Effect of Consultation Number on the Assessment and Treatment of Polycystic Ovary Syndrome.

Background: The basic medical education stage is not enough to support physicians to fully diagnose and evaluate polycystic ovary syndrome (PCOS). The study aims to discover the difference in treatment choice between participants with different annual consultation number of PCOS, to promote lifelong learning, and drive balanced development within healthcare. Methods: This is a multicenter cross-sectional survey. Participants' basic information, knowledge of PCOS and treatment options were collected online. According to the annual consultation number of patients with PCOS, physicians were divided into three groups: 0-50 people/yr, 50-200 people/yr, and >200 people/yr, and the results were derived from χ2 test, Fisher exact test, and multivariate logistic regression analysis. Results: The study analyzed 1689 questionnaires, and 1206 physicians (71.4%) received less than 50 women per year, 388 physicians (30.0%) with an annual number of 50-200 women, and 95 physicians (5.6%) with patient turnover for more than 200 people. Reproductive endocrinologists generally have higher access to the clinic. As the number of visits increases, more and more physicians would perceive patients as more likely to have abnormal blood glucose and heavy weight. Physicians with large numbers of consultations are more likely to use Asian or Chinese standards to assess obesity. The multivariate analysis involved variables such as age, hospital level, specialty, and patient turnover annually, and more young doctors actively assessed lipid profile (odds ratio (OR) 1.56, 95% confidence interval (CI) (1.16, 2.16)), and primary hospitals (OR 0.65 CI (0.44, 0.89)) chose OGTT for blood glucose assessment less than tertiary hospitals. Physicians in secondary hospitals are more aggressive in evaluating androgens. Conclusion: Our survey found differences in endocrine assessment, metabolic screening, and treatment in PCOS women in terms of the number of obstetrician-gynecologists who received different patient consultation numbers. The importance of continuing education for physicians is emphasized, to promote lifelong learning.

Cost-effectiveness analysis of metformin versus insulin in the treatment of gestational diabetes mellitus.

OBJECTIVE: Although there have been many studies on gestational diabetes mellitus (GDM) treatment, there is still a knowledge gap regarding the comparative cost-effectiveness of metformin and insulin in the treatment phase. Existing studies have focused on treatment efficacy and drug safety, but relatively little has been explored regarding cost-effectiveness analysis. In particular, no comprehensive study has evaluated the cost-effectiveness of metformin and insulin for GDM treatment. Therefore, this study aimed to fill this knowledge gap by conducting a cost-effectiveness analysis of these two treatments for GDM. METHODS: A decision-analytic model was used to compare the cost-effectiveness of metformin and insulin in China. Probabilities, costs, and utilities were derived from the literature. The cost and quality-adjusted life years (QALYs) were calculated using the roll-back method. The strategy was considered cost-effective if the incremental cost-effectiveness ratio (ICER) was below the willingness-to-pay (WTP) threshold of ¥242,938 per QALY. Sensitivity analyses were also conducted to assess the robustness of the results. RESULTS: The roll-back analysis indicated that insulin was not cost-effective compared to metformin, resulting in increased costs and decreased QALYs, with a negative ICER. These findings suggested that metformin is a cost-effective option than insulin. Furthermore, the sensitivity analysis showed that the model was robust. CONCLUSIONS: Compared with insulin, metformin is a cost-effective treatment option for GDM.

Chinese herbal medicine decreases incidence of hepatocellular carcinoma in diabetes mellitus patients with regular insulin management.

BACKGROUND: Type 2 diabetes mellitus (DM) is an independent risk factor for hepatocellular carcinoma (HCC), while insulin is a potent mitogen. Identifying a new therapeutic modality for preventing insulin users from developing HCC is a critical goal for researchers. AIM: To investigate whether regular herbal medicine use can decrease HCC risk in DM patients with regular insulin control. METHODS: We used data acquired from the Taiwanese National Health Insurance research database between 2000 and 2017. We identified patients with DM who were prescribed insulin for > 3 months. The herb user group was further defined as patients prescribed herbal medication for DM for > 3 months per annum during follow-up. We matched the herb users to nonusers at a 1:3 ratio according to age, sex, comorbidities and index year by propensity score matching. We analyzed HCC incidence, HCC survival rates, and the herbal prescriptions involved. RESULTS: We initially enrolled 657144 DM patients with regular insulin use from 2000 to 2017. Among these, 46849 patients had used a herbal treatment for DM, and 140547 patients were included as the matched control group. The baseline variables were similar between the herb users and nonusers. DM patients with regular herb use had a 12% decreased risk of HCC compared with the control group [adjusted hazard ratio (aHR) = 0.88, 95%CI = 0.80-0.97]. The cumulative incidence of HCC in the herb users was significantly lower than that of the nonusers. Patients with a herb use of > 5 years cumulatively exhibited a protective effect against development of HCC (aHR = 0.82, P < 0.05). Of patients who developed HCC, herb users exhibited a longer survival time than nonusers (aHR = 0.78, P = 0.0001). Additionally, we report the top 10 herbs and formulas in prescriptions and summarize the potential pharmacological effects of the constituents. Our analysis indicated that Astragalus propinquus (Huang Qi) plus Salvia miltiorrhiza Bunge (Dan Shen), and Astragalus propinquus (Huang Qi) plus Trichosanthes kirilowii Maxim. (Tian Hua Fen) were the most frequent combination of single herbs. Meanwhile, Ji Sheng Shen Qi Wan plus Dan Shen was the most frequent combination of herbs and formulas. CONCLUSION: This large-scale retrospective cohort study reveals that herbal medicine may decrease HCC risk by 12% in DM patients with regular insulin use.

Homeostasis Model Assessment for Insulin Resistance Mediates the Positive Association of Triglycerides with Diabetes.

Elevated circulating triglyceride levels have been linked to an increased risk of diabetes, although the precise mechanisms remain unclear. This study aimed to investigate whether low-density lipoprotein (LDL) cholesterol, homeostatic model assessment (HOMA) for insulin resistance, and C-reactive protein (CRP) served as mediators in this association across a sample of 18,435 US adults. Mediation analysis was conducted using the PROCESS Version 4.3 Macro for SPSS. Simple mediation analysis revealed that all three potential mediators played a role in mediating the association. However, in parallel mediation analysis, where all three mediators were simultaneously included, HOMA for insulin resistance remained a significant mediator (indirect effect coefficient, 0.47; 95% confidence interval [CI], 0.43-0.52; p < 0.05) after adjusting for all tested confounding factors. Conversely, LDL cholesterol (indirect effect coefficient, -0.13; 95% CI, -0.31-0.05; p > 0.05) and C-reactive protein (indirect effect coefficient, 0.01; 95% CI, -0.003-0.02; p > 0.05) ceased to be significant mediators. HOMA for insulin resistance accounted for 49% of the association between triglycerides and diabetes. In conclusion, HOMA for insulin resistance was the dominant mediator underlying the association between triglycerides and diabetes. Therefore, reducing triglyceride levels may hold promise for improving insulin sensitivity in diabetic patients.

Diabetes subgroups and sociodemographic inequalities in Mexico: a cross-sectional analysis of nationally representative surveys from 2016 to 2022.

Background: Differences in the prevalence of four diabetes subgroups have been reported in Mexico compared to other populations, but factors that may contribute to these differences are poorly understood. Here, we estimate the prevalence of diabetes subgroups in Mexico and evaluate their correlates with indicators of social disadvantage using data from national representative surveys. Methods: We analyzed serial, cross-sectional Mexican National Health and Nutrition Surveys spanning 2016, 2018, 2020, 2021, and 2022, including 23,354 adults (>20 years). Diabetes subgroups (obesity-related [MOD], severe insulin-deficient [SIDD], severe insulin-resistant [SIRD], and age-related [MARD]) were classified using self-normalizing neural networks based on a previously validated algorithm. We used the density-independent social lag index (DISLI) as a proxy of state-level social disadvantage. Findings: We identified 4204 adults (median age: 57, IQR: 47-66, women: 64%) living with diabetes, yielding a pooled prevalence of 16.04% [95% CI: 14.92-17.17]. When stratified by diabetes subgroup, prevalence was 6.62% (5.69-7.55) for SIDD, 5.25% (4.52-5.97) for MOD, 2.39% (1.95-2.83) for MARD, and 1.27% (1.00-1.54) for SIRD. SIDD and MOD clustered in Southern Mexico, whereas MARD and SIRD clustered in Northern Mexico and Mexico City. Each standard deviation increase in DISLI was associated with higher odds of SIDD (OR: 1.12, 95% CI: 1.06-1.12) and lower odds of MOD (OR: 0.93, 0.88-0.99). Speaking an indigenous language was associated with higher odds of SIDD (OR: 1.35, 1.16-1.57) and lower odds of MARD (OR 0.58, 0.45-0.74). Interpretation: Diabetes prevalence in Mexico is rising in the context of regional and sociodemographic inequalities across distinct diabetes subgroups. SIDD is a subgroup of concern that may be associated with inadequate diabetes management, mainly in marginalized states. Funding: This research was supported by Instituto Nacional de Geriatría in Mexico.

Reduction in Diabetes-Related Hospitalizations and Medical Costs After Dexcom G6 Continuous Glucose Monitor Initiation in People with Type 2 Diabetes Using Intensive Insulin Therapy.

INTRODUCTION: Some people with type 2 diabetes (T2D) require intensive insulin therapy to manage their diabetes. This can increase the risk of diabetes-related hospitalizations. We hypothesize that initiation of real-time continuous glucose monitoring (RT-CGM), which continuously measures a user's glucose values and provides threshold- and trend-based alerts, will reduce diabetes-related emergency department (ED) and inpatient hospitalizations and concomitant costs. METHODS: A retrospective analysis of US healthcare claims data using Optum's de-identified Clinformatics® Data Mart database was performed. The cohort consisted of commercially insured, CGM-naïve individuals with T2D who initiated Dexcom G6 RT-CGM system between August 1, 2018, and March 31, 2021. Twelve months of continuous health plan enrollment before and after RT-CGM initiation was required to capture baseline and follow-up rates of diabetes-related hospitalizations and associated healthcare resource utilization (HCRU) costs. Analyses were performed for claims with a diabetes-related diagnosis code in either (1) any position or (2) first or second position on the claim. RESULTS: A total of 790 individuals met the inclusion criteria. The average age was 52.8 (10.5) [mean (SD)], 53.3% were male, and 76.3% were white. For claims with a diabetes-related diagnosis code in any position, the number of individuals with ≥ 1 ED visit decreased by 30.0% (p = 0.01) and with ≥ 1 inpatient visit decreased by 41.5% (p < 0.0001). The number of diabetes-related visits and average number of visits per person similarly decreased by at least 31.4%. Larger relative decreases were observed for claims with a diabetes-related diagnosis code in the first or second position on the claim. Total diabetes-related costs expressed as per-person-per-month (PPPM) decreased by $341 PPPM for any position and $330 PPPM for first or second position. CONCLUSION: Initiation of Dexcom G6 among people with T2D using intensive insulin therapy was associated with a significant reduction in diabetes-related ED and inpatient visits and related HCRU costs. Expanded use of RT-CGM could augment these benefits and result in further cost reductions.

Reducing Inequity in the Use of Automated Insulin Delivery Systems by Adults with Type 1 Diabetes: Key Learnings from a Safety Net Diabetes Clinic Program.

BACKGROUND: Recent advancements in diabetes technology have significantly improved Type 1 diabetes (T1D) management, but disparities persist, particularly in the adoption of automated insulin delivery (AID) systems within minoritized communities. We aimed to improve patient access to AID system training and overcome clinical inertia to referral. METHODS: We report on a transformative program implemented at Boston Medical Center, the largest safety-net hospital in New England, aimed at reducing disparities in AID system utilization. We employed a multidisciplinary team and quality improvement principles to identify barriers and develop solutions. Strategies included increasing access to diabetes educators, creating a referral system, and developing telemedicine education classes. We also made efforts to raise clinician awareness and confidence in recommending AID therapy. RESULTS: At baseline, 13.5% of our clinic T1D population was using an insulin pump. The population referred included 97 people with T1D (49% female, mean A1c 8.7%, 68% public insurance beneficiaries, 25% Hispanic and 25% non-Hispanic Black). Results from the first year showed a 166% increase in AID system use rates, with 64% of referred patients starting on AID. Notably, 78% of patients with A1c > 8.5% adopted AID systems, addressing a gap in representation observed in clinical efficacy trials. The initiative successfully narrowed disparities in AID use among minoritized populations. CONCLUSIONS: The program's success among minoritized patients underscores the significance of tailored, collaborative, team-based care and targeted educational initiatives. Our experience provides a foundation for future efforts to ensure equitable access to diabetes technologies, emphasizing the potential of local quality improvement interventions.

Expert consensus on nutrition and lower-carbohydrate diets: An evidence- and equity-based approach to dietary guidance.

There is a substantial body of clinical evidence supporting the beneficial effects of lower-carbohydrate dietary patterns on multiple established risk factors associated with insulin resistance and cardiovascular diseases in adult populations. Nutrition and health researchers, clinical practitioners, and stakeholders gathered for, "The Scientific Forum on Nutrition, Wellness, and Lower-Carbohydrate Diets: An Evidence- and Equity-Based Approach to Dietary Guidance" to discuss the evidence base around lower-carbohydrate diets, health outcomes, and dietary guidance. Consensus statements were agreed upon to identify current areas of scientific agreement and spotlight gaps in research, education, and practice to help define and prioritize future pathways. Given the evidence base and considering that most American adults are living with at least one nutrition-related chronic disease, there was consensus that including a lower-carbohydrate dietary pattern as one part of the Dietary Guidelines for Americans could help promote health equity among the general population.

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.

Cost-Effectiveness of Closed-Loop Automated Insulin Delivery Using the Cambridge Hybrid Algorithm in Children and Adolescents with Type 1 Diabetes: Results from a Multicenter 6-Month Randomized Trial.

BACKGROUND/OBJECTIVE: The main objective of this study is to evaluate the incremental cost-effectiveness (ICER) of the Cambridge hybrid closed-loop automated insulin delivery (AID) algorithm versus usual care for children and adolescents with type 1 diabetes (T1D). METHODS: This multicenter, binational, parallel-controlled trial randomized 133 insulin pump using participants aged 6 to 18 years to either AID (n = 65) or usual care (n = 68) for 6 months. Both within-trial and lifetime cost-effectiveness were analyzed. Analysis focused on the treatment subgroup (n = 21) who received the much more reliable CamAPS FX hardware iteration and their contemporaneous control group (n = 24). Lifetime complications and costs were simulated via an updated Sheffield T1D policy model. RESULTS: Within-trial, both groups had indistinguishable and statistically unchanged health-related quality of life, and statistically similar hypoglycemia, severe hypoglycemia, and diabetic ketoacidosis (DKA) event rates. Total health care utilization was higher in the treatment group. Both the overall treatment group and CamAPS FX subgroup exhibited improved HbA1C (-0.32%, 95% CI: -0.59 to -0.04; P = .02, and -1.05%, 95% CI: -1.43 to -0.67; P < .001, respectively). Modeling projected increased expected lifespan of 5.36 years and discounted quality-adjusted life years (QALYs) of 1.16 (U.K. tariffs) and 1.52 (U.S. tariffs) in the CamAPS FX subgroup. Estimated ICERs for the subgroup were £19 324/QALY (United Kingdom) and -$3917/QALY (United States). For subgroup patients already using continuous glucose monitors (CGM), ICERs were £10 096/QALY (United Kingdom) and -$33 616/QALY (United States). Probabilistic sensitivity analysis generated mean ICERs of £19 342/QALY (95% CI: £15 903/QALY to £22 929/QALY) (United Kingdom) and -$28 283/QALY (95% CI: -$59 607/QALY to $1858/QALY) (United States). CONCLUSIONS: For children and adolescents with T1D on insulin pump therapy, AID using the Cambridge algorithm appears cost-effective below a £20 000/QALY threshold (United Kingdom) and cost saving (United States).

Assessment of estimated and measured resting metabolic rates in type 1 and type 2 diabetes mellitus.

Aim: This study aimed to compare the estimated and measured resting metabolic rates of patients with type 1 and type 2 diabetes mellitus in an outpatient clinical setting. Material and methods: Participants were categorized into three groups that included type 1 diabetes, type 2 diabetes, and individuals without diabetes. Bland-Altman analysis was used to identify the equation that most accurately predicted the measured resting metabolic rates. Multiple regression analysis was used to identify the factors affecting resting metabolic rates. Results: Resting metabolic rates was observed to be higher in subjects with type 2 diabetes compared to that of the other groups. There was a proportional bias between predicted and measured resting metabolic rates. Type 1 diabetes, type 2 diabetes, male sex, body weight, waist circumference, and triglyceride level were factors that positively predicted resting metabolic rates, and age was a factor that negatively predicted it. Conclusions: Although there was a bias between estimated and measured RMR, the most accurate results were achieved with the Mifflin-St Jeor equation for women with type 1 diabetes, with the Owen equation for men with type 1 diabetes, with the Harris Benedict equation for women with type 2 diabetes, and with the Ikeda equation for men with type 2 diabetes as well as for women and men in the control group.

An exploratory analysis of the cost-effectiveness of insulin glargine 300 units/mL versus insulin glargine 100 units/mL over a lifetime horizon using the BRAVO diabetes model.

BACKGROUND: This analysis assessed the cost-effectiveness of insulin glargine 300 units/mL (Gla-300) versus insulin glargine 100 units/mL (Gla-100) in insulin-naïve adults with type 2 diabetes (T2D) inadequately controlled with oral antidiabetic drugs (OADs). METHODS: Costs and outcomes for Gla-300 versus Gla-100 from a US healthcare payer perspective were assessed using the BRAVO diabetes model. Baseline clinical data were derived from EDITION-3, a 12-month randomized controlled trial comparing Gla-300 with Gla-100 in insulin-naïve adults with inadequately controlled T2D on OADs. Treatment costs were calculated based on doses observed in EDITION-3 and 2020 US net prices, while costs for complications were based on published literature. Lifetime costs ($US) and quality-adjusted life-years (QALYs) were predicted and used to calculate incremental cost-effectiveness ratio (ICER) estimates; extensive scenario and sensitivity analyses were conducted. RESULTS: Lifetime medical costs were estimated to be $353,441 and $352,858 for individuals receiving Gla-300 and Gla-100 respectively; insulin costs were $52,613 and $50,818. Gla-300 was associated with a gain of 8.97 QALYs and 21.12 life-years, while Gla-100 was associated with a gain of 8.89 QALYs and 21.07 life-years. This resulted in an ICER of $7522/QALY gained for Gla-300 versus Gla-100. Thus, Gla-300 was cost-effective versus Gla-100 based on a willingness-to-pay threshold of $50,000/QALY. Compared with Gla-100, Gla-300 provided a net monetary benefit of $3290. Scenario and sensitivity analyses confirmed the robustness of the base case. CONCLUSION: Gla-300 may be a cost-effective treatment option versus Gla-100 over a lifetime horizon for insulin-naïve people in the United States with T2D inadequately controlled on OADs.

Metabolic health tracking using Ultrahuman M1 continuous glucose monitoring platform in non- and pre-diabetic Indians: a multi-armed observational study.

Continuous glucose monitoring (CGM) device adoption in non- and pre-diabetics for preventive healthcare has uncovered a paucity of benchmarking data on glycemic control and insulin resistance for the high-risk Indian/South Asian demographic. Furthermore, the correlational efficacy between digital applications-derived health scores and glycemic indices lacks clear supportive evidence. In this study, we acquired glycemic variability (GV) using the Ultrahuman (UH) M1 CGM, and activity metrics via the Fitbit wearable for Indians/South Asians with normal glucose control (non-diabetics) and those with pre-diabetes (N = 53 non-diabetics, 52 pre-diabetics) for 14 days. We examined whether CGM metrics could differentiate between the two groups, assessed the relationship of the UH metabolic score (MetSc) with clinical biomarkers of dysglycemia (OGTT, HbA1c) and insulin resistance (HOMA-IR); and tested which GV metrics maximally correlated with inflammation (Hs-CRP), stress (cortisol), sleep, step count and heart rate. We found significant inter-group differences for mean glucose levels, restricted time in range (70-110 mg/dL), and GV-by-SD, all of which improved across days. Inflammation was strongly linked with specific GV metrics in pre-diabetics, while sleep and activity correlated modestly in non-diabetics. Finally, MetSc displayed strong inverse relationships with insulin resistance and dysglycemia markers. These findings present initial guidance GV data of non- and pre-diabetic Indians and indicate that digitally-derived metabolic scores can positively influence glucose management.

Continuous Glucose Monitoring Profiles and Health Outcomes after Dapagliflozin Plus Saxagliptin vs Insulin Glargine.

CONTEXT: Glycemic variability and hypoglycemia during diabetes treatment may impact therapeutic effectiveness and safety, even when glycated hemoglobin (HbA1c) reduction is comparable between therapies. OBJECTIVE: We employed masked continuous glucose monitoring (CGM) during a randomized trial of dapagliflozin plus saxagliptin (DAPA+SAXA) vs insulin glargine (INS) to compare glucose variability and patient-reported outcomes (PROs). DESIGN: 24-week sub-study of a randomized, open-label, two-arm, parallel-group, phase 3b study. SETTING: Multicenter study (112 centers in 11 countries). PATIENTS: 283 adults with type 2 diabetes (T2D) inadequately controlled with metformin ± sulfonylurea. INTERVENTIONS: DAPA+SAXA vs INS. MAIN OUTCOME MEASURES: Changes in CGM profiles, HbA1c, and PROs. RESULTS: Changes from baseline in HbA1c with DAPA+SAXA were similar to those observed with INS, with mean difference [95% CI] between decreases of -0.12% [-0.37 to 0.12%], P = .33. CGM analytics were more favorable for DAPA+SAXA, including greater percent time in range (> 3.9 and ≤ 10 mmol/L; 34.3 ± 1.9 vs 28.5 ± 1.9%, P = .033), lower percent time with nocturnal hypoglycemia (area under the curve ≤ 3.9 mmol/L; 0.6 ± 0.5 vs 2.7 ± 0.5%, P = .007), and smaller mean amplitude of glycemic excursions (-0.7 ± 0.1 vs -0.3 ± 0.1 mmol/L, P = .017). Improvements in CGM were associated with greater satisfaction, better body weight image, less weight interference, and improved mental and emotional well-being. CONCLUSIONS: DAPA+SAXA and INS were equally effective in reducing HbA1c at 24 weeks, but people with T2D treated with DAPA+SAXA achieved greater time in range, greater reductions in glycemic excursions and variability, less time with hypoglycemia, and improved patient-reported health outcomes.

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 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.

The Short-Term Cost-Effectiveness of a Fixed-Ratio Combination of Insulin Degludec and Aspart: A Cost of Control Analysis in Australia and India.

OBJECTIVES: The real-world ARISE study demonstrated initiation of fixed-ratio combination insulin degludec and aspart (IDegAsp) led to improvements in people achieving key glycemic control targets compared with prior therapies in Australia and India. This study evaluated the short-term cost-effectiveness of IDegAsp in these countries, in terms of the cost per patient achieving these targets. METHODS: A model was developed to evaluate the cost of control (treatment costs divided by the proportion of patients achieving each target) of IDegAsp versus prior therapies received in ARISE for 2 endpoints: glycated hemoglobin (HbA1c) <7.0%, and HbA1c less than a predefined individual treatment target. Costs, expressed from a healthcare payer perspective, were captured in 2022 Australian dollars (AUD) and 2022 Indian rupees (INR). RESULTS: The number of patients needed to treat to bring one to endpoints of HbA1c <7.0% and less than an individualized target with IDegAsp was 51% and 87% lower, respectively, than with prior therapies in Australia, and 52% and 66% lower, respectively, versus prior therapies in India. Cost of control was AUD 2449 higher and AUD 64 863 lower with IDegAsp versus prior therapies for endpoints of HbA1c <7.0% and less than an individualized target, respectively, in Australia and INR 211 142 and INR 537 490 lower with IDegAsp compared with prior therapies in India. CONCLUSIONS: IDegAsp was estimated to be cost-effective versus prior therapies when considering an individualized HbA1c target in Australia, and when considering an individualized HbA1c target and HbA1c <7.0% in India.

Assessment of the Impact of Subcutaneous Catheter Change on Glucose Control in Patients with Type 1 Diabetes Treated by Insulin Pump in Open- and Closed-Loop Modes.

Introduction: Most continuous subcutaneous insulin infusion (CSII) catheters (KT) are changed every 3 days. This study aims at evaluating whether KT changes impact glucose control while under open-loop (OL) or automated insulin delivery (AID) modes. Methods: We included patients with type 1 diabetes who used Tandem t:slim x2 insulin pump and Dexcom G6 glucose sensor for 20 days in OL, then as AID. CSII and sensor glucose data in OL and for the past 20 days of 3-month AID were retrospectively analyzed. The percentage of time spent with sensor glucose above 180 mg/dL (%TAR180) was compared between the calendar day of KT change (D0), the next day (D1), and 2 days later (D2). Values were adjusted for age, gender, body mass index (BMI), hemoglobin A1c (HbA1c) at inclusion, and %TAR180 for the 2 h before KT change. Results: A total of 1636 KT changes were analyzed in 134 patients: 72 women (54%), age: 35.6 ± 15.7 years, BMI: 25.2 ± 4.7 kg/m2, and HbA1c: 7.5 ± 0.8%. %TAR180 in the 2 h before the KT change was 51.3 ± 37.0% in OL and 33.2 ± 30.0% in AID mode. In OL, significant absolute increases of %TAR180 at D0 versus D1 (+6.9%; P < 0.0001) or versus D2 (+6.8%; P < 0.0001) were observed. In AID, significant absolute increases of %TA180R at D0 versus D1 (+4.8%; P < 0.0001) or versus D2 (+4.2%; P < 0.0001) were also observed. Conclusion: This study shows an increase in time spent in hyperglycemia on the day of the KT change both in OL and AID modes. This additional information should be taken into account to improve current AID algorithms. ClinicalTrials.gov: NCT04939766.

Why the increase? Examining the rise in prescription medication expenditures in the United States between 2011 and 2020.

The objective of this cross-sectional analysis was to identify determinants of increasing medicine expenditures in the US between 2011 and 2020. Prescription medication expenditures from the 2011-2020 Medical Expenditures Panel Survey (MEPS) were used to calculate total annual medication expenditures by payer categories (Out-of-pocket, Medicare, Medicaid, TRICARE/Veterans Administration/CHAMPVA (TVAC), Other Government Sources, Private Insurance, and Other Sources). From here, expenditures were stratified by therapeutic category using Multum Lexicon Drug Class to examine trends in expenditures by therapeutic area. Linear regression was used to identify temporal trends in medication expenditures. From 2011 to 2020, total annual prescription medication expenditures rose from $341.49 to $473.12 billion per year with metabolic agents being the most costly category. Among the metabolic agents, antidiabetic agents were the most costly therapeutic area, with an increasing trend observed from $27.15 to $89.17 billion over the same period. Medicare, Medicaid, Private Insurance, TVAC, and Other Sources also saw an increasing trend in antidiabetic agent expenditure, while no trend was observed for Out-of-pocket and Other Government Sources. Insulin had the highest expenditure among antidiabetic agents. Further studies are warranted to explore specific factors contributing to the increasing trend.

Cardiometabolic risk assessment: A school-based study in Brazilian adolescent.

BACKGROUND AND AIMS: Recently, new indices combining routine and low-cost anthropometric and biochemical measurements have emerged. Among them, the visceral adiposity index (VAI) and lipid accumulation product (LAP) are being investigated for the prediction of altered blood pressure (BP) and insulin resistance (IR). Therefore, this study aimed to evaluate whether visceral adiposity index (VAI) and height-corrected lipid accumulation product (HLAP) are predictors of cardiometabolic risk in Brazilian adolescents. METHODS AND RESULTS: Data were obtained from the Cardiovascular Risk in Adolescents (ERICA) study, a cross-sectional, national, multicenter, school-based survey conducted between 2013 and 2014 in Brazil. The sample consisted of 37,815 adolescents aged 12-17 years of both genders attending the last 3 years of elementary or secondary school from public and private schools located in 273 municipalities with more than 100,000 inhabitants. A Poisson regression was performed to verify associations between VAI and HLAP indices and the presence of altered BP and IR according to sex. In addition, receiver operating characteristic curve (ROC) analysis was applied to compare the predictive ability and determine the cut-off points of the VAI and HLAP indices in identifying cardiometabolic risk obtained by altered BP and IR. The prevalences of altered BP and IR were 24.49 % (95 % confidence interval [CI]: 23.14-25.87) and 24.22 % (95 % CI: 22.70-25.80), respectively. CONCLUSIONS: The VAI and HLAP indices are good predictors of cardiometabolic risk in Brazilian adolescents. HLAP showed better performance in identifying insulin resistance in males.