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.

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).

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.

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.

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.

Exercise Prescription for Postprandial Glycemic Management.

The detrimental impacts of postprandial hyperglycemia on health are a critical concern, and exercise is recognized a pivotal tool in enhancing glycemic control after a meal. However, current exercise recommendations for managing postprandial glucose levels remain fairly broad and require deeper clarification. This review examines the existing literature aiming to offer a comprehensive guide for exercise prescription to optimize postprandial glycemic management. Specifically, it considers various exercise parameters (i.e., exercise timing, type, intensity, volume, pattern) for crafting exercise prescriptions. Findings predominantly indicate that moderate-intensity exercise initiated shortly after meals may substantially improve glucose response to a meal in healthy individuals and those with type 2 diabetes. Moreover, incorporating short activity breaks throughout the exercise session may provide additional benefits for reducing glucose response.

Tailored Meal-Type Food Provision for Diabetes Patients Can Improve Routine Blood Glucose Management in Patients with Type 2 Diabetes: A Crossover Study.

This study aimed to determine whether patients with type 2 diabetes can benefit from a meal plan designed based on diabetes management guidelines to improve blood glucose levels. Participants were divided into intervention and control groups. The intervention group consumed a diabetic diet for 2 weeks, while the control group consumed their normal diet. After 2 weeks, the groups switched their dietary regimens. The participants' demographic and clinical characteristics were evaluated, including factors such as blood pressure, blood lipid levels, weight and waist circumference, blood glucose levels (self-monitored and continuously monitored), nutritional status, and blood-based markers of nutrient intake. The dietary intervention group improved waist circumference, body fat percentage, low-density lipoprotein cholesterol, triglyceride levels, and glucose. The energy composition ratio of carbohydrates and proteins changed favorably, and sugar intake decreased. In addition, the proportion of continuous glucose monitoring readings within the range of 180-250 mg/dL was relatively lower in the intervention group than that of the control group. Meals designed based on diabetes management guidelines can improve clinical factors, including stable blood glucose levels in daily life, significantly decrease the carbohydrate energy ratio, and increase the protein energy ratio. This study can help determine the role of dietary interventions in diabetes management and outcomes.

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.

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.

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.

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.

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.

Novel Automated Self-adjusting Subcutaneous Insulin Algorithm Improves Glycemic Control and Physician Efficiency in Hospitalized Patients.

BACKGROUND: Hyperglycemia occurs in 22% to 46% of hospitalized patients, negatively affecting patient outcomes, including mortality, inpatient complications, length of stay, and hospital costs. Achieving inpatient glycemic control is challenging due to inconsistent caloric intake, changes from home medications, a catabolic state in the setting of acute illness, consequences of acute inflammation, intercurrent infection, and limitations in labor-intensive glucose monitoring and insulin administration. METHOD: We conducted a retrospective cross-sectional analysis at the University of California San Francisco hospitals between September 3, 2020 and September 2, 2021, comparing point-of-care glucose measurements in patients on nil per os (NPO), continuous total parenteral nutrition, or continuous tube feeding assigned to our novel automated self-adjusting subcutaneous insulin algorithm (SQIA) or conventional, physician-driven insulin dosing. We also evaluated physician efficiency by tracking the number of insulin orders placed or modified. RESULTS: The proportion of glucose in range (70-180 mg/dL) was higher in the SQIA group than in the conventional group (71.0% vs 69.0%, P = .153). The SQIA led to a lower proportion of severe hyperglycemia (>250 mg/dL; 5.8% vs 7.2%, P = .017), hypoglycemia (54-69 mg/dL; 0.8% vs 1.2%, P = .029), and severe hypoglycemia (<54 mg/dL; 0.3% vs 0.5%, P = .076) events. The number of orders a physician had to place while a patient was on the SQIA was reduced by a factor of more than 12, when compared with while a patient was on conventional insulin dosing. CONCLUSIONS: The SQIA reduced severe hyperglycemia, hypoglycemia, and severe hypoglycemia compared with conventional insulin dosing. It also improved physician efficiency by reducing the number of order modifications a physician had to place.

Ingesting probiotic yogurt containing Lactiplantibacillus plantarum OLL2712 improves glycaemic control in adults with prediabetes in a randomized, double-blind, placebo-controlled trial.

AIM: The ingestion of Lactiplantibacillus plantarum OLL2712 (OLL2712) cells has been shown to improve glucose metabolism by suppressing chronic inflammation in murine models and clinical studies. This study aimed to clarify the effect of OLL2712 on glycaemic control in healthy adults with prediabetes. MATERIALS AND METHODS: The study was a randomized, double-blind, placebo-controlled, parallel-group design. Adult participants with prediabetes [n = 148, glycated haemoglobin (HbA1c) range: 5.6%-6.4%, age range: 20-64 years] were assigned randomly to placebo or OLL2712 groups (n = 74/group) and administered daily for 12 weeks either conventional yogurt or yogurt containing >5 × 109 heat-treated OLL2712 cells, respectively. In addition, the participants were followed for 8 weeks after the discontinuation of either yogurt. The primary outcome was the changes in HbA1c levels at weeks 12 and 16 by analysis of covariance. RESULTS: The levels of HbA1c and glycoalbumin decreased significantly in both groups at week 12 in comparison with those at week 0, but only in the OLL2712 group at week 16. HbA1c levels decreased significantly at weeks 12 and 16 in the OLL2712 group in comparison with the placebo group (p = .014 and p = .006, respectively). No significant inter- and intragroup differences in HbA1c levels were observed at week 20. CONCLUSIONS: The ingestion of OLL2712 prevents the deterioration of glycaemic control and maintains the HbA1c levels within the normal range in adults with prediabetes; yogurt probably exhibits similar effects, which may contribute to reducing the risk of developing type 2 diabetes.