Diabetes Therapy最新文献

Introduction: The purpose of this study was to explore the roles and methods of inflammatory factors and total load of cerebral small vessel disease (CSVD) in diabetic retinopathy (DR) and cognitive impairment.

Materials and methods: In total, 1860 patients with type 2 diabetes mellitus (T2DM) were divided into a DR group and a non-diabetic retinopathy (NDR) group, and nonproliferative DR was divided into mild and moderate-to-severe according to the severity. The patients' baseline data were recorded, and imaging indicators were collected to evaluate CSVD. Monofactor analysis was performed to identify the risk factors associated with DR and cognitive impairment, and a logistic regression model was used to determine independent risk factors. Finally, Nomogram and receiver operating characteristic (ROC) curves were constructed to evaluate the prediction effect of the model.

Results: (1) 693 patients (37.26%) had DR and 1167 patients (62.74%) had no DR. In the DR group, hypertension, disease course, low-density lipoprotein cholesterol (LDL-C), uric acid (UA), glycosylated hemoglobin (HbA1c), triglyceride glucose index (TyG), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) were all significantly higher than in the NDR group (p < 0.001). Multivariate logistic regression analysis further verified that hypertension, LDL-C, PLR, and SII were independent risk factors for DR. (2) Among 612 patients with nonproliferative DR, the levels of hypertension, UA, HbA1c, TyG index, interleukin-6 (IL-6), monocyte-to-lymphocyte ratio (MLR), and SII in the moderate-to-severe nonproliferative DR group were significantly higher than those in the mild nonproliferative DR group (p < 0.01). (3) Patients with moderate-to-severe nonproliferative DR were divided into a cognitive impairment group and a non-cognitive impairment group. Smoking history, drinking history, fasting blood glucose, HbA1c, TyG index, PLR, MLR, SII, total CSVD magnetic resonance imaging (MRI) load, and white matter hyperintensities (WMHs) were significantly associated with cognitive impairment (p < 0.01). Smoking history, fasting blood glucose, HbA1c, TyG index, SII, total CSVD load, and lacunar infarction (LI) were independent risk factors for cognitive impairment in patients with moderate-to-severe DR. In addition, total MRI load (r = 0.711, p < 0.05), TyG index (r = 0.712, p < 0.05), SII (r = 0.703, p < 0.05), and PLR (r = 0.724, p < 0.05) were significantly negatively correlated with Montreal Cognitive Assessment (MoCA) score.

Conclusions: This study identified hypertension history, LDL-C, PLR, and SII as factors independently associated with the presence of DR in patients with T2DM. In addition, UA, TyG, SII, total CSVD load, and WMHs were significantly associated with more severe stages of DR.

Introduction: Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized primarily by insulin resistance and hyperglycemia, often leading to multiple complications. Sleep disturbances, including insomnia and sleep apnea, are prevalent in patients with T2DM and are associated with poorer glucose metabolism. Despite research examining the relationship between glucose metabolism, body composition, and sleep quality, the underlying mechanisms remain unclear, particularly within patients with T2DM.

Methods: This study involved 269 newly diagnosed patients with T2DM from January to June 2024. Data collected included demographic information, clinical variables, glycemic markers, and body composition analyses. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI), categorizing participants into poor (PSQI-H) and good sleep quality (PSQI-L) groups. Univariate and multivariate regression analyses, along with mediation analysis, were performed using SPSS 26.0 and R software to explore associations between sleep quality, glycemic markers, and body composition.

Results: Significant correlations were found between PSQI scores and glycemic markers such as HbA1c, HOMA-IR, and postprandial blood glucose levels, showing that poorer glucose control was correlated with worse sleep quality. Mediation analysis suggested that body composition, particularly the trunk-to-limb fat mass ratio, may act as a statistical mediator in the relationship between glucose metabolism and sleep quality.

Conclusions: Our findings highlight the complex relationship between glucose metabolism, body composition, and sleep quality in patients with T2DM. Targeting glucose regulation and body composition may be explored in future studies as potential approaches to improve sleep quality in individuals with T2DM.

Trial registration: Clinical ChiCTR1900022768.

Chronic kidney disease continues to be a significant burden for people living with type 2 diabetes, despite the available guideline-directed treatment options. Traditionally, a stepwise approach has been implemented for the management of chronic kidney disease and type 2 diabetes, which involves the linear sequential initiation of one therapy after the other on the basis of an individual's treatment outcomes. However, this approach is not beneficial for all individuals, as it can lead to treatment inertia and subsequent disease progression. Therefore, primary care practitioners should consider implementing a more proactive treatment strategy to optimize care. The pillar risk-based approach is an emerging concept with goals of glucose control and blood pressure control as well as comprising simultaneous or rapid sequential initiation of multiple therapies, such as renin-angiotensin system inhibitors (RASi), sodium-glucose cotransporter 2 inhibitors, a nonsteroidal mineralocorticoid receptor antagonist (finerenone), and glucagon-like peptide-1 receptor agonists, which target the different hemodynamic, metabolic, and fibrotic/inflammatory pathways involved in chronic kidney disease and type 2 diabetes. This approach enables earlier chronic kidney disease risk reduction, and the recently published CONFIDENCE trial reported tolerability and efficacy of simultaneous initiation of two of these therapies (finerenone and empagliflozin) in those already receiving RASi. This review article provides primary care practitioners with practical considerations, discussing current guideline-directed treatment options for chronic kidney disease in people with type 2 diabetes in the context of a historical stepwise approach versus the new patient-centric pillar risk-based approach.

Introduction: This study aims to examine the extent to which experienced and/or internalized weight stigma and diabetes stigma may be associated with HbA1c level in adults with type 2 diabetes mellitus.

Methods: A total of 857 participants completed a web-based survey including self-reported demographics, weight, HbA1c, and measures of weight stigma and diabetes stigma, including the Modified Weight Bias Internalization Scale (WBIS-M), Weight Self-Stigma Questionnaire (WSSQ), and the Type 2 Diabetes Stigma Assessment Scale (DSAS-2).

Results: Participants with elevated HbA1c reported greater weight stigma and diabetes stigma than those with an HbA1c level within the standard-of-care range. Exploratory subgroup analysis of participants who did not provide an HbA1c level reported experiencing and internalizing weight stigma and diabetes stigma at similarly high levels as those with elevated HbA1c. Compared to Black non-Hispanic participant's mean WBIS-M and WSSQ-Total scores, Hispanic participants and White non-Hispanic participants reported greater weight stigma. Hispanic participants endorsed higher DSAS-2 Self-Stigma scores than Black non-Hispanic participants.

Conclusions: Weight stigma and diabetes stigma may be associated with suboptimal diabetes care outcomes measured as elevated HbA1c or inability to report an HbA1c level.

Introduction: The primary goal of managing type 1 diabetes mellitus (T1D) is to achieve glycemic control and prevent both acute and chronic complications. In recent years, automated insulin delivery (AID) systems, such as the 780G AID system, have significantly improved glycemic control and patient safety. Despite being the most advanced treatment option, AID initiation is often delayed until the honeymoon stage (partial remission phase). This study evaluated the impact of initiating MiniMed™ 780G at diagnosis on metabolic control and glycemic metrics in children newly diagnosed with T1D. It compares early AID initiation with continuous glucose monitoring (CGM) and multiple daily injection (MDI) therapy over a 1-year follow-up period.

Methods: This retrospective study included children and adolescents (age range 0.87-17.72 years) newly diagnosed with T1D between January 2023 and August 2024. Ten patients who were initiated on AID therapy at diagnosis were included, with eight patients completing a 1-year follow-up. Data from these eight patients and seven patients on CGM + MDI therapy were analyzed at baseline and at 3, 6, and 12 months.

Results: The mean age at diagnosis was 6.98 ± 3.22 years (0.87-9.82) for the AID group and 9.77 ± 4.89 years (3.70-17.72) for the CGM + MDI group (p = 0.14). The AID system was initiated at an average of 3.33 ± 7.73 days (2-23) after diagnosis, while sensor use in the CGM + MDI group began an average of 17.37 ± 8.86 days (1-29) after diagnosis. At 12 months, mean hemoglobin A1c (HbA1c) was 6.10% (43 mmol/mol) in the AID group compared with 7.73% (61 mmol/mol) in the CGM + MDI group. Time in range (TIR) was 79.0% vs. 50.7%, and time above range (TAR) was 13.4% vs. 30.7%, based on 2-week CGM data prior to the 12-month visit (p = 0.02, p = 0.009, p = 0.02). No case of diabetic ketoacidosis or severe hypoglycemia was reported during the follow-up period.

Conclusion: This study highlights the potential benefits of initiating AID therapy at the time of diagnosis, offering novel insights into its safety and efficacy in the early management of T1D. These findings suggest that early initiation of AID therapy at the time of diagnosis is feasible and may improve glycemic outcomes.

Introduction: Early onset type 2 diabetes (T2D), diagnosed before age 40 years, is potentially more aggressive than later-onset disease and is increasing in prevalence globally. We examined the prevalence of early onset T2D in the USA and characterised this population.

Methods: Data from the longitudinal series of NHANES cross-sectional surveys conducted between 1999 and 2020 were analysed retrospectively. The prevalence of diagnosed and undiagnosed early onset T2D was estimated across this period and the demographics, clinical characteristics and frequency of comorbidities in this population were described. Findings were compared with the US later-onset T2D population during the same period.

Results: The prevalence of diagnosed and undiagnosed early onset T2D increased from 1.42% (standard error 0.19) and 0.18% (0.09), respectively, during the 1999-2000 survey cycle to 1.72% (0.24) and 0.35% (0.06), respectively, during the 2017-2020 cycle. Compared with those with later-onset disease, participants with early onset T2D had a lower mean poverty-income ratio, were more likely to be Hispanic or have no health insurance and less likely to be non-Hispanic white or have private or Medicare insurance (all p < 0.05). Individuals with early onset T2D generally had a worse cardiometabolic profile, with higher mean glycated haemoglobin, Homeostatic Model Assessment for Insulin Resistance score, fasting insulin and glucose, body mass index and waist circumference but were less likely to have congestive heart failure, coronary heart disease, stroke, chronic kidney disease or cancer (all p < 0.05). All comparisons remained statistically significant after adjustment for T2D duration among participants with diagnosed T2D.

Conclusions: These findings suggest that early onset T2D may disproportionately affect underserved populations with a higher likelihood of having cardiometabolic risk factors, suggesting a more aggressive disease that warrants the need for better diagnoses and treatment. Further research is needed to explore the potential link between cardiometabolic profile, risk of complications and longer-term cardiovascular outcomes in people with early onset T2D.

Introduction: To evaluate real-world hemoglobin A1c (HbA1c) and weight change in adults initiating treatment with tirzepatide (dual glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist [GLP-1 RA]) or injectable semaglutide (GLP-1 RA) indicated for type 2 diabetes (T2D) management.

Methods: This retrospective analysis utilized the Healthcare Integrated Research Database® to identify adults with T2D starting tirzepatide or injectable semaglutide between May 13, 2022 and May 29, 2023. GLP-1 RA naïve and non-naïve cohorts were identified based on the history of GLP-1 RA use within ≤ 6 months of initiation. Propensity score matching balanced 6-month baseline characteristics between groups. HbA1c and weight changes were assessed from initiation to 12 months for matched patients with HbA1c and weight data at both time points.

Results: Both matched naïve cohorts were comprised of 10,702 patients (tirzepatide: 1399 with HbA1c data and 454 with weight data; semaglutide: 1173 with HbA1c data and 432 with weight data). Mean baseline HbA1c and weight were 7.8% and 112.4 kg, respectively, for the tirzepatide group and 7.8% and 110.7 kg for the semaglutide group. Both matched non-naïve cohorts were comprised of 5577 patients (tirzepatide: 792 with HbA1c data and 296 with weight data; semaglutide: 738 with HbA1c data and 224 with weight data). Mean baseline HbA1c and weight were 7.7% and 112.5 kg for tirzepatide, and 7.9% and 108.5 kg for semaglutide. Tirzepatide was associated with greater mean reductions in HbA1c (naïve: - 1.3% vs. - 0.9%; non-naïve: - 0.9% vs. - 0.6%; p < 0.001) and weight (naïve: - 10.2 kg vs. - 6.1 kg; non-naïve: - 7.9 kg vs. - 3.7 kg; p < 0.001) than semaglutide.

Conclusions: Patients with T2D starting tirzepatide had greater HbA1c and weight reductions at 12 months post-initiation than those on injectable semaglutide, regardless of previous GLP-1 RA use, consistent with previous clinical trial results.

Introduction: Basal insulin injections have historically been administered via once-daily (OD) or twice-daily (BD) injections. Once-weekly (OW) basal insulin injections have recently been developed. This study aimed to quantify the relative importance of the administration frequency in basal insulin treatment preferences of people living with T2D in Canada, Spain, France, and Japan, using a discrete choice experiment (DCE).

Methods: Best-practice guidelines for patient preference studies were followed in a three-phase study design. Phases one (targeted literature review) and two (qualitative interviews) informed the development of an attributes and levels grid. Phase three consisted of pilot interviews to evaluate the feasibility of preference survey completion and DCE tasks among adults living with T2D across Canada, France, Spain, and Japan. Hierarchical Bayesian estimation was used to estimate part-worth utilities for attribute levels, then calculate the relative importance of each attribute among other attributes tested.

Results: The DCE survey was completed by N = 513 participants (aged 20-90; 54% male, 45% female; mean time since diagnosis: 11.6 years). Participants were split into three treatment groups: basal insulin and injectable glucagon-like peptide-1 receptor agonist (GLP-1 RA) naïve (n = 176), basal insulin naïve but with injectable GLP-1 RA experience (n = 176) and basal insulin experienced (n = 161). The administration frequency had a relative importance of 40% across the full sample, double that of any other treatment attribute tested in this study. A preference for OW administration was found relative to OD and BD. Findings were consistent across treatment groups and countries.

Conclusions: This study demonstrated the value and importance of administration frequency in making choices for basal insulin treatments when glycemic control is held constant. Per the pre-specified conditions, participants expressed a preference for OW basal insulin, making considered trade-offs between treatment risks (e.g., risk of a severe hypoglycemic event) and convenience (e.g., frequency of administration).

Post-bariatric hypoglycemia (PBH) is a frequent yet complex complication following Roux-en-Y gastric bypass, typically related to exaggerated insulin responses after rapid glucose absorption. Identifying alternative or contributing mechanisms is particularly challenging in this population due to altered anatomy and limited access to standard diagnostic tools. We describe the case of a 65-year-old man with a history of type 2 diabetes, obesity, and cardiac sarcoidosis, who achieved diabetes remission after gastric bypass. Several months later, he developed frequent postprandial and nocturnal hypoglycemic episodes despite strict dietary adjustments. Continuous glucose monitoring showed 38% time below range. A 72-h fasting test revealed inappropriately high proinsulin and C-peptide levels, indicating endogenous hyperinsulinemia. The patient was receiving sacubitril/valsartan for heart failure. Upon discontinuation of this treatment due to worsening renal function, hypoglycemic episodes resolved completely, and a repeat fasting test was normal. This is, to our knowledge, the first case report describing sacubitril/valsartan-associated hypoglycemia in a patient post-gastric bypass surgery, and the first to document inappropriate insulin secretion under treatment using a fasting test. Preclinical data suggest that neprilysin inhibition may enhance insulin secretion, possibly via increased GLP-1 bioavailability. While sacubitril/valsartan has demonstrated cardiovascular benefit, its metabolic effects remain underrecognized. Given the growing number of patients who have undergone bariatric surgery and the widespread use of this medication, clinicians should consider its potential role in refractory hypoglycemia. Early identification may avoid unnecessary investigations and support appropriate therapeutic adjustments.

Introduction: Diabetes represents an increasing public health challenge in France, yet national data distinguishing type 1 from type 2 diabetes and insulin use remain limited. This study aimed to describe trends in the epidemiology, care pathways and health outcomes of adult individuals living with type 1 or type 2 diabetes in France from 2010 to 2019. It focused on individuals treated or not with insulin and applied a predictive classification algorithm to accurately distinguish between diabetes types using real-world data.

Methods: A 10-year retrospective population-based cohort study was conducted from a representative one-tenth sample of the French national healthcare database (i.e. SNDS, Système National des données de Santé), covering nearly the entire French population. Adults (≥ 18 years) affiliated with the general insurance scheme were included. A machine learning algorithm, trained on clinical data from general practitioners, was applied to classify diabetes type. Annual trends in prevalence, incidence, comorbidities, treatments, outpatient care, complications and mortality were assessed.

Results: Among an extrapolated 5.5 million individuals with diabetes in 2019, 3.5% had type 1 diabetes and 96.5% had type 2 diabetes. The prevalence of type 2 diabetes increased from 6.2% in 2010 to 8.0% in 2019, while type 1 diabetes remained stable. Comorbidity rates were high and increasing in insulin-treated individuals with type 2 diabetes. In 2019, 15.3% of insulin-treated individuals with type 2 diabetes had at least one complication-related hospitalisation. Specialist consultations were underused, especially in type 2 diabetes. The mortality rate in individuals with type 1 diabetes declined from 2.6% to 1.5%, with an increase in mean age at death.

Conclusion: This national study provides updated insights into diabetes in France and highlights the need to improve access to specialised care and reinforce long-term surveillance strategies.