Diabetes Therapy最新文献

Introduction: Painful diabetic peripheral neuropathy (pDPN) affects approximately 25% of individuals with diabetes in the UK and remains underdiagnosed and suboptimally managed in primary care. The condition causes chronic pain, limits daily functioning, impairs quality of life, and increases the risk of complications like foot ulcers and amputations due to underlying neuropathy. Current care pathways are fragmented, leading to delays in diagnosis and limited access to evidence-based therapies. This article aims to address the challenges of screening, diagnosis, and management of pDPN in UK primary care by proposing a consensus-driven, five-step pragmatic strategy.

Methods: An expert panel of general practitioners and a diabetes nurse practitioner from across the UK convened to review and discuss strategies for improving pDPN care. Consensus was reached through an evaluation of barriers in clinical practice, supported by real-world experience and examples of innovative care delivery models, resulting in the development of practical recommendations and workflow.

Results: Key barriers identified include insufficient training of healthcare professionals in pDPN, underutilisation of validated screening tools such as the DN4 questionnaire, and inconsistent and outdated treatment guidelines. To address these challenges, a five-step approach was proposed to include screening high-risk patients using validated questionnaires, following up on these patients to enable early diagnoses, initiating early treatments with first-line therapies while monitoring responses, referring complex cases to secondary care on the basis of structured criteria, and ensuring coordinated follow-up to streamline and optimise care delivery. Case studies demonstrate the practical application of these strategies in improving early detection, treatment adherence, and long-term care for individuals with pDPN.

Conclusion: Current practices have fallen short in providing adequate care for one in four individuals with diabetes. Implementing a straightforward five-step approach can significantly improve diagnostic accuracy and treatment outcomes, reducing the burden of pDPN on both patients and society.

Introduction: Chronic kidney disease (CKD) progression is associated with a significant incremental economic burden. Previous work has demonstrated high accuracy of the laboratory-based machine learning model, Klinrisk, in predicting the risk of CKD progression. We sought to use the Klinrisk model to evaluate the association of risk of CKD progression with healthcare resource utilization (HRU) and costs of care in adults with type 2 diabetes and CKD.

Methods: This retrospective observational study included 413,177 eligible patients from Optum's electronic health records database (1/1/2007-9/30/2022). Patients were classified into low-, medium-, and high-risk groups based on their 2-year risk of CKD progression as predicted by the Klinrisk model. All-cause HRU and medical costs during the 1 year after CKD were estimated for each group.

Results: Of the 413,177 patients included, 110,399 (26.7%) were classified as low-risk of CKD progression, 253,188 (61.3%) as medium-risk, and 49,590 (12.0%) as high-risk. The observed risk of CKD progression at 2 years, 5 years, and 10 years was 18.6%, 36.5%, and 54.1% for high-risk patients, 3.7%, 11.7%, and 26.4% for medium-risk patients, and 1.5%, 5.7%, and 15.8% for low-risk patients, which were similar to the predicted risks of CKD progression. High-risk patients had higher HRU and more than 2-3 times higher costs than lower-risk patients. Inpatient costs were the major cost driver for high-risk patients.

Conclusions: The Klinrisk model accurately identified patients with type 2 diabetes and CKD requiring the most healthcare resources. Such tools can support the identification and targeting of high-risk patients for interventions that may lead to a more cost-effective model of care.

Introduction: IcoSema is under development as a once-weekly injectable combination therapy of icodec (basal insulin) and semaglutide (glucagon-like peptide 1 receptor agonist). This study assessed the pharmacokinetic characteristics of icodec and semaglutide following IcoSema administration vs. administration of icodec and semaglutide alone in Chinese individuals with type 2 diabetes (T2D).

Methods: In a randomized, double-blind, three-period crossover study, 20 Chinese individuals with T2D (18-64 years, body mass index 18.5-34.9 kg/m², glycated hemoglobin ≤ 9.0%) were given single subcutaneous administrations of IcoSema, icodec, or semaglutide separated by 6-9 weeks. Blood was drawn for pharmacokinetic measurement until 840 h post dose.

Results: Combining icodec with semaglutide had no impact on icodec pharmacokinetics. The ratio and 90% confidence interval of IcoSema/icodec was 1.04 [0.99;1.08] for area under the curve from zero to last quantifiable observation (AUC_0-t) and 1.02 [0.96;1.09] for maximum concentration (C_max), i.e., within the bioequivalence acceptance interval of 0.80-1.25. Likewise, combining semaglutide with icodec had no impact on semaglutide AUC_0-t (IcoSema/semaglutide 0.99 [0.94;1.05]). However, semaglutide C_max was higher for IcoSema vs. semaglutide alone (1.42 [1.31;1.53]) and occurred earlier for IcoSema (12 vs. 66 h). All three treatments were safe with no differences in frequency, severity or outcome of adverse events, or relationship to study product.

Conclusion: In Chinese individuals with T2D, icodec pharmacokinetics and semaglutide total exposure are unaffected when combining icodec and semaglutide in IcoSema. However, maximum semaglutide concentration is higher and occurs earlier with IcoSema. This information may help to ensure suitable dose recommendations for IcoSema.

Trial registration: ClinicalTrials.gov identifier, NCT05435677.

Platelets are crucial for haemostasis and thrombosis. They acquire a distinct prothrombotic and proinflammatory platelet phenotype in individuals with diabetes mellitus, particularly type 2 diabetes mellitus (T2DM). Such platelets in people with diabetes (diabetic platelets) contribute to the pathogenesis of micro- and macro-vascular complications in T2DM. Chronic hyperglycaemia, oxidative stress, advanced glycation end-products (AGEs) and insulin resistance converge to reprogram platelet function at the molecular level. This results in platelet hyperreactivity, enhanced aggregation and a diminished therapeutic response to standard antiplatelet medications. Platelets in people with diabetes play a central role in the development and progression of cardiovascular disease (CVD), the most common cause of mortality in such patients. This manuscript explores the structural and functional changes in platelets in people with diabetes, underlying molecular mechanisms, their role in vascular complications and therapeutic perspectives in patients with diabetes. Also, we introduce the concept of 'haematobolomics' to drive more research in the metabolic profile of platelets in people with diabetes, being a potential avenue for personalised therapeutics.

Intravitreal therapy using anti-vascular endothelial growth factor (anti-VEGF) has transformed the approach to treating diabetic retinopathy (DR), but its application in individuals with diabetes and chronic kidney disease, the majority of whom have diabetic kidney disease, involves a complex evaluation of risks and benefits. Emerging evidence indicates that the systemic absorption of anti-VEGF agents administered intravitreally may lower circulating VEGF levels and negatively impact the renal endothelium, especially in individuals with pre-existing kidney issues. In this article, we showcase an evidence-based framework for the safe administration of anti-VEGF therapy in patients with DR accompanied by chronic kidney disease. We introduce a novel renoretinal syndrome, which we refer to as anti-VEGF-associated nephropathy (AVAN), and outline diagnostic criteria, severity classifications, biopsy indications, and treatment recommendations to guide clinical practice.

Introduction: These analyses explored the efficacy and safety of once-weekly insulin icodec (icodec) in Indian participants with type 1 or type 2 diabetes (T1D/T2D) from the global ONWARDS 1, 4, and 6 studies.

Methods: This was a subgroup analysis of Indian participants enrolled in the multicentre, randomised, treat-to-target phase 3a studies: ONWARDS 1 (insulin-naïve T2D), ONWARDS 4 (basal-bolus treated T2D), and ONWARDS 6 (basal-bolus treated T1D). Participants were randomised 1:1 to receive once-weekly insulin icodec or once-daily comparator insulin (glargine U100 [ONWARDS 1 and 4] or degludec [ONWARDS 6]). The primary outcome was change in glycated haemoglobin (HbA_1c) from baseline to week 52 for ONWARDS 1, week 26 for ONWARDS 4 and 6.

Results: A total of 217 Indian participants were included. The estimated treatment differences (95% confidence interval, CI) in HbA_1c change for icodec versus once-daily comparator were 0.04% [- 0.46; 0.54], - 0.04% [- 0.41; 0.32], and 0.08% [- 0.67; 0.82] in ONWARDS 1, 4, and 6 studies, respectively. Time in range was similar between groups in the three studies. Icodec showed numerically lower rates of clinically significant hypoglycaemia compared to glargine U100 in ONWARDS 1 and 4, though a numerically higher rate of hypoglycaemic events was noted in ONWARDS 6 compared with degludec; results were consistent with global populations. Adverse event profiles were similar between groups, and no new safety findings were reported in the Indian subpopulation.

Conclusion: Icodec demonstrated comparable efficacy and safety to once-daily basal insulins in Indian participants with T1D and T2D. These findings support icodec as a viable option for insulin initiation or intensification in Indian clinical practice.

Trial registrations: ONWARDS 1: NCT04460885; ONWARDS 4: NCT04880850; ONWARDS 6: NCT04848480.

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.