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.

Application of machine learning in affordable and accessible insulin management for type 1 and 2 diabetes: A comprehensive review.

Proper insulin management is vital for maintaining stable blood sugar levels and preventing complications associated with diabetes. However, the soaring costs of insulin present significant challenges to ensuring affordable management. This paper conducts a comprehensive review of current literature on the application of machine learning (ML) in insulin management for diabetes patients, particularly focusing on enhancing affordability and accessibility within the United States. The review encompasses various facets of insulin management, including dosage calculation and response, prediction of blood glucose and insulin sensitivity, initial insulin estimation, resistance prediction, treatment adherence, complications, hypoglycemia prediction, and lifestyle modifications. Additionally, the study identifies key limitations in the utilization of ML within the insulin management literature and suggests future research directions aimed at furthering accessible and affordable insulin treatments. These proposed directions include exploring insurance coverage, optimizing insulin type selection, assessing the impact of biosimilar insulin and market competition, considering mental health factors, evaluating insulin delivery options, addressing cost-related issues affecting insulin usage and adherence, and selecting appropriate patient cost-sharing programs. By examining the potential of ML in addressing insulin management affordability and accessibility, this work aims to envision improved and cost-effective insulin management practices. It not only highlights existing research gaps but also offers insights into future directions, guiding the development of innovative solutions that have the potential to revolutionize insulin management and benefit patients reliant on this life-saving treatment.

Estimated Sustainable Cost-Based Prices for Diabetes Medicines.

Importance: The burden of diabetes is growing worldwide. The costs associated with diabetes put substantial pressure on patients and health budgets, especially in low- and middle-income countries. The prices of diabetes medicines are a key determinant for access, yet little is known about the association between manufacturing costs and current market prices. Objectives: To estimate the cost of manufacturing insulins, sodium-glucose cotransporter 2 inhibitors (SGLT2Is), and glucagonlike peptide 1 agonists (GLP1As), derive sustainable cost-based prices (CBPs), and compare these with current market prices. Design, Setting, and Participants: In this economic evaluation, the cost of manufacturing insulins, SGLT2Is, and GLP1As was modeled. Active pharmaceutical ingredient cost per unit (weighted least-squares regression model using data from a commercial database of trade shipments, data from January 1, 2016, to March 31, 2023) was combined with costs of formulation and other operating expenses, plus a profit margin with an allowance for tax, to estimate CBPs. Cost-based prices were compared with current prices in 13 countries, collected in January 2023 from public databases. Countries were selected to provide representation of different income levels and geographic regions based on the availability of public databases. Main Outcomes and Measures: Estimated CBPs; lowest current market prices (2023 US dollars). Results: In this economic evaluation of manufacturing costs, estimated CBPs for treatment with insulin in a reusable pen device could be as low as $96 (human insulin) or $111 (insulin analogues) per year for a basal-bolus regimen, $61 per year using twice-daily injections of mixed human insulin, and $50 (human insulin) or $72 (insulin analogues) per year for a once-daily basal insulin injection (for type 2 diabetes), including the cost of injection devices and needles. Cost-based prices ranged from $1.30 to $3.45 per month for SGLT2Is (except canagliflozin: $25.00-$46.79) and from $0.75 to $72.49 per month for GLP1As. These CBPs were substantially lower than current prices in the 13 countries surveyed. Conclusions and Relevance: High prices limit access to newer diabetes medicines in many countries. The findings of this study suggest that robust generic and biosimilar competition could reduce prices to more affordable levels and enable expansion of diabetes treatment globally.

Association of State Insulin Out-of-Pocket Caps With Insulin Cost-Sharing and Use Among Commercially Insured Patients With Diabetes : A Pre-Post Study With a Control Group.

BACKGROUND: Twenty-five states have implemented insulin out-of-pocket (OOP) cost caps, but their effectiveness is uncertain. OBJECTIVE: To examine the effect of state insulin OOP caps on insulin use and OOP costs among commercially insured persons with diabetes. DESIGN: Pre-post study with control group. SETTING: Eight states implementing insulin OOP caps of $25 to $30, $50, or $100 in January 2021, and 17 control states. PARTICIPANTS: Commercially insured persons with diabetes and insulin users younger than 65 years. Subgroups of particular interest included members from states with insulin OOP caps of $25 to $30, enrollees with health savings accounts (HSAs) that require high insulin OOP payments, and lower-income members. MEASUREMENTS: Mean monthly 30-day insulin fills and OOP costs. RESULTS: State insulin caps were not associated with changes in insulin use in the overall population (relative change in fills per month, 1.8% [95% CI, -3.2% to 6.9%]). Insulin users in intervention states saw a 17.4% (CI, -23.9% to -10.9%) relative reduction in insulin OOP costs, largely driven by reductions among HSA enrollees; there was no difference in OOP costs among nonaccount plan members. More generous ($25 to $30) state insulin OOP caps were associated with insulin OOP cost reductions of 40.0% (CI, -62.5% to -17.6%), again primarily driven by a larger reduction in the subgroup with HSA plans. LIMITATIONS: Single national insurer; 9-month follow-up. CONCLUSION: Insulin OOP caps were associated with reduced insulin OOP costs but no overall increases in insulin use. A proposed national insulin cap of $35 for commercially insured persons might lead to meaningful insulin OOP savings but have a limited effect on insulin use. PRIMARY FUNDING SOURCE: Centers for Disease Control and Prevention and National Institute of Diabetes and Digestive and Kidney Diseases.

Out-of-pocket costs for diabetes medications in employer-sponsored health insurance plans.

Out-of-pocket costs of diabetes medications other than insulin can be quite high for individuals with employer-sponsored health insurance.

A short-term economic evaluation of early insulin therapy compared to oral anti-diabetic drugs in order to reduce the major adverse events in type 2 diabetes patients in Iran.

OBJECTIVE: While there are some recommendations about early insulin therapy in newly diagnosed Type 2 Diabetes Mellitus (T2DM) patients, there is not sufficient evidence on this strategy's cost-effectiveness. This study compared early insulin therapy versus oral anti-diabetic drugs (OADs) for managing T2DMusing a cost-effectiveness analysis approach in Iran. METHODS: In this economic evaluation, a decision analytic model was designed. The target population was newly diagnosed type 2 diabetic patients, and the study was carried out from the perspective of Iran's healthcare system with a one-year time horizon. Basal insulin, Dipeptidyl peptidase-4 (DPP-4) inhibitors, and Thiazolidinediones (TZDs) were compared in this evaluation. The main outcome for assessing the effectiveness of each intervention was the reduction in the occurrence of diabetes complications. Strategies were compared using the incremental cost-effectiveness ratio (ICER), and deterministic and probabilistic sensitivity analyses were carried out. RESULTS: The DPP-4 inhibitors strategy was the dominant strategy with the highest effectiveness and the lowest cost. Early insulin therapy was dominated (ICER: $-53,703.18), meaning that it was not cost-effective. The sensitivity analyses consistently affirmed the robustness of the base case findings. The probabilistic sensitivity analysis indicated probabilities of 77%, 22%, and 1% for DPP-4 inhibitors, TZDs strategies, and early insulin therapy, respectively, in terms of being cost-effective. CONCLUSION: In terms of cost-effectiveness, early insulin therapy was not cost-effective compared to OADs for managing newly diagnosed T2DM patients. Future studies in this regard, utilizing more comprehensive evidence, can yield more accurate results.

Alisol B 23-acetate promotes white adipose tissue browning to mitigate high-fat diet-induced obesity by regulating mTOR-SREBP1 signaling.

OBJECTIVE: Obesity is a global health concern with management strategies encompassing bariatric surgery and anti-obesity drugs; however, concerns regarding complexities and side effects persist, driving research for more effective, low-risk strategies. The promotion of white adipose tissue (WAT) browning has emerged as a promising approach. Moreover, alisol B 23-acetate (AB23A) has demonstrated efficacy in addressing metabolic disorders, suggesting its potential as a therapeutic agent in obesity management. Therefore, in this study, we aimed to investigate the therapeutic potential of AB23A for mitigating obesity by regulating metabolic phenotypes and lipid distribution in mice fed a high-fat diet (HFD). METHODS: An obesity mouse model was established by administration of an HFD. Glucose and insulin metabolism were assessed via glucose and insulin tolerance tests. Adipocyte size was determined using hematoxylin and eosin staining. The expression of browning markers in WAT was evaluated using Western blotting and quantitative real-time polymerase chain reaction. Metabolic cage monitoring involved the assessment of various parameters, including food and water intake, energy metabolism, respiratory exchange rates, and physical activity. Moreover, oil red O staining was used to evaluate intracellular lipid accumulation. A bioinformatic analysis tool for identifying the molecular mechanisms of traditional Chinese medicine was used to examine AB23A targets and associated signaling pathways. RESULTS: AB23A administration significantly reduced the weight of obese mice, decreased the mass of inguinal WAT, epididymal WAT, and perirenal adipose tissue, improved glucose and insulin metabolism, and reduced adipocyte size. Moreover, treatment with AB23A promoted the expression of browning markers in WAT, enhanced overall energy metabolism in mice, and had no discernible effect on food intake, water consumption, or physical activity. In 3T3-L1 cells, AB23A inhibited lipid accumulation, and both AB23A and rapamycin inhibited the mammalian target of rapamycin-sterol regulatory element-binding protein-1 (mTOR-SREBP1) signaling pathway. Furthermore, 3-isobutyl-1-methylxanthine, dexamethasone and insulin, at concentrations of 0.25 mmol/L, 0.25 µmol/L and 1 µg/mL, respectively, induced activation of the mTOR-SREBP1 signaling pathway, which was further strengthened by an mTOR activator MHY1485. Notably, MHY1485 reversed the beneficial effects of AB23A in 3T3-L1 cells. CONCLUSION: AB23A promoted WAT browning by inhibiting the mTOR-SREBP1 signaling pathway, offering a potential strategy to prevent obesity. Please cite this article as: Han LL, Zhang X, Zhang H, Li T, Zhao YC, Tian MH, Sun FL, Feng B. Alisol B 23-acetate promotes white adipose tissue browning to mitigate high-fat diet-induced obesity by regulating mTOR-SREBP1 signaling. J Integr Med. 2024; 22(1): 83-92.

Development and validation of machine learning-augmented algorithm for insulin sensitivity assessment in the community and primary care settings: a population-based study in China.

Objective: Insulin plays a central role in the regulation of energy and glucose homeostasis, and insulin resistance (IR) is widely considered as the "common soil" of a cluster of cardiometabolic disorders. Assessment of insulin sensitivity is very important in preventing and treating IR-related disease. This study aims to develop and validate machine learning (ML)-augmented algorithms for insulin sensitivity assessment in the community and primary care settings. Methods: We analyzed the data of 9358 participants over 40 years old who participated in the population-based cohort of the Hubei center of the REACTION study (Risk Evaluation of Cancers in Chinese Diabetic Individuals). Three non-ensemble algorithms and four ensemble algorithms were used to develop the models with 70 non-laboratory variables for the community and 87 (70 non-laboratory and 17 laboratory) variables for the primary care settings to screen the classifier of the state-of-the-art. The models with the best performance were further streamlined using top-ranked 5, 8, 10, 13, 15, and 20 features. Performances of these ML models were evaluated using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPR), and the Brier score. The Shapley additive explanation (SHAP) analysis was employed to evaluate the importance of features and interpret the models. Results: The LightGBM models developed for the community (AUROC 0.794, AUPR 0.575, Brier score 0.145) and primary care settings (AUROC 0.867, AUPR 0.705, Brier score 0.119) achieved higher performance than the models constructed by the other six algorithms. The streamlined LightGBM models for the community (AUROC 0.791, AUPR 0.563, Brier score 0.146) and primary care settings (AUROC 0.863, AUPR 0.692, Brier score 0.124) using the 20 top-ranked variables also showed excellent performance. SHAP analysis indicated that the top-ranked features included fasting plasma glucose (FPG), waist circumference (WC), body mass index (BMI), triglycerides (TG), gender, waist-to-height ratio (WHtR), the number of daughters born, resting pulse rate (RPR), etc. Conclusion: The ML models using the LightGBM algorithm are efficient to predict insulin sensitivity in the community and primary care settings accurately and might potentially become an efficient and practical tool for insulin sensitivity assessment in these settings.

The impact of a statewide insulin copay cap policy for insured patients with diabetes in Utah.

BACKGROUND: Insulin affordability is a huge concern for patients with diabetes in the United States. On March 30, 2020, Utah signed House Bill 207 into law, aimed at capping copayments for insulin at $30 for a 30-day supply. The bill was enacted on January 1, 2021. OBJECTIVE: To assess patient basal insulin adherence, out-of-pocket costs, health plan costs, total costs on insulin, and hemoglobin A1c (A1c) in prepolicy vs postpolicy periods. METHODS: This study is a retrospective analysis using data from a regional health plan in Utah from October 1, 2019, to September 30, 2021. Inclusion criteria were fully enrolled members of all ages, under commercial insurance, with at least 1 fill for any type of insulin in both the preperiod and the postperiod. Adherence was measured by proportion of days covered (PDC). Paired t-tests and Wilcoxon sign rank tests were conducted to compare the health and economic outcomes. RESULTS: Out of 24,150 commercially insured individuals, a total of 244 patients were included. Across all 244 patients, there was a significant decline in monthly median out-of-pocket costs of insulin by 58.5% (P < 0.001), whereas the monthly median health plan costs of insulin increased by 22.0% (P < 0.001). The total monthly costs of insulin (the sum of out-of-pocket and health plan costs) were unchanged (P = 0.115). Only 74 patients with enough basal insulin fills in both periods were included in the analysis for PDC changes. PDC change was not statistically significant (P = 0.43). Among the 74 patients with PDC calculations, 29 patients had A1c recorded in both periods. The change in A1c was not statistically significant (P = 0.23). CONCLUSIONS: An insulin copayment max of $30 in Utah demonstrated lower patient out-of-pocket costs, subsidized by the health plan. PDC did not change, and HbA1c did not improve. An assessment of a longer period and on a larger population is needed.

The Health Economics of Automated Insulin Delivery Systems and the Potential Use of Time in Range in Diabetes Modeling: A Narrative Review.

Intensive therapy with exogenous insulin is the treatment of choice for individuals living with type 1 diabetes (T1D) and some with type 2 diabetes, alongside regular glucose monitoring. The development of systems allowing (semi-)automated insulin delivery (AID), by connecting glucose sensors with insulin pumps and algorithms, has revolutionized insulin therapy. Indeed, AID systems have demonstrated a proven impact on overall glucose control, as indicated by effects on glycated hemoglobin (HbA1c), risk of severe hypoglycemia, and quality of life measures. An alternative endpoint for glucose control that has arisen from the use of sensor-based continuous glucose monitoring is the time in range (TIR) measure, which offers an indication of overall glucose control, while adding information on the quality of control with regard to blood glucose level stability. A review of literature on the health-economic value of AID systems was conducted, with a focus placed on the growing place of TIR as an endpoint in studies involving AID systems. Results showed that the majority of economic evaluations of AID systems focused on individuals with T1D and found AID systems to be cost-effective. Most studies incorporated HbA1c, rather than TIR, as a clinical endpoint to determine treatment effects on glucose control and subsequent quality-adjusted life year (QALY) gains. Likely reasons for the choice of HbA1c as the chosen endpoint is the use of this metric in most validated and established economic models, as well as the limited publicly available evidence on appropriate methodologies for TIR data incorporation within conventional economic evaluations. Future studies could include the novel TIR metric in health-economic evaluations as an additional measure of treatment effects and subsequent QALY gains, to facilitate a holistic representation of the impact of AID systems on glycemic control. This would provide decision makers with robust evidence to inform future recommendations for health care interventions.

Burden of Illness of Type 2 Diabetes Mellitus in the Kingdom of Saudi Arabia: A Five-Year Longitudinal Study.

INTRODUCTION: Type 2 diabetes mellitus (T2DM) is associated with huge clinical and economic burden in the Kingdom of Saudi Arabia (KSA) which can be curtailed by efficacious treatment. In order to achieve this, current treatment pathways for T2DM and associated costs need to be assessed. METHODS: A longitudinal cohort review was conducted to collect country-specific and patient-specific clinical data, over a minimum observation period of 5 years in the KSA. Patient demographics, clinical characteristics and treatment patterns were recorded. The IQVIA Core Diabetes Model (CDM) version 9.5 Plus was used to assess the burden of illness, which included long-term projections of clinical (life expectancy [LE], quality-adjusted life-years [QALYs], event rates of diabetes-related complications) and direct medical cost (per-patient annual or lifelong [50 years]) outcomes of the most commonly used first-line (1st-line) regimens for T2DM from a payer perspective in the KSA. RESULTS: Data were collected from a subpopulation of 638 patients from 15 participating centres. There was an equal gender representation with a majority of the patients belonging to Arabian/Saudi ethnicity (71.0%). Biguanides (81.5%), sulfonylureas (51.6%), dipeptidyl peptidase 4 (DPP4) inhibitors (26.2%) and fast-acting insulins (17.2%) were the most prescribed 1st-line agents. The most frequently used 1st-line regimens resulted in an estimated LE of 25-28 years, QALYs of 18-21 years and lifelong total cost of illness of 201,377-437,371 Saudi Arabian riyal (53,700-116,632 US dollars). CONCLUSION: Our study addresses gaps in the current research by providing a complete landscape of baseline demographic, clinical characteristics and treatment patterns from a heterogeneous group of patients with T2DM in the KSA. Additionally, the burden of illness analysis using CDM showed substantially higher cost of T2DM care from a payer perspective in the KSA.

DNA Methylation-Based Assessment of Cell Composition in Human Pancreas and Islets.

Assessment of pancreas cell type composition is crucial to the understanding of the genesis of diabetes. Current approaches use immunodetection of protein markers, for example, insulin as a marker of ß-cells. A major limitation of these methods is that protein content varies in physiological and pathological conditions, complicating the extrapolation to actual cell number. Here, we demonstrate the use of cell type-specific DNA methylation markers for determining the fraction of specific cell types in human islet and pancreas specimens. We identified genomic loci that are uniquely demethylated in specific pancreatic cell types and applied targeted PCR to assess the methylation status of these loci in tissue samples, enabling inference of cell type composition. In islet preparations, normalization of insulin secretion to ß-cell DNA revealed similar ß-cell function in pre-type 1 diabetes (T1D), T1D, and type 2 diabetes (T2D), which was significantly lower than in donors without diabetes. In histological pancreas specimens from recent-onset T1D, this assay showed ß-cell fraction within the normal range, suggesting a significant contribution of ß-cell dysfunction. In T2D pancreata, we observed increased α-cell fraction and normal ß-cell fraction. Methylation-based analysis provides an accurate molecular alternative to immune detection of cell types in the human pancreas, with utility in the interpretation of insulin secretion assays and the assessment of pancreas cell composition in health and disease.

mTORC1 in energy expenditure: consequences for obesity.

In eukaryotic cells, the mammalian target of rapamycin complex 1 (sometimes referred to as the mechanistic target of rapamycin complex 1; mTORC1) orchestrates cellular metabolism in response to environmental energy availability. As a result, at the organismal level, mTORC1 signalling regulates the intake, storage and use of energy by acting as a hub for the actions of nutrients and hormones, such as leptin and insulin, in different cell types. It is therefore unsurprising that deregulated mTORC1 signalling is associated with obesity. Strategies that increase energy expenditure offer therapeutic promise for the treatment of obesity. Here we review current evidence illustrating the critical role of mTORC1 signalling in the regulation of energy expenditure and adaptive thermogenesis through its various effects in neuronal circuits, adipose tissue and skeletal muscle. Understanding how mTORC1 signalling in one organ and cell type affects responses in other organs and cell types could be key to developing better, safer treatments targeting this pathway in obesity.

Smart connected insulin dose monitoring technologies versus standard of care: a Canadian cost-effectiveness analysis.

Aim: There is growing interest in novel insulin management systems that improve glycemic control. This study aimed to evaluate the cost-effectiveness of smart connected insulin re-usable pens or caps for disposable insulin pens versus pens without connected capabilities in the management of adult patients with Type 1 diabetes (T1DM) from a Canadian societal perspective. Materials & methods: The IQVIA Core Diabetes Model was utilized to conduct the analyses. Applying data from a non-interventional study, the connected insulin device arm was assumed to result in greater reductions (-0.67%) in glycated hemoglobin from baseline and fewer non-severe hypoglycemic events (-32.87 events/patient annually). Macro- and micro-vascular risks were predicted using the Epidemiology of Diabetes Interventions and Complications study data. Direct and indirect costs and utilities were sourced from literature. Key model outcomes included life years and quality-adjusted life-years (QALYs). Both costs and effects were annually discounted at 1.5% over a 60-year time horizon. Uncertainty was explored in scenario and probabilistic sensitivity analyses (PSA). Results: The connected insulin pen device was associated with lower mean discounted total costs (CAD221,943 vs 266,199; -CAD44,256), improvement in mean life expectancy (25.78 vs 24.29; +1.49 years) and gains in QALYs (18.48 vs 16.74; +1.75 QALYs) over the patient's lifetime. Most scenario analyses confirmed the base case results. The PSA showed dominance in 99.5% of cases. Conclusion: For adults with T1DM in Canada, a connected insulin pen device is likely to be a cost-effective treatment option associated with greater clinical benefits and lower costs relative to a standard re-usable or disposable pen.

Cost-utility of real-time continuous glucose monitoring versus self-monitoring of blood glucose in people with insulin-treated Type II diabetes in France.

Aim: Clinical trials and real-world data for Type II diabetes both show that glycated hemoglobin (HbA1c) levels and hypoglycemia occurrence can be reduced by real-time continuous glucose monitoring (rt-CGM) versus self-monitoring of blood glucose (SMBG). The present cost-utility study investigated the long-term health economic outcomes associated with using rt-CGM versus SMBG in people with insulin-treated Type II diabetes in France. Materials & methods: Effectiveness data were obtained from a real-world study, which showed rt-CGM reduced HbA1c by 0.56% (6.1 mmol/mol) versus sustained SMBG. Analyses were conducted using the IQVIA Core Diabetes Model. A French payer perspective was adopted over a lifetime horizon for a cohort aged 64.5 years with baseline HbA1c of 8.3% (67 mmol/mol). A willingness-to-pay threshold of €147,093 was used, and future costs and outcomes were discounted at 4% annually. Results: The analysis projected quality-adjusted life expectancy was 8.50 quality-adjusted life years (QALYs) for rt-CGM versus 8.03 QALYs for SMBG (difference: 0.47 QALYs), while total mean lifetime costs were €93,978 for rt-CGM versus €82,834 for SMBG (difference: €11,144). This yielded an incremental cost-utility ratio (ICUR) of €23,772 per QALY gained for rt-CGM versus SMBG. Results were particularly sensitive to changes in the treatment effect (i.e., change in HbA1c), annual price and quality of life benefit associated with rt-CGM, SMBG frequency, baseline patient age and complication costs. Conclusion: The use of rt-CGM is likely to be cost-effective versus SMBG for people with insulin-treated Type II diabetes in France.

Exploring Technology's Influence on Health Behaviours and Well-being in Type 1 Diabetes: a Review.

PURPOSE OF REVIEW: Maintaining positive health behaviours promotes better health outcomes for people with type 1 diabetes (T1D). However, implementing these behaviours may also lead to additional management burdens and challenges. Diabetes technologies, including continuous glucose monitoring systems, automated insulin delivery systems, and digital platforms, are being rapidly developed and widely used to reduce these burdens. Our aim was to review recent evidence to explore the influence of these technologies on health behaviours and well-being among adults with T1D and discuss future directions. RECENT FINDINGS: Current evidence, albeit limited, suggests that technologies applied in diabetes self-management education and support (DSME/S), nutrition, physical activity (PA), and psychosocial care areas improved glucose outcomes. They may also increase flexibility in insulin adjustment and eating behaviours, reduce carb counting burden, increase confidence in PA, and reduce mental burden. Technologies have the potential to promote health behaviours changes and well-being for people with T1D. More confirmative studies on their effectiveness and safety are needed to ensure optimal integration in standard care practices.

Factors and economic burden of non-severe hypoglycemia among insulin-treated type 2 diabetes patients: a cross-sectional study.

OBJECTIVE: This cross-sectional survey was performed to assess the prevalence, factors, and economic burden of non-severe hypoglycemia among insulin-treated type 2 diabetes (T2D) patients in northern Thailand. METHODS: Between April 2021 and August 2022, 600 participants were evaluated via structured questionnaires containing sociodemographic and clinical characteristics, medications, and economic burden. Patients were divided into two groups (having and not having non-severe hypoglycemia). Variables with a p value <.05 in the univariate model were included in the multivariate model. RESULTS: The percentage of non-severe hypoglycemia was 50.3% (302/600). Of all participants, the average age was 61.4 ± 26.0 years, 55.7% were female, 53.5% used premix insulin, and the average duration of diabetes was 16.1 ± 10.0 years. Multivariate logistic regression analysis indicated that age (OR = .96; p <.001), duration of diabetes (OR = 1.04; p <.001), BMI (OR = .95; p = .002), thiazolidinedione (OR = 1.56; p = .012) and insulin regimens were associated with having non-severe hypoglycemia. Compared to basal insulin, basal bolus (OR = 6.93; p = .001), basal plus (OR = 3.58; p <.001), and premix insulin (OR = 1.83; p =.003) were associated with hypoglycemia. Greater numbers of sick leave were found in the hypoglycemia group (14 vs 4 patients, p = .029). CONCLUSIONS: These findings help to individuate those patients who are at higher risk of non-severe hypoglycemia in insulin-treated T2D patients. Compared to the non-hypoglycemia group, patients with hypoglycemia were younger, had longer diabetes duration, lower BMI, received thiazolidinedione and insulin regimens such as premix, basal plus, or basal bolus insulins, and more productivity loss.

Partnering for Better Health: Using Continuous Glucose Monitoring and Clinical Pharmacist Collaboration to Improve Glycemic Control in Underserved Patients With Type 2 Diabetes.

PURPOSE: The purpose of this study was to examine the effect of initiating use of a continuous glucose monitor (CGM) in patients being treated for type 2 diabetes mellitus, specifically those who face barriers to obtaining this device because of its cost. METHODS: This retrospective medical record review compared diabetes control of patients before and after use of a CGM device within a single primary care office. Patient medical records were reviewed 18 months after initial CGM was provided, and only those who received a CGM directly from the clinic were included in the review. Statistical analysis comparing the difference in mean baseline glycosylated hemoglobin (HbA1c) level with the first HbA1c level after CGM placement was completed using the paired t test for the primary outcome. FINDINGS: A total of 41 patients who obtained at least 1 CGM reader and a minimum of a 30-day supply of sensors from the clinic were included in the review. The primary outcome resulted in a significant reduction in the mean (SD) first HbA1c level after CGM placements of -1.9% (2.5%) (P < .001) with a total of 10 and 22 patients with an HbA1c level <7% and 8%, respectively. This mean (SD) reduction in HbA1c level was also seen in both insulin-treated patients (-1.8% [2.8%], n = 30) and non-insulin-treated patients (-2% [2.8%], n=11). The largest reduction in the first HbA1c level after CGM placement was seen in those patients provided a CGM along with collaborative care with a clinical pharmacist. These patients saw a mean (SD) decrease of -2.5% [2.7%] (n = 26) in their HbA1c level with a mean (SD) decrease of -0.8% (1.6%) (n = 15) for those not comanaged by the clinical pharmacist. IMPLICATIONS: The results of this study suggest that the use of CGM in the underserved population can lead to a significant improvement in glycemic control in patients with diabetes, regardless of treatment therapies used. Involving a multidisciplinary team in diabetes management, including clinical pharmacists, may further improve outcomes. Access to these devices in the underserved population may be crucial in reducing the risk of developing complications related to uncontrolled diabetes.