People with type 2 diabetes in Asia have heterogeneous phenotypes but share common features of young age-at-diagnosis, low body mass index, low pancreatic beta-cell capacity, rapid decline in insulin secretion as well as visceral and ectopic fat excess. Cardiovascular diseases are the leading causes of mortality in people with diabetes. In clinical trial settings, despite receiving protocol-driven care, Asians had higher risk of chronic kidney disease than non-Asians. Aging and improved survival in people with diabetes continue to drive the epidemic of diabetes. People with old age, long disease duration and complications might benefit from both insulin to optimize glucose control and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) for cardiovascular-renal protection. Complex therapies pose challenges in administration and adherence where fixed-dose combination such as basal insulin plus GLP-1 RA may improve safety, effectiveness and acceptability. In this narrative review, we summarized the efficacy and safety data from randomized controlled trials using iGlarLixi, a fixed-ratio combination of insulin glargine 100 U/mL (iGlar) and lixisenatide (Lixi), a short acting GLP-1 RA, studied widely in Asians. We discussed the guidelines on the use of this fixed-ratio combination illustrated by real-world case studies in older Asian adults with young-onset type 2 diabetes.
Background The RADAR (Reorganizing the Approach to Diabetes through the Application of Registries) project was launched to enhance type 2 diabetes (T2D) care and outcomes in on-reserve First Nations communities in Alberta, Canada. The objective of this study is to determine whether previously observed improvements in diabetes care outcomes were sustained over time in the communities that continued the program (continued communities) and whether these improvements were reproducible in new communities. Methods RADAR involved an innovative, culturally contextually grounded care model designed for First Nations people, which was deployed in a stepped-wedge design to communities. The primary outcome was a 10% improvement or persistence at target in A1C, systolic blood pressure (SBP), and/or LDL, using the intention-to-treat (ITT) framework. Outcomes were assessed in 3 continued communities at 3-, 4-, and 6- years post-implementation of the RADAR program. We provided the same intervention to 2 new communities and assessed outcomes at 1 year post-implementation (repeatability assessment). Results In 2024, 256 T2D patients were registered in RADAR, ranging from 28 to 86 individuals per community. The average age was 61 years (SD=11.7) with 57% females (N = 145). ITT analysis showed all 3 continued communities maintained high rates of primary endpoint achievement, with 94%, 100% and 92% of participants in each community achieving the primary endpoint (n = 174), respectively, relative to baseline (p < 0.001). After 1 year of RADAR in the 2 new communities (n = 28 and n = 54), the ITT combined endpoint was achieved in 82% and 91% of participants, respectively (p < 0.001). Conclusion RADAR continues to be associated with high levels of achievement of the primary combined endpoint across communities and over time. This study shows promise that future RADAR implementation could be adapted, in collaboration with First Nation Health Managers, to other First Nations community settings.
Aims This study evaluated whether a gamified mHealth application (CareAide®) improves Health-Related Quality of Life (HRQoL) in Type 2 Diabetes Mellitus (T2DM) and whether this effect is mediated by medication adherence. Methods Prespecified secondary analysis of the T2DM cohort from a 6-month multicentre RCT (NCT06068309; N = 663; three Malaysian hospitals). Participants were randomised 1:1 to standard care or CareAide®. Adherence (MMAS-8), EQ-5D-5L utility (Malaysian value set), and AQoL-6D were assessed at baseline and 6 months. Simple mediation analysis (PROCESS Model 4; 5000 bootstraps) adjusted for baseline HRQoL. Results CareAide® significantly predicted higher MMAS-8 scores (mean difference +1.756; d = 1.638; p < 0.001). Higher MMAS-8 scores significantly predicted improved AQoL-6D utility (b = 0.024; p < 0.001). The direct effect on AQoL-6D was non-significant (p = 0.248). Bootstrapped indirect effect confirmed full mediation via AQoL-6D (0.042; 95% CI [0.024, 0.060]). A sensitivity analysis adjusting for baseline HbA1c confirmed full mediation (indirect = 0.034; 95% CI [0.015, 0.052]; n = 563). EQ-5D-5L utility showed a significant direct between-group difference at 6 months (p = 0.012) but did not operate as a mediation outcome. Conclusions Medication adherence fully mediates the AQoL-6D HRQoL benefit of a gamified mHealth intervention in T2DM, as confirmed by both the primary and HbA1c-adjusted sensitivity analyses. These findings support integration of behaviourally informed digital adjuncts into routine primary diabetes care.
Aims To evaluate the quality of type 2 diabetes mellitus (T2DM) care and variability across three Spanish healthcare areas using a standardized set of quality indicators (QIs) applied to routine clinical data. Methods This retrospective cohort study included 30,111 adults with T2DM drawn from electronic health records across three areas. Fifteen QIs, including nine process and six outcome indicators, were used to evaluate adherence to guideline-recommended monitoring and treatment. Results For most QIs, adherence to process indicators was below 70%. Only 20.4% of patients had timely 6-month glycosylated hemoglobin (HbA1c) follow-up, and just 3.9% of those out-of-target received quarterly checks. Sixty percent of patients with cardiovascular or chronic kidney disease received sodium-glucose cotransporter type 2 inhibitors (SGLT2i) or glucagon-like peptide type 1 receptor agonists (GLP1ras) treatment, yet only 15% received combination therapy. GLP1ras were used by 1.5% of patients with obesity. Among out-of-target patients, 41% achieved a ≥ 1% HbA1c reduction. Insulin initiation was delayed a median of 7.7 years. Conclusions In summary, applying a common set of indicators across three healthcare areas proved feasible and helped identify relevant gaps in T2DM care. The Diabetes Lighthouse initiative may support quality monitoring and benchmarking, and help guide targeted improvement strategies.
The aim of this study was to evaluate the long-term effectiveness of the FreeStyle Libre 2 device in reducing time below range levels 1 (TBR-1) and 2 (TBR-2), compared with the first-generation FreeStyle Libre device without alarms, in people with type 1 diabetes mellitus. A longitudinal observational pre-post study of a single cohort was conducted in a cohort of 93 people with type 1 diabetes mellitus who switched from FreeStyle Libre to FreeStyle Libre 2 in routine clinical practice. At 24 months post-switch, significant improvements were observed in TBR-1 (p = 0.001) and TBR-2 (p < 0.001). A significant direct association was identified between years with diabetes mellitus and change in total basal insulin dose from T0 to T1, with a coefficient of 0.14. Additionally, a significant inverse association was found between annual income and coefficient of variation, with a coefficient of -6.3, as well as between annual income and TBR-2, with a coefficient of -2.45. Switching to a flash glucose monitoring system with alarms was associated with improvements at 24 months in time below range, coefficient of variation, and HbA1c in individuals with type 1 diabetes mellitus.
Aims Study the treatment gap of guideline-indicated therapies in people with T2D and atherosclerotic cardiovascular disease (ASCVD) or heart failure (HF) or chronic kidney disease (CKD). Methods We extracted prescription history from 2005 to 2025 from a national dataset, a community-based health system, and an academic center. We assessed treatment gap (current and ever) within four subgroups defined using American Diabetes Association Standards of Care indications for SGLT2i and GLP-1RA use. Results We identified 6,951,624 people in the national dataset, 58,390 people at the community-based health system, and 15,235 people at the academic center. The current treatment gaps among people with ASCVD (without HF or CKD) were 72%, 67%, and 49%; with ASCVD and HF or CKD3 were 73%, 71%, and 55%; with CKD3 or HF without ASCVD were 75%, 71%, and 65%; with CKD4/5 were 87%, 89%, and 74% within the national dataset, community-based health system, and academic health system, respectively. The ever-prescription rates ranged from 23% to 39%, 30%-47%, 42%-64% within the national dataset, community-based health system, and academic center, respectively. Discussion Over half the population never received an indicated cardio-kidney protective prescription, and two-thirds lack a current prescription. These gaps were substantial across all systems; however, lowest at the academic center.
Aim The aim of this study was to systematically review and evaluate the types and effectiveness of digital health interventions used for diabetes management in the Eastern Mediterranean Region (EMRO). Methods This systematic review, conducted according to PRISMA guidelines, searched PubMed, Web of Science, and Scopus up to May 2025 to identify studies on digital interventions for diabetes management in EMRO countries. Methodological quality of the included studies was evaluated using the EPHPP tool, and findings were categorized by intervention type, outcome measures, and intervention effectiveness. Results A total of 46 studies were included, mainly from Iran and Saudi Arabia. Phone calls and SMS were the most common digital tools. Digital interventions significantly improved HbA1c, fasting blood sugar, and several behavioral outcomes such as physical activity, medication adherence, and self-efficacy, while effects on psychological outcomes were mixed. Conclusion Digital health interventions, especially phone calls and SMS, effectively improve glycemic control and self-care behaviors, though their impact on psychological outcomes remains inconsistent.
AIMS:Type 2 diabetes mellitus is a major global public health concern closely associated with unhealthy dietary patterns. Medical nutrition therapy plays a central role in its prevention and management; however, assessing adherence remains challenging. This study aimed to develop and psychometrically evaluate the Type 2 Diabetes Nutrition Therapy Adherence Scale (DNTA-S), a culturally appropriate instrument for assessing adherence to nutrition therapy among individuals with type 2 diabetes. METHODS:This methodological and cross-sectional study was conducted with 420 adults diagnosed with type 2 diabetes. Content validity was assessed using the Davis technique based on expert evaluations. Construct validity was examined through exploratory and confirmatory factor analyses. Reliability was evaluated using Cronbach's alpha, split-half, and test-retest analyses. RESULTS:The final 20-item scale consisted of four dimensions. The four-factor structure explained 61.29% of the total variance, with acceptable factor loadings. Confirmatory factor analysis supported the structure and demonstrated good model fit (RMSEA=0.060; CFI=0.943). The overall Cronbach's alpha was 0.915, and subdimension reliability coefficients were within acceptable ranges. Test-retest reliability indicated excellent stability (ICC=0.95). CONCLUSIONS:The DNTA-S is a valid and reliable multidimensional instrument that captures key aspects of dietary adherence and may support both clinical practice and research.
AIMS:Digital health technologies including mobile apps, web portals, and connected devices can enhance diabetes care, but population-level data on their use and attitudes toward data sharing among U.S. adults with diabetes are limited. This study examined patterns of digital health use, online communication, and willingness to share health data. METHODS:Data were drawn from a national online survey conducted in March 2020, using the Qualtrics online panel with quota sampling on race/ethnicity, gender, education and age. Of 828 respondents, 121 reported a diabetes diagnosis and were included in the analysis. Measures included demographics, internet-connected device and health app use, health-related internet behaviors, and willingness to share data. RESULTS:Nearly all respondents reported daily internet use, but fewer than two-thirds used it for health purposes and only 56% had health-specific apps. Most common health purposes were searching for information (60%) or reviewing test results (42%). Data sharing was reported by 40% with providers and 36% with family. Engagement varied by age, education, employment, and insurance, but not by race or geographic region. CONCLUSIONS:Despite broad internet access, digital health engagement and trust in data-sharing among U.S. adults with diabetes remains limited, with gaps concentrated among older adults and those with lower socioeconomic resources.
INTRODUCTION:Sleep is increasingly recognized as a modifiable factor influencing metabolic and cardiovascular outcomes in type 2 diabetes mellitus (T2DM). Reliable sleep assessments are essential in primary care to assess sleep in T2DM. However, the stability of self-rated sleep measures in this group remains unclear. AIM:This study evaluated the temporal stability of the Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), and STOP-BANG questionnaire in T2DM patients. MATERIAL AND METHODS:This prospective observational study included 53 individuals with T2DM referred from Swedish primary care for OSA evaluation (median age 65, 53% male). A total of 109 eligible individuals were approached and 53 agreed to participate. Participants completed ESS, PSQI, and STOP-BANG twice with a median interval of 68.5 days. Stability was analysed using Spearman's rho, intraclass correlation coefficients (ICC), and Cohen's kappa. Systematic differences were assessed with the Wilcoxon signed-rank test, and the impact of interval duration on score stability was analysed using robust rank regression. RESULTS:ESS, PSQI, and STOP-BANG all showed significant test-retest stability. Spearman's rho was 0.73 for ESS, 0.78 for PSQI, and 0.81 for STOP-BANG (all p < 0.001), and Cohen's kappa at clinical thresholds was 0.62, 0.46, and 0.75, respectively. No systematic score drift was observed for ESS or PSQI; STOP-BANG exhibited a small mean decrease (-0.4 points, p < 0.01). No significant association was found between interval length and score differences. CONCLUSION:This study confirms the stability of ESS and PSQI in assessing sleep quality and sleepiness in patients with T2DM. STOP-BANG showed reasonable stability, with variations in snoring responses suggesting it may be more effective if administered prior to the clinical visit. Incorporating these validated tools into routine care could improve the management of sleep disturbances and their impact on metabolic health.
AIM:We aimed to determine the prevalence of undiagnosed impaired glucose metabolism (IGM) and metabolic syndrome (MetS) in men presenting with erectile dysfunction (ED) and to assess whether ED severity is associated with specific IGM subgroups. METHODS:605 consecutive men aged ≥ 18 years presenting with ED were evaluated for inclusion. Patients with known IGM, chronic diseases, antiandrogen use or prior testicular, pituitary, or prostate surgery were excluded. ED severity was assessed using the 5-item International Index of Erectile Function (IIEF-5). Clinical data, anthropometrics, and laboratory measurements were obtained. RESULTS:Of the 310 patients included in the study, MetS was identified in 94 (30.3%) and IGM in 82 (26.4%), including 28 newly diagnosed with diabetes mellitus (DM) (9.0%) and 54 with prediabetes (17.4%). Among patients with prediabetes, 29 (53.7%) had impaired fasting glucose (IFG), 4 (7.4%) had both IFG and impaired glucose tolerance (IGT), and 21 (38.9%) had HbA1c levels of 5.7-6.4%. IGM prevalence differed significantly by ED severity categories; 23 (28%) mild, 39 (47.6%) mild-to-moderate, 17 (20.7%) moderate, and 3 patients (3.7%) with severe ED (p = 0.042). Testosterone levels were significantly lower in patients with MetS (p < 0.001). IIEF-5 score demonstrated a statistically significant but modest ability to predict IGM and MetS (p = 0.008 and p = 0.047). While age was an independent predictive factor for the mild, mild-to-moderate, and moderate ED categories, MetS and prediabetes were independently predictive in patients with mild-to-moderate ED. CONCLUSIONS:Newly diagnosed IGM and MetS were identified in nearly one-third of patients presenting with ED, most frequently in those with mild-to-moderate symptoms. These findings suggest that ED, particularly in milder forms, may indicate underlying metabolic risk and warrant careful evaluation.
In a retrospective cohort of 5801 births from individuals with gestational diabetes, 363 (6%) completed 4-12-week postpartum screening for GDM and had evidence of ongoing clinical care in our system. Among these, only half completed recommended type 2 diabetes screening 1-3 years postpartum. Screening rates did not vary by demographic or clinical factors and were primarily performed by primary care clinicians, highlighting persistent gaps in long-term diabetes surveillance after gestational diabetes.
OBJECTIVE:This study aimed to assess whether visceral fat area (VFA) enhances prediction of diabetic microvascular disease (DMV) beyond the triglyceride-glucose (TyG) index in a county-level population of individuals with type 2 diabetes mellitus. METHODS:A cross-sectional study was conducted among 1042 adults with type 2 diabetes between 2022 and 2025. DMV was defined as the presence of diabetic retinopathy, chronic kidney disease, or diabetic peripheral neuropathy. Multivariable logistic regression analysis, receiver operating characteristic curve analysis, decision curve analysis, and calibration plots were applied to evaluate model performance. The predictive value of the TyG index was first assessed, after which the incremental contribution of VFA was quantified using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS:After adjustment for established risk factors, each 1-unit increase in TyG was associated with 31% higher odds of DMV (OR 1.31, 95% CI 1.04-1.65). VFA was not independently associated with DMV (OR 1.00, 95% CI 0.99-1.00). The area under the receiver operating characteristic curve (AUC) was 0.740 for the TyG-plus-covariates model and 0.741 for the TyG-plus-VFA-plus-covariates model. The categorical NRI was 0.8% (p = 0.310), and the IDI was 0.04% (p = 0.258). Subgroup analyses for diabetic retinopathy, chronic kidney disease, and diabetic peripheral neuropathy Subgroup analyses for diabetic retinopathy, chronic kidney disease, and diabetic peripheral neuropathy yielded consistent results: categorical NRI, IDI, and ΔAUC 95% CIs all crossed zero. Sensitivity analyses supported the primary findings. CONCLUSIONS:The TyG index was independently associated with diabetic microvascular disease, whereas the addition of visceral fat area provided negligible incremental predictive value beyond established risk factors.
AIMS:This study aims to evaluate the impact of alarm activation on Continuous Glucose Monitoring (CGM) metrics in people with type 2 diabetes (PwT2D) using the FSL2 system in a primary care setting. METHODS:A cross-sectional study was conducted including PwT2D who were treated with insulin, used FreeStyle Libre 2 system and were managed at the Cafam FreeStyle Libre (FSL) Program, in Bogotá, Colombia. All patients received education upon enrolment and were followed up by a team of primary care physicians (PCP). Data were obtained from the LibreView and LibreLens platforms. CGM metrics based on alarm usage were analyzed. Additionally, glycemic control and adherence metrics were evaluated classifying patients into three groups: adequate control (TBR>70%,TBR<4%), high-risk of hypoglycemia (TBR≥4%), or high-risk of hyperglycemia (TIR≤70%,TBR<4% and TAR>25%). RESULTS:Analysis of 221 individuals (median age 61; IQR 51-71) revealed that only 14.5% had active glucose alarms. Those with active alarms showed a non-significant trend toward improved glycemic control (median TIR 65% [52.8-79.3%] vs 61% [42.5-75%], p = 0.107). Glycemic risk stratification showed that 53% of participants were at high risk for hyperglycemia and 19% at high risk for hypoglycemia, with only 28% achieving adequate control. No CGM adherence differences were found between groups. CONCLUSION:Patients with active alarms tend to have a higher TIR, suggesting that alarm activation may positively influence glycemic control in this population. However, given the low rate of alarm utilization, structured training to promote alarm use among PwT2D under PCPs follow-up is essential.
Aim To explore the occurrence of diabetes distress and its associations with diabetes self-management, sociodemographic factors, treatment regimen and late complications in individuals with type 2 diabetes in Sweden. Methods A cross-sectional study was conducted among 193 adults with type 2 diabetes between 2021 and 2023. Data were collected through questionnaires and linked to the Swedish National Diabetes Registry. Diabetes distress was assessed using the Diabetes Distress Scale (DDS-17), and self-management was measured with the Diabetes Self-Management Questionnaire (DSMQ). Linear regression analyses were performed with DDS scores as the outcome variable. Results Moderate or high levels of diabetes distress were reported by 47.6% of participants, with regimen-related distress being the most prevalent subtype. Higher levels of diabetes distress were significantly associated with poorer diabetes self-management, particularly regarding dietary control, physical activity, and healthcare use. Having a partner was associated with lower regimen-related distress. No significant associations were observed between diabetes distress and treatment regimen or diabetes-related complications. Conclusions Diabetes distress appears to be high among individuals with type 2 diabetes in Sweden and is closely linked to self-management. Clinical indicators, such as treatment regimens or diabetes complications alone, cannot reliably identify individuals experiencing distress. These findings underscore the need for systematic screening.
AIMS:To evaluate the impact of sarcopenia on clinical outcomes in patients with diabetes through systematic review and meta-analysis. METHODS:A systematic search across nine English and Chinese databases until December 10, 2025, identified eligible cohort studies. Two investigators independently screened studies, extracted data, and assessed quality using the Newcastle-Ottawa Scale. A random-effects model was employed for the meta-analysis of primary outcomes. Secondary outcomes were summarized descriptively. RESULTS:Seventeen cohort studies, involving a combined cohort of 471,986 patients with diabetes, were included. Meta-analysis showed that sarcopenia significantly increased the risk of all-cause mortality (HR = 1.95, 95% CI: 1.40-2.73), cardiovascular disease (HR = 1.65, 95% CI: 1.01-2.68), and hospital readmission (OR = 2.20, 95% CI: 1.05-4.61) in this population. Subgroup analysis indicated a higher mortality risk among older patients (HR = 2.39). The descriptive synthesis indicated that sarcopenia was also associated with an increased risk of diabetic kidney disease, disability, cognitive decline, depressive symptoms, fragility fractures, and sleep disorders. CONCLUSIONS:Sarcopenia is a significant risk factor for multiple adverse clinical outcomes in patients with diabetes. These findings support the role of sarcopenia as a prognostic marker for risk stratification in diabetes management.
AIMS:We assessed the prevalence and risk factors of erectile dysfunction (ED) in men with type 2 diabetes (T2DM) compared with men without diabetes in Catalonia, Spain. METHODS:This cross-sectional study used routinely collected primary care data from the SIDIAP database (covering ∼80% of the Catalan population) from 1st January 2010-30 th June 2023. Men ≥ 18 years with at least one primary care visit and one recorded laboratory test were included. T2DM was identified through ICD-10 codes, antidiabetic drugs, or HbA1c ≥ 6.5%; men without diabetes had no recorded diagnosis or criteria for any diabetes. ED was defined by ICD-10 codes (F52, N48.9) and/or prescriptions for approved ED treatments. Sociodemographic, lifestyle, clinical and laboratory data, comorbidities and medications were extracted. Multivariable logistic regression assessed factors associated with ED. RESULTS:Among 659,501 men (177,380 with T2DM; 492,121 without), overall ED prevalence was 9.5%. Prevalence was 1.5-fold higher in T2DM (12.6%) than in men without diabetes (8.3%), peaking at 55-64 years. Older age, longer diabetes duration, poorer glycaemic control, smoking, high-risk alcohol use, hypertension, dyslipidaemia, cardiovascular and microvascular disease, obesity and depression were independently associated with ED. CONCLUSIONS:Men with T2DM show markedly higher ED prevalence and multiple cardiometabolic risk factors. ED remains under-recognised and should be systematically assessed in primary care as both a complication and a clinical marker of cardiometabolic risk.
