND:  The Central Chronic Medicines Dispensing and Distribution (CCMDD) programme facilitates clinically stable patients to collect their chronic medication from community-based pick-up points. AIM:  We determined baseline glycaemic control and rates and predictors of becoming sub-optimally controlled for type 2 diabetes mellitus (T2DM) CCMDD-enrolled patients. SETTING:  The setting of the study was eThekwini, KwaZulu-Natal, South Africa. METHODS:  We performed a cohort study (April 2018- December 2021). We linked T2DM CCMDD-enrolled patients to glycated haemoglobin (HbA1c) data from the National Health Laboratory Service. We selected patients optimally controlled at their baseline HbA1c, with ≥ 1 repeat-test available. We used Kaplan-Meier analysis to assess survival rates and extended Cox regression to determine associations between time to sub-optimal control (HbA1c 7%) and predictors. Adjusted hazard ratios (aHRs), 95% confidence interval (CI), and p-values are reported. RESULTS:  Of the 41145 T2DM patients enrolled in the CCMDD programme, 7960 (19%) had a HbA1c result available. Twenty-seven percent (2147/7960) were optimally controlled at their baseline HbA1c. Of those controlled at baseline, 695 (32%) patients had a repeat test available, with 35% (242/695) changing to sub-optimal status. The HbA1c testing frequency as per national guidelines was associated with a lower hazard of sub-optimal glycaemic control (aHR: 0.46; 95% CI: 0.24-0.91; p-value = 0.024). Patients prescribed dual-therapy had a higher hazard of sub-optimal glycaemic control (aHR: 1.50; 95% CI: 1.16-1.95; p-value = 0.002) versus monotherapy. CONCLUSIONS:  The HbA1c monitoring, in-line with testing frequency guidelines, is needed to alert the CCMDD programme of patients who become ineligible for enrolment. Patients receiving dual-therapy require special consideration.Contribution: Addressing identified shortfalls can assist programme implementation.

Tirzepatide Reduces Fat Mass and Provides Good Glycaemic Control in Type 2 Diabetes Patients Undergoing Haemodialysis: A Single-Centre Retrospective Study.

OBJECTIVE: Tirzepatide is an injectable peptide approved by the US Food and Drug Administration for the treatment of Type 2 diabetes (T2DM). Its weight-loss effect primarily targets fat reduction; however, such effect on patients with chronic kidney disease (CKD) undergoing haemodialysis (HD) has not been reported. METHODS: Nine patients with CKD undergoing HD received weekly tirzepatide doses (2.5-7.5 mg) once a week. Evaluations encompassed tirzepatide's impact on dry weight (DW) and body composition assessed at baseline and study conclusion using bioelectrical impedance analysis. This longitudinal study included nine patients, with a median age of 53 years and median HD duration of 4 years. RESULTS: Tirzepatide treatment significantly decreased glycated albumin compared with the value at baseline (22.7 ± 5.4 vs. 18.3 ± 2.5%, p = 0.028, respectively). Significant reductions were observed in DW (-1.0 kg, p = 0.024) and body mass index (-0.6 kg/m2, p = 0.050) following tirzepatide administration. Total fat mass was also reduced, but not significantly (- 2.51% from baseline, p = 0.214). In contrast, skeletal muscle mass was not decreased (-1.02% from baseline, p = 0.722). No serious side effects other than nausea were observed during the study period. CONCLUSION: Tirzepatide effectively provides good glycaemic control in T2DM patients undergoing HD, decreasing DW by reducing body fat mass without increasing frailty risk.

Functional insulin therapy in type 1 diabetics: Short-term effects on weight and nutritional intake.

INTRODUCTION-AIM: Flexible insulin therapy is currently considered the gold standard therapy of type 1 diabetes. We aimed to study the evolution of glycemic control, weight and nutritional intake of a group of patients with type 1 diabetes, three months after the initiation of functional insulin therapy (FIT). METHODS: This was a prospective longitudinal study having included 30 type 1 diabetic patients hospitalized for education to FIT. Each patient underwent an assessment of glycemic control (glycated hemoglobin (A1C) and number of hypoglycemia), weight and nutritional intake before FIT and 3 months after the initiation of this educative approach. RESULTS: The mean age of patients was 21,8 ± 7,9 years and the sex ratio was 0,5. The mean duration of diabetes was 7,2 ± 6 years. Three months after initiation of FIT, we observed a significant lowering of A1C, which went from 9,2 ± 1,6% to 8,3 ± 1,4% (p<0,001) of the number of minor hypoglycemia (p=0,001) and that of severe hypoglycemia (p= 0,021). the average weight went from 64,6 ± 13,1 kg to 65,5 ± 13,5 kg (p = 0,040) with a significant increase in BMI (p = 0,041). Weight gain was observed in 67% of patients. This weight gain contrasted with a significant decrease in caloric (p = 0,040) and in carbohydrates intakes (p = 0,027). CONCLUSION: Weight gain, associated with better glycemic control, should encourage the healthcare team to strengthen therapeutic education of patients undergoing FIT in order to limit weight gain.

Glucagon-like-peptide-1 receptor agonists versus dipeptidyl peptidase-4 inhibitors and cardiovascular outcomes in diabetes in relation to achieved glycemic control. A Danish nationwide study.

AIM: To compare the cardiovascular preventive effect associated with glucagon-like-peptide-1 receptor agonists (GLP-1 RA) versus dipeptidyl peptidase-4 inhibitors (DPP-4i) according to the achieved target level of glycated hemoglobin (HbA1c). METHODS: We used retrospective Danish registries to include type 2 diabetes patients already in metformin treatment initiating GLP-1 RA or DPP-4i between 2007 and 2021. Patients were included 6 months after GLP-1 RA or DPP-4i initiation. The last available HbA1c measurement before inclusion was collected. The achieved HbA1c level was categorized according to a target level below or above 53 mmol/mol (7%). The primary outcome was a composite of nonfatal myocardial infarction, nonfatal stroke, and all-cause death. We used a multivariable Cox proportional hazard model to estimate the effect of HbA1c levels on the outcome among GLP-1 RA users compared to DPP-4i users. RESULTS: The study included 13 634 GLP-1 RA users (median age 56.9, interquartile range [IQR]: 48.5-65.5; 53% males) and 39 839 DPP-4i users (median age 63.4, IQR: 54.6-71.8; 61% males). The number of GLP-1 RA and DPP-4i users according to achieved HbA1c levels were as follows: HbA1c ≤ 53 mmol/mol (≤7.0%): 3026 (22%) versus 4824 (12%); HbA1c > 53 mmol/mol (>7.0%): 6577 (48%) versus 17 508 (44%); missing HbA1c: 4031 (30%) versus 17 507 (44%). During a median follow-up of 5 years (IQR: 2.6-5.0), 954 GLP-1 RA users experienced the primary outcome compared to 7093 DPP-4i users. The 5-year risk (95% confidence interval [CI]) of the outcome associated with GLP1-RA versus DPP-4i according to HbA1c categories was as follows: HbA1c ≤ 53 mmol/mol: 10.3% (8.2-12.3) versus 24.3% (22.7-25.8); HbA1c > 53 mmol/mol: 16.0% (14.3-17.6) versus 21.1% (20.3-21.9); missing HbA1c: 17.1% (15.7-18.5) versus 25.6% (24.9-26.3). The preventive effect associated with GLP-1 RA versus DPP-4i was significantly enhanced when achieving lower HbA1c levels: HbA1c ≤ 53 mmol/mol: 0.65 (0.52-0.80); HbA1c > 53 mmol/mol: 0.92 (0.83-1.03); missing HbA1c: 0.92 (0.84-1.02) (p value for interaction <.001). CONCLUSION: GLP-1 RA use was associated with a lower rate of major adverse cardiovascular outcomes. The association was stronger in patients achieving the target glycemic level and weaker in patients not achieving the target glycemic level, suggestive of an interaction between achieved HbA1c level and GLP-1 RA.

Ultra rapid lispro improves postprandial glucose control versus lispro in combination with basal insulin: a study based on CGM in type 2 diabetes in China.

Aim: To evaluate the efficacy and safety of URLi (ultra rapid lispro insulin) compared to insulin lispro as bolus insulin with basal insulin using CGM in the individuals with type 2 diabetes(T2D) in China. Methods: This was a double-blind, randomized, parallel, prospective, phase 3 study. Subjects with uncontrolled T2D were recruited and randomized 1:2 into the insulin lispro and URLi groups. Subjects received a consistent basal insulin regimen during the study and self-administered insulin lispro or URLi before each meal throughout the treatment period. Subjects underwent a 3-day continuous glucose monitoring (CGM) at the baseline and endpoint respectively, and then CGM data were analyzed. The primary endpoint was to compare the difference in postprandial glucose (PPG) control using CGM between the two groups. Results: A total of 57 subjects with T2D completed the study. Our CGM data showed that postprandial glucose excursions after breakfast (BPPGE) in the URLi group was lower than that in the insulin lispro group (1.59 ± 1.57 mmol/L vs 2.51 ± 1.73 mmol/L, p = 0.046). 1-hour PPG was observed to decrease more in the URLi group than that in the insulin lispro group (-1.37 ± 3.28 mmol/L vs 0.24 ± 2.58 mmol/L, p = 0.047). 2-hour PPG was observed to decrease more in the URLi group than that in the insulin lispro group (-1.12 ± 4.00 mmol/L vs 1.22 ± 2.90 mmol/L, p = 0.021). The mean HbA1c level decreased by 1.1% in the URLi group and 0.99% in the insulin lispro group, with no treatment difference (p = 0.642). In the CGM profile, TBR was not significantly different between the two groups (p = 0.743). The weight gain also did not differ between the two groups (p = 0.303). Conclusion: URLi can control breakfast PPG better than insulin lispro in adults with T2D in China, while it is non-inferior in improving HbA1c. The incidence of hypoglycemic and weight gain were similar between the two groups.

Comparing advanced hybrid closed loop therapy and standard insulin therapy in pregnant women with type 1 diabetes (CRISTAL): a parallel-group, open-label, randomised controlled trial.

BACKGROUND: Advanced hybrid closed loop (AHCL) therapy can improve glycaemic control in pregnant women with type 1 diabetes. However, data are needed on the efficacy and safety of AHCL systems as these systems, such as the MiniMed 780G, are not currently approved for use in pregnant women. We aimed to investigate whether the MiniMed 780G can improve glycaemic control with less hypoglycaemia in pregnant women with type 1 diabetes. METHODS: CRISTAL was a double-arm, parallel-group, open-label, randomised controlled trial conducted in secondary and tertiary care specialist endocrinology centres at 12 hospitals (11 in Belgium and one in the Netherlands). Pregnant women aged 18-45 years with type 1 diabetes were randomly assigned (1:1) to AHCL therapy (MiniMed 780G) or standard insulin therapy (standard of care) at a median of 10·1 (IQR 8·6-11·6) weeks of gestation. Randomisation was done centrally with minimisation dependent on baseline HbA1c, insulin administration method, and centre. Participants and study teams were not masked to group allocation. The primary outcome was proportion of time spent in the pregnancy-specific target glucose range (3·5-7·8 mmol/L), measured by continuous glucose monitoring (CGM) at 14-17 weeks, 20-23 weeks, 26-29 weeks, and 33-36 weeks. Key secondary outcomes were overnight time in target range, and time below glucose range (<3·5 mmol/L) overall and overnight. Analyses were conducted on an intention-to-treat basis. This trial is registered with ClinicalTrials.gov (NCT04520971). FINDINGS: Between Jan 15, 2021 and Sept 30, 2022, 101 participants were screened, and 95 were randomly assigned to AHCL therapy (n=46) or standard insulin therapy (n=49). 43 patients assigned to AHCL therapy and 46 assigned to standard insulin therapy completed the study. At baseline, 91 (95·8%) participants used insulin pumps, and the mean HbA1c was 6·5% (SD 0·6). The mean proportion of time spent in the target range (averaged over four time periods) was 66·5% (SD 10·0) in the AHCL therapy group compared with 63·2% (12·4) in the standard insulin therapy group (adjusted mean difference 1·88 percentage points [95% CI -0·82 to 4·58], p=0·17). Overnight time in the target range was higher (adjusted mean difference 6·58 percentage points [95% CI 2·31 to 10·85], p=0·0026), and time below range overall (adjusted mean difference -1·34 percentage points [95% CI, -2·19 to -0·49], p=0·0020) and overnight (adjusted mean difference -1·86 percentage points [95% CI -2·90 to -0·81], p=0·0005) were lower with AHCL therapy than with standard insulin therapy. Participants assigned to AHCL therapy reported higher treatment satisfaction. No unanticipated safety events occurred with AHCL therapy. INTERPRETATION: In pregnant women starting with tighter glycaemic control, AHCL therapy did not improve overall time in target range but improved overnight time in target range, reduced time below range, and improved treatment satisfaction. These data suggest that the MiniMed 780G can be safely used in pregnancy and provides some additional benefits compared with standard insulin therapy; however, it will be important to refine the algorithm to better align with pregnancy requirements. FUNDING: Diabetes Liga Research Fund and Medtronic.

The Impact of a Nutritional Intervention on Glycemic Control and Cardiovascular Risk Markers in Type 2 Diabetes.

INTRODUCTION: Nutritional management plays a crucial role in treating patients with type 2 diabetes (T2D), working to prevent and control the progression of chronic non-communicable diseases. OBJECTIVES: To evaluate the effects of individualized nutritional interventions on weight, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), fasting blood glucose (FBG), hemoglobin A1c (HbA1c), total cholesterol (TC), LDL cholesterol (LDL-C), HDL cholesterol (HDL-C), triglycerides (TGs), systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR)} over 12 months and subsequently at follow-up (15 months). METHODS: This longitudinal experimental study (without randomization and blinding) enrolled 84 sedentary participants with T2D (both sexes, aged 18-80 years). They were divided into a control group of 40 participants who received only medical consultations, and an intervention group of 44 participants who received the same medical care along with a nutritional assessment. Consultations occurred quarterly from August 2020 to November 2022 (first-twelfth month), with six to nine patients per session. Subsequently, a follow-up was conducted from December 2022 to November 2023, during which the intervention group had only medical care (during the 12th-15th months). Personalized dietary planning was inspired by the Mediterranean/DASH diets adapted to Brazilian foods and socioeconomic cultures. STATISTICAL ANALYSIS: Normal variables were compared between groups for each time point and also within each group across different time points using a two-way ANOVA (repeated measures for intragroup) followed by the Sídák post hoc test. Non-normal variables were compared between groups for each time point using Kruskal-Wallis followed by the Dunn post hoc test, and within each group across different time points using Friedman followed by the Dunn post hoc test. Data with a Gaussian distribution were presented as mean ± standard deviation (SD), and data with a non-Gaussian distribution were presented as median ± interquartile range (IQR). For all cases, α < 0.05 and p < 0.05 were adopted. RESULTS: In the intervention group, significant reductions were observed between the first and twelfth month for all parameters (p < 0.05), (except for TC), along with an increase in HDL-C (p = 0.0105). Conversely, in the control group, there was a significant increase in HbA1c, weight, BMI, FBG, and WHR (p < 0.05) between the first and twelfth months. Regarding the comparison between groups, there was a significant difference for all analyzed parameters (p < 0.05) from the first to the twelfth month. In the follow-up, differences were also observed (p < 0.05), except for BMI (p > 0.05). CONCLUSION: The individualized nutritional intervention improved eating habits, anthropometric, biochemical, and cardiovascular markers in T2D over 12 months, with sustained results during follow-up. The dietary plan inspired by the Mediterranean and DASH diets demonstrated good adaptation to the Brazilian food culture and the patients' socioeconomic contexts. Consistent monitoring and personalized nutritional management are essential for optimizing long-term outcomes. However, more clinical trials are necessary in order to optimize the level of evidence for longitudinal interventions.

Effects of Dietary Carbohydrate Concentration and Glycemic Index on Blood Glucose Variability and Free Fatty Acids in Individuals with Type 1 Diabetes.

Monitoring glycemic control status is the cornerstone of diabetes management. This study aimed to reveal whether moderate-carbohydrate (CHO) diets increase the risk of free fatty acid (FFA) levels, and it presents the short-term effects of four different diet models on blood sugar, glycemic variability (GV), and FFA levels. This crossover study included 17 patients with type 1 diabetes mellitus to identify the effects of four diets with different CHO contents and glycemic index (GI) on GV and plasma FFA levels. Diet 1 (D1) contained 40% CHO with a low GI, diet 2 (D2) contained 40% CHO with a high GI, diet 3 (D3) contained 60% CHO with a low GI, and diet 4 (D4) contained 60% CHO with a high GI. Interventions were performed with sensor monitoring in four-day periods and completed in four weeks. No statistical difference was observed among the groups in terms of blood glucose area under the curve (p = 0.78), mean blood glucose levels (p = 0.28), GV (p = 0.59), and time in range (p = 0.567). FFA and total triglyceride levels were higher in the D1 group (p < 0.014 and p = 0.002, respectively). Different diets may increase the risk of cardiovascular diseases by affecting GI, FFA, and blood glucose levels.

Study of Glycemic Variability in Well-controlled Type 2 Diabetic Patients Using Continuous Glucose Monitoring System.

INTRODUCTION: The world has changed tremendously for patients suffering from diabetes mellitus with the development of cutting-edge technologies like continuous glucose monitoring and flash glucose monitoring systems. Now, the details of constant fluctuations of glucose in their blood can be monitored not only by medical professionals but also by patients, and this is called glycemic variability (GV). Traditional metrics of glycemic control measurement, such as glycated hemoglobin (HbA1c), fail to reflect various short-term glycemic changes like postprandial hyperglycemia and hypoglycemic episodes, paving the way to the occurrence of various diabetic complications even in asymptomatic, well-controlled diabetic patients. This need for advanced management of diabetes and effective monitoring of these swings in blood glucose can be met by using a continuous glucose monitoring system (CGMS). AIM AND OBJECTIVE: To evaluate the extent of GV in well-controlled type 2 diabetes mellitus (T2DM) patients using a flash CGMS and to assess the correlation between GV and HbA1c. MATERIALS AND METHODS: A hospital-based prospective observational study was carried out from May 2020 to Oct 2021 at the Department of Medicine, SMS Hospital, Jaipur, Rajasthan (India), after approval from the Ethics Committee of the institution. A total of 30 patients with well-controlled T2DM (HbA1c was ≥6.5, but ≤7.5) were included in the study using simple random techniques after written informed consent from patients. Patients were studied for glycemic excursions over a period of 7 days by using FreeStyle® Libre Pro™, which is a flash glucose monitoring system. The CGM sensor was attached to the left upper arm of the patient on day 0 and removed on day 7. The data recorded in the sensor was then retrieved using pre-installed computer software and analyzed using standard CGM metrics like standard deviation (SD), percentage coefficient of variation (%CV), time above range (TAR), time below range (TBR), and time in range (TIR), out of which %CV was used to quantify GV. %CV has been used to cluster patients into four cohorts from best to worst, namely: best/low CV ≤ 10%, intermediate CV from 10 to 20%, high CV from 20 to 30%, and very high CV of >30%. Scatterplots are used to establish correlations between various parameters. RESULT: Data from a total of 30 patients were analyzed using CGMS and thus used for calculating standard CGM metrics; glucose readings every 15 minutes were recorded consecutively for 7-day periods, making it a total of 672 readings for each patient. Interpreting the CGM data of all 30 patients, the following results were found: the mean blood glucose of all cases is 134.925 ± 22.323 mg/dL, the mean SD of blood glucose of all cases is 35.348 ± 9.388 mg/dL, the mean of %CV of all cases is 26.376 ± 6.193%. CGM parameters of time are used in the form of percentages, and the following results were found: the mean of TAR, TBR, and TIR is 14.425 ± 13.211, 5.771 ± 6.808, and 82.594 ± 12.888%, respectively. Clustering the patients into cohorts, the proportion of patients exhibiting best/low %CV (10%) is 0, intermediate %CV (10-20%) is 16.67% (five out of 30 patients), high %CV (20-30%) is 50% (15 out of 30 patients) and very high %CV (>30%) is 33.33% (10 out of 30 patients). Also, there is no significant correlation found between HbA1c and %CV (ρ = 0.076, p-value = 0.690); a significant negative correlation was found between %CV and TIR (ρ = -0.604, p < 0.001S); a positive correlation of %CV with TAR and TBR is significant (ρ = 0.816, p-value of <0.001). CONCLUSION: Using a flash CGMS device and considering %CV as the parameter and primary measure of GV, the study demonstrated the overall instability of a person's glycemic control, making note of unrecognized events of hypoglycemia and hyperglycemia in asymptomatic well-controlled T2DM patients, revealing the overall volatile glycemic control. The most important finding of this study is that even those diabetics who are considered well-controlled experience a great degree of GV as assessed by CGM-derived metrics. This study also demonstrated that there is no significant correlation between HbA1c and GV, suggesting that patients may not have optimal control of their diabetes despite having "normal HbA1c" values; hence, GV can be considered an HbA1c-independent danger factor, having more harmful effects than sustained hyperglycemia in the growth of diabetic complications. So, by using CGM-derived metrics, the measurement of GV has the potential to complement HbA1c data. In this manner, a more comprehensive assessment of glycemic excursions can be provided for better treatment decisions, thereby facilitating optimal glycemic control, which is essential for reducing overall complications and promoting good quality of life.

Assessing glycemic variability in critically ill patients: A prospective cohort study comparing insulin infusion therapy with insulin sliding scale.

Glycemic variability (GV) has been associated with an increased mortality rate among critically ill patients. The clinical outcomes of having less GV even with slight hyperglycemia are better than those having tight glycemic control but higher GV. Insulin infusion remains the preferred method to control stress hyperglycemia in critically ill patients. However, its impacts on GV and clinical outcomes in critically ill patients still need further investigation. This study intended to evaluate the impact of insulin infusion therapy (IIT) compared to the insulin sliding scale (ISS) on the extent of GV and explore its impact on the clinical outcomes for critically ill patients. A prospective, single-center observational cohort study was conducted at a tertiary academic hospital in Saudi Arabia between March 2021 and November 2021. The study included adult patients admitted to ICUs who received insulin for stress hyperglycemia management. Patients were categorized into two groups based on the regimen of insulin therapy during ICU stay (IIT versus ISS). The primary outcome was the GV between the two groups. Secondary outcomes were ICU mortality, the incidence of hypoglycemia, and ICU length of stay (LOS). A total of 381 patients were screened; out of them, eighty patients met the eligibility criteria. The distribution of patients having diabetes and a history of insulin use was similar between the two groups. The GV was lower in the IIT group compared to the ISS group using CONGA (- 0.65, 95% CI [- 1.16, - 0.14], p-value = 0.01). Compared with ISS, patients who received IIT had a lower incidence of hypoglycemia that required correction (6.8% vs 2.77%; p-value = 0.38). In contrast, there were no significant differences in ICU LOS and ICU mortality between the two groups. Our study demonstrated that the IIT is associated with decreased GV significantly in critically ill patients without increasing the incidence of severe hypoglycemia. There is no survival benefit with the use of the IIT. Further studies with larger sample size are required to confirm our findings and elaborate on IIT's potential effect in reducing ICU complications in critically ill patients.

A randomized controlled trial of an app-based intervention on physical activity and glycemic control in people with type 2 diabetes.

BACKGROUND: We investigated the effects of a physical activity encouragement intervention based on a smartphone personal health record (PHR) application (app) on step count increases, glycemic control, and body weight in patients with type 2 diabetes (T2D). METHODS: In this 12-week, single-center, randomized controlled, 12-week extension study, patients with T2D who were overweight or obese were randomized using ratio 1:2 to a group using a smartphone PHR app (control group) or group using the app and received individualized motivational text messages (intervention group) for 12 weeks. During the extension period, the sending of the encouraging text messages to the intervention group was discontinued. The primary outcome was a change in daily step count after 12 weeks and analyzed by independent t-test. The secondary outcomes included HbA1c, fasting glucose, and body weight analyzed by paired or independent t-test. RESULTS: Of 200 participants, 62 (93.9%) and 118 (88.1%) in the control and intervention group, respectively, completed the 12-week main study. The change in daily step count from baseline to week 12 was not significantly different between the two groups (P = 0.365). Among participants with baseline step counts < 7,500 steps per day, the change in the mean daily step count at week 12 in the intervention group (1,319 ± 3,020) was significantly larger than that in control group (-139 ± 2,309) (P = 0.009). At week 12, HbA1c in the intervention group (6.7 ± 0.5%) was significantly lower than that in control group (6.9 ± 0.6%, P = 0.041) and at week 24, changes in HbA1c from baseline were significant in both groups but, comparable between groups. Decrease in HbA1c from baseline to week 12 of intervention group was greater in participants with baseline HbA1c ≥ 7.5% (-0.81 ± 0.84%) compared with those with baseline HbA1c < 7.5% (-0.22 ± 0.39%) (P for interaction = 0.014). A significant reduction in body weight from baseline to week 24 was observed in both groups without significant between-group differences (P = 0.370). CONCLUSIONS: App-based individualized motivational intervention for physical activity did not increase daily step count from baseline to week 12, and the changes in HbA1c levels from baseline to week 12 were comparable. TRIAL REGISTRATION: ClinicalTrials.gov (NCT03407222).

Characterization of tirzepatide-treated patients achieving different glycemic control levels in SURPASS-AP-Combo.

OBJECTIVE: The study objective was to characterize subgroups of Asia-Pacific patients with type 2 diabetes who achieved different glycated hemoglobin (HbA1c) targets on tirzepatide treatment. METHODS: This was a post hoc analysis of the SURPASS AP-Combo study. Baseline characteristics, changes in metabolic markers, and safety were compared between tirzepatide-treated patients achieving HbA1c <7.0% (<53 mmol/mol) and those achieving ≥7.0% (≥53 mmol/mol) at week 40. Among patients achieving HbA1c <7.0% (<53 mmol/mol), further comparisons were conducted among subgroups achieving HbA1c <5.7% (<39 mmol/mol), 5.7% to 6.5% (39 to 48 mmol/mol), and >6.5% to <7.0% (>48 to <53 mmol/mol). RESULTS: Five hundred ninety-eight patients on tirzepatide treatment without rescue medication were included (56.9% male; mean age: 53.1 years; mean baseline HbA1c: 8.7% [71.6 mmol/mol]). Patients achieving HbA1c <7.0% (<53 mmol/mol) versus ≥7.0% (≥53 mmol/mol) were slightly younger with a shorter disease duration and lower HbA1c at baseline, and they had greater improvements in HbA1c, fasting serum glucose, body weight, BMI, waist circumference, waist-height ratio, diastolic blood pressure, lipids, and self-monitored blood glucose at week 40. Patients achieving HbA1c <5.7% (<39 mmol/mol) versus those achieving 5.7% to 6.5% (39 to 48 mmol/mol) and those achieving >6.5% to <7.0% (>48 to <53 mmol/mol) were much younger, had much lower HbA1c, and had further improvements in metabolic markers. Tirzepatide treatment was well tolerated irrespective of the HbA1c level achieved, with a low incidence of hypoglycemic events. CONCLUSIONS: These findings may help to inform clinical decisions in Asia-Pacific patients with type 2 diabetes.

Long-term assessment of the NHS hybrid closed-loop real-world study on glycaemic outcomes, time-in-range, and quality of life in children and young people with type 1 diabetes.

Hybrid closed-loop (HCL) systems seamlessly interface continuous glucose monitoring (CGM) with insulin pumps, employing specialised algorithms and user-initiated automated insulin delivery. This study aimed to assess the efficacy of HCLs at 12 months post-initiation on glycated haemoglobin (HbA1c), time-in-range (TIR), hypoglycaemia frequency, and quality of life measures among children and young people (CYP) with type 1 diabetes mellitus (T1DM) and their caregivers in a real-world setting. Conducted between August 1, 2021, and December 10, 2022, the prospective recruitment took place in eight paediatric diabetes centres across England under the National Health Service England's (NHSE) HCL pilot real-world study. A cohort of 251 CYP (58% males, mean age 12.3 years) with T1DM participated (89% white, 3% Asian, 4% black, 3% mixed ethnicity, and 1% other). The study utilised three HCL systems: (1) Tandem Control-IQ AP system, which uses the Tandem t:slim X2 insulin pump (Tandem Diabetes Care, San Diego, CA, USA) with the Dexcom G6® CGM (Dexcom, San Diego, CA, USA) sensor; (2) Medtronic MiniMed™ 780G with the Guardian 4 sensor (Medtronic, Northridge, CA, USA); and (3) the CamAPS FX (CamDiab, Cambridge, UK) with the Ypsomed insulin pump (Ypsomed Ltd, Escrick, UK) and Dexcom G6® CGM.All systems were fully funded by the NHS. Results demonstrated significant improvements in HbA1c (average reduction at 12 months 7 mmol/mol; P < 0.001), time-in-range (TIR) (average increase 13.4%; P < 0.001), hypoglycaemia frequency (50% reduction), hypoglycaemia fear, and quality of sleep (P < 0.001) among CYP over a 12-month period of HCL usage. Additionally, parents and carers experienced improvements in hypoglycaemia fear and quality of sleep after 6 and 12 months of use. In addition to the improvements in glycaemic management, these findings underscore the positive impact of HCL systems on both the well-being of CYP with T1DM and the individuals caring for them.

Continuous subcutaneous insulin infusion versus multiple daily injection therapy in pregnant women with type 1 diabetes.

INTRODUCTION: The study aimed to compare glycemic control and pregnancy outcomes in women with type 1 diabetes mellitus (T1DM) using multiple daily injection therapy (MDI) and continuous subcutaneous insulin infusion (CSII) and to compare outcomes of women treated with long-acting insulin or neutral protamine Hagedorn (NPH). METHODS: This multicenter prospective cohort study involved women with pregestational T1DM treated with MDI and CSII. Primary outcome was glycated hemoglobin (HbA1c) before and during pregnancy. Secondary outcomes included maternal and neonatal outcomes and quality of life. RESULTS: Of the 121 studied women, the average age was 28.48 years, and the average body mass index was 21.29 kg/m2 at conception and 26.32 kg/m2 at delivery. Of the studied women, 78.51% had planned pregnancy. Women treated with MDI and CSII had comparable HbA1c before pregnancy or in the first and second trimesters. In the third trimester, women on CSII therapy had significantly lower HbA1c (6.07 ± 0.62 vs 6.20 ± 0.88%, p = .017), higher HbA1c on-target rate (71.43% vs 64.62%, p = .030), and greater decline of HbA1c from preconception to the third trimester (-0.65 vs -0.30%, p = .047). Fewer daily insulin requirements were observed in those used CSII compared with MDI-treated women (0.60 ± 0.22 vs 0.73 ± 0.25 U/kg/day, p = .004). Newborns born of mothers treated with the CSII method were more likely to have neonatal jaundice (adjusted odds ratio [OR] 2.76, 95% confidence interval [CI] 1.16-6.57) and neonatal intensive care unit (adjusted OR 3.73, 95%CI 1.24-11.16), and women on CSII had lower scores in patient-reported quality of life (p = .045). In the MDI group, those receiving long-acting insulin had nonsignificant lower HbA1c and higher HbA1c on-target rate in the second and third trimesters, compared with those treated with NPH. CONCLUSIONS: Insulin pump users may achieve better glycemic control than multiple daily insulin injections, which did not substantially improve pregnancy outcome.

Intermittently scanned continuous glucose monitoring provides no benefit over structured self-monitoring of blood glucose in type 2 diabetes not on prandial insulin, in the context of diabetes self-management education: GLucose monitoring programme SingaporE (GLiMPSE).

OBJECTIVE: We evaluated the impact of intermittently scanned continuous glucose monitoring(is-CGM)over self-monitoring of blood glucose(SMBG) in the context of diabetes self-management education (DSME) in sub-optimally controlled type 2 diabetes(T2D) in a multi-ethnicsetting. RESEARCH DESIGN AND METHOD: Randomized-controlled, open-label trial (NCT04564911), of T2D with HbA1c ≥ 7.5-≤10 %, on oral agents with/without basal insulin was carried out. Intervention arm received 6 weeks(w) continuous is-CGM, followed by one is-CGM/month till 24w. Control arm was advised to perform 4 SMBG/day. Educationwas delivered at weeks 0, 2, 8, 16. PRIMARY OUTCOME: Change in HbA1c from baseline at 24w. Modified intention-to-treat (mITT) analysis with linear mixed-effect model for repeated measurementswas performed. RESULTS: 176 subjects, age 55 ± 10.7 years(y), DM duration 11 ± 7.3y, BMI 27.8 ± 5.9 kg/m2, 58 % Male, 29.5 % basal insulin users were analysed. Within each arm,from baseline to 24w, mean HbA1c decreasedby -0.6 % (-6.6.mmol/mol, p-value < 0.01)and weight decreased(isCGM: -1.44 kg; SMBG: -1.25 kg, both p < 0.01). These changes were sustained to one year. However, there wasno significant difference in these parameters between arms (p-value > 0.05). CONCLUSION: In the context of DSME, use of either SMBG or is-CGM led to improved glycaemia and reduced weight over a period of 24 weeks, sustained to one year.

Role of nutritional therapy on dietary habits and glycemic control in insulin-treated kidney transplant patients with diabetes.

AIMS: To evaluate the effect of nutritional therapy on glycemic compensation and key cardio-renal risk markers in patients with diabetes and kidney transplant, on insulin treatment by Multiple Daily Injection (MDI) or Continuous Subcutaneous Insulin Infusion (CSII). METHODS: 34 patients with diabetes on insulin treatment and kidney transplant recipients were enrolled;12 participated in the structured nutritional program (intervention group), 22 patients (control group) did not receive nutritional protocol. Both groups were then divided into subgroups according to the method of insulin administration (MDI and CSII). RESULTS: Statistically significant reduction in fasting blood glucose values, glycosylated hemoglobin (HbA1c) and glycosuria were observed in both groups at the end of the study. The intervention group, significantly reduced total cholesterolemia and the glycemic index, together with reduced dietary intake of lipids, cholesterol, soluble carbohydrates and increased consumption of carbohydrates and fiber. These improvements were even more pronounced in patients treated with CSII. CONCLUSIONS: A proper nutritional approach optimize glycometabolic outcomes and contribute significantly to the reduction of the major cardiovascular risk factors in renal transplant patients.

Management of diabetes mellitus patients with sickle cell anemia: Challenges and therapeutic approaches.

The coexistence of diabetes mellitus (DM) and sickle cell anemia (SCA) poses significant challenges in clinical management due to the complex interactions and overlapping complications associated with both conditions. Managing diabetes in individuals with SCA requires a comprehensive approach that addresses the unique physiological and pathological aspects of both diseases. This paper reviews the challenges encountered in the management of DM in patients with SCA and explores therapeutic strategies and approaches to optimize patient care. Challenges in the management of DM in individuals with SCA stem from several factors, including the impact of hemoglobin variants on glycemic control assessment, increased susceptibility to infections, altered immune response, and complications associated with both diseases. Moreover, the coexistence of SCA and DM heightens the susceptibility to infections due to compromised immune function, emphasizing the need for vigilant preventive measures, including vaccinations and close monitoring for infectious complications. Close collaboration among healthcare providers specializing in diabetes, hematology, and other relevant fields is crucial for developing comprehensive care plans. Individualized treatment strategies that balance glycemic control, pain management, and preventive care are essential to mitigate complications and optimize the overall health outcomes of patients with both DM and SCA. In conclusion, managing diabetes in the context of SCA necessitates a nuanced and patient-centered approach. By addressing the challenges and employing tailored therapeutic strategies, healthcare providers can improve the quality of life and health outcomes for individuals affected by both conditions.

Effects of whole grains on glycemic control: a systematic review and dose-response meta-analysis of prospective cohort studies and randomized controlled trials.

PURPOSE: Whole grains have recently been promoted as beneficial to diabetes prevention. However, the evidence for the glycemic benefits of whole grains seems to conflict between the cohort studies and randomized control trials (RCTs). To fill the research gap, we conducted a meta-analysis to determine the effects of whole grains on diabetes prevention and to inform recommendations. METHODS: We searched PubMed, Clarivate Web of Science, and Cochrane Library until March 2024. We used the risk ratio (RR) of type 2 diabetes to represent the clinical outcomes for cohort studies, while the biomarkers, including fasting blood glucose and insulin, HbA1C, and HOMA-IR, were utilized to show outcomes for RCTs. Dose-response relationships between whole grain intakes and outcomes were tested with random effects meta-regression models and restricted cubic splines models. This study is registered with PROSPERO, CRD42021281639. RESULTS: Ten prospective cohort studies and 37 RCTs were included. Cohort studies suggested a 50 g/day whole grain intake reduced the risk of type 2 diabetes (RR = 0.761, 95% CI: 0.700 to 0.828, I2 = 72.39%, P < 0.001) and indicated a monotonic inverse relationship between whole grains and type 2 diabetes rate. In RCTs, whole grains significantly reduced fasting blood glucose (Mean difference (MD) = -0.103 mmol/L, 95% CI: -0.178 to -0.028; I2 = 72.99%, P < 0.01) and had modest effects on HbA1C (MD = -0.662 mmol/mol (-0.06%), 95% CI: -1.335 to 0.010; I2 = 64.55%, P = 0.05) and HOMA-IR (MD = -0.164, 95% CI: -0.342 to 0.013; I2 = 33.38%, P = 0.07). The intake of whole grains and FBG, HbA1C, and HOMA-IR were significantly dose-dependent. The restricted spline curves remained flat up to 150 g/day and decreased afterward. Subgroup analysis showed that interventions with multiple whole-grain types were more effective than those with a single type. CONCLUSION: Our study findings suggest that a daily intake of more than 150 g of whole grain ingredients is recommended as a population approach for diabetes prevention.